Accelerated Flight Control LAW Clearance Using Stores Grouping Concept

5th International Conference on Advances Advances in in Control Control and and 5th International Conference on Optimization of Dynamical Systems Optimization of Systems 5th International Conference on Advances Advances in Optimization of Dynamical Dynamical Systems February 18-22, 2018. Hyderabad, India 5th International Conference on in Control Control and and February 18-22, 18-22, Dynamical 2018. Hyderabad, Hyderabad, India Available online at www.sciencedirect.com Optimization Systems February 2018. India Optimization of of Dynamical Systems February February 18-22, 18-22, 2018. 2018. Hyderabad, Hyderabad, India India

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IFAC PapersOnLine 51-1 (2018) 365–370

Accelerated Accelerated Flight Flight Control Control LAW LAW Clearance Clearance Using Using Stores Stores Accelerated Flight Control LAW Clearance Using Grouping Concept Accelerated Flight Control LAW Clearance Using Stores Stores Grouping Concept Grouping Grouping Concept Concept

Sreelalitha B *, Jayalakshmi M **, Lakshmi P***, Vijay V Patel**** Sreelalitha Sreelalitha B B *, *, Jayalakshmi Jayalakshmi M M **, **, Lakshmi Lakshmi P***, P***, Vijay Vijay V V Patel**** Patel**** Sreelalitha B *, Jayalakshmi M **, Lakshmi P***, Vijay V Sreelalitha B *, Jayalakshmi M **, Agency, LakshmiP.B.1718, P***, Vijay V Patel**** Patel**** India IFCS Directorate, Aeronautical Development Bangalore-560017, IFCS Directorate, Directorate, Aeronautical Aeronautical Development Development Agency, Agency, P.B.1718, P.B.1718, Bangalore-560017, Bangalore-560017, India India IFCS * e-mail: [email protected], [email protected] IFCS Aeronautical Development Agency, P.B.1718, Bangalore-560017, India * e-mail: e-mail: [email protected], [email protected] * [email protected], [email protected] IFCS Directorate, Directorate, Aeronautical Development Agency, P.B.1718, Bangalore-560017, India **e-mail: [email protected], [email protected] ** e-mail: [email protected], [email protected] **e-mail: [email protected], [email protected] **e-mail: [email protected], [email protected] e-mail: [email protected], [email protected] ***e-mail: [email protected], [email protected] **e-mail: [email protected], [email protected] ***e-mail: [email protected], [email protected] ***e-mail: [email protected], [email protected] **e-mail: [email protected], [email protected] ****e-mail: [email protected], [email protected] ***e-mail: [email protected], [email protected] ****e-mail: [email protected], [email protected] ****e-mail: [email protected], [email protected] ***e-mail: [email protected], [email protected] ****e-mail: ****e-mail: [email protected], [email protected], [email protected] [email protected] Abstract: Current fighter aircraft are demanded to feature multirole capability with large number of Abstract: Current Current fighter fighter aircraft are are demanded to to feature feature multirole multirole capability capability with with large large number number of of Abstract: different external stores to aircraft be integrateddemanded on the aircraft. These stores represent air to air, air to surface Abstract: Current fighter aircraft are demanded to feature multirole capability with large number of different external stores to be integrated on the aircraft. These stores represent air to air, air to surface different external stores to be integrated on the aircraft. These stores represent air to air, air to surface Abstract: Current aircraft areofdemanded to feature multirole with large of weapons etc., whichfighter have wide range aerodynamic characteristics as capability well as different massnumber properties different stores be on the These stores air air, air to surface weapons external etc., which which haveto wide range of of aerodynamic aerodynamic characteristics asrepresent well as as different different mass properties weapons etc., have wide range characteristics as well mass different external to be integrated integrated onrequirement the aircraft. aircraft. stores represent air to to handling air, air properties toqualities, surface (CG, mass, inertia).stores This conflicts with the ofThese adequate stability, optimum weapons etc., which have wide range aerodynamic as as different mass (CG, mass, mass, inertia). This conflicts withof the requirementcharacteristics of adequate adequate stability, stability, optimum handling qualities, (CG, inertia). This with requirement of handling qualities, weapons etc., which haveconflicts widecharacteristics range ofthe aerodynamic as well well optimum as different massanproperties properties superior agility and robustness over the characteristics entire flight envelope. Especially with unstable (CG, mass, inertia). This conflicts with the requirement of adequate stability, optimum handling superior agility and robustness robustness characteristics over the the entire entire flight envelope. envelope. Especially with an anqualities, unstable superior agility and characteristics over flight Especially with unstable (CG, mass, inertia). This conflicts with the requirement of adequate stability, optimum handling qualities, aircraft it is impossible to fulfill these requirements for all stores with just one set of control laws. superior and robustness characteristics over the entire envelope. Especially with an unstable aircraft it itagility is impossible impossible to fulfill fulfill these requirements requirements for all allflight stores with just just one set set of of control laws. aircraft is to these for stores with one control laws. superior agility and robustness characteristics over the entire flight envelope. Especially with an unstable Therefore, automatic reconfiguration in control laws based on similar flight dynamic characteristics is aircraft it is impossible to fulfill these requirements for all stores with just one set of control laws. Therefore, automatic reconfiguration in control laws based on similar flight dynamic characteristics is Therefore, reconfiguration iniscontrol laws to based similar is aircraft out. it isautomatic impossible to fulfill these requirements forreconfigure allonstores with justdynamic one set characteristics of control carried Stores grouping concept often used theflight flight control laws with laws. store Therefore, automatic reconfiguration in control laws based on similar flight dynamic characteristics is carried out. Stores grouping concept is often used to reconfigure the flight control laws with store carried out.automatic Stores conceptiniscontrol often used to reconfigure theflight flightand control laws with store Therefore, lawsdynamics based oncharacteristics similar dynamic characteristics is information in order grouping toreconfiguration normalize/optimize the flight corresponding support carried out. Stores concept is often used to reconfigure the flight control laws with store information in order grouping to normalize/optimize normalize/optimize the flight flight dynamics characteristics and corresponding support information in order to the dynamics characteristics and corresponding support carried out. Stores grouping concept is often used to reconfigure the flight control laws with store towards flight clearance. The flight clearance is a tedious procedure as a host of criteria need to be information in order to the flight dynamics characteristics and corresponding support towards flight flight clearance. The flight flight clearance clearance is aa tedious tedious procedure as aa host host of criteria criteria need to towards clearance. The is as of need to be be information order to normalize/optimize normalize/optimize the conditions flight dynamics characteristics and corresponding support evaluated at in a large number of nominal flight for procedure different airframe configurations, multiples towards clearance. The clearance is aa tedious as aa host of criteria need to be evaluatedflight at aa large large number of flight nominal flight conditions conditions for procedure different airframe airframe configurations, multiples evaluated at number of nominal flight for different configurations, multiples towards flight clearance. The flight clearance is tedious procedure as host of criteria need to be thereof with tolerances and failures. This paper describes how various stores configurations can be evaluated at aatolerances large number nominal flight conditions for different airframe configurations, thereof with with tolerances and of failures. This paper describes how various various stores configurationsmultiples can be be thereof and failures. This paper describes how stores configurations can evaluated at large number of nominal flight conditions for different airframe configurations, multiples grouped together in order to accelerate the clearance process. thereof tolerances failures. This paper grouped with together in order orderand to accelerate the clearance process. how grouped together in to accelerate process. thereof with tolerances and failures. the Thisclearance paper describes describes how various various stores stores configurations configurations can can be be Keywords: Aircraft, Control law, clearance, stores grouping grouped together in order to accelerate the clearance process. © 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. grouped together in order to accelerate the clearance process. Keywords: Aircraft, Control law, clearance, stores grouping Keywords: Aircraft, Control law, clearance, stores grouping Keywords: Laws. Control Laws are implemented in Simulink and Keywords: Aircraft, Aircraft, Control Control law, law, clearance, clearance, stores stores grouping grouping Laws. Control Laws are implemented in and Laws. Control areSIMULINK implemented in Simulink Simulink 1. INTRODUCTION MATLAB code Laws runs the model/s iterativelyand in 1. INTRODUCTION Laws. Control Laws are implemented in Simulink and MATLAB code runs the SIMULINK model/s iteratively in INTRODUCTION MATLAB code The runsresults the model/s iteratively in Laws. Control Laws areSIMULINK implemented inplots Simulink and the batch mode. are presented as in order to 1. INTRODUCTION MATLAB code runs the SIMULINK model/s iteratively in the batch mode. The results are presented as plots in order to 1. INTRODUCTION the batch mode. The results are presented as plots in order to MATLAB code runs the SIMULINK model/s iteratively in know the trends and likely problem areas in the flight Modern fighter aircraft is intentionally designed quickly the batch mode. The results are presented as plots in order to quickly know the trends and likely problem areas in the flight Modern fighter aircraft is intentionally designed quickly know the trends and likely problem areas in the flight the batch mode. The results are presented as plots in order Modern fighter aircraft is intentionally designed The results are also presented as tables in order to to aerodynamically unstable to improve performance and envelope. quickly know the trends and likely problem areas in the flight envelope. The results are also presented as tables in order to Modern fighter aircraft is intentionally designed aerodynamically unstable to improve performance and envelope. The results are also presented as tables in order to quickly trends and likelyThe problem the flight aerodynamically performance and Modern fighter unstable aircraft to artificial isimprove intentionally designed theknow exactthe numerical values. secondareas majorinstep is the manoeuvrability. Therefore, stability must be know envelope. The results are also presented as tables in order to know the exact numerical values. The second major step is the aerodynamically unstable to improve performance and manoeuvrability. Therefore, artificial stability must be know the exact numerical values. The second major step is the envelope. The results are also presented as tables in order to manoeuvrability. Therefore, artificial stability be clearance through non-linear offline simulation. Here aerodynamically unstable tocontrol improve performance and provided by a redundant flight system whichmust becomes know the exact numerical values. The second major step is the clearance through non-linear offline simulation. Here manoeuvrability. Therefore, artificial stability must be provided by a redundant flight control system which becomes clearance through non-linear offline simulation. Here know the exact numerical values. The second major step is the provided by a redundant flight control system which becomes manoeuvrability. Therefore, stabilityanalysis must and be MATLAB is used as interfacing tool to set flight condition, safety critical system. Prior to artificial flight, extensive through offline Here MATLAB is used as as non-linear interfacing tool tool to set setsimulation. flight condition, condition, provided by redundant flight which becomes safety critical system. Prior Prior tocontrol flight, system extensive analysis and clearance MATLAB is used interfacing to flight clearance through offline simulation. Here safety system. to flight, extensive analysis and provided by aa need redundant flight control system becomes pilot input which will non-linear be used by validated and proven 6 DOF groundcritical tests to be done to prove towhich the clearance MATLAB is used as interfacing tool to set flight condition, pilot input which will be used by validated and proven 6 DOF safety critical system. to flight, extensive analysis and ground tests need need to Prior be done done to prove prove to the the clearance pilot input which will be used by validated and proven 6 DOF MATLAB is used as interfacing tool to set flight condition, ground tests to be to to clearance safety critical system. Prior to flight, extensive analysis and offline non-linear simulation FORTRAN code authorities, that the aircraft can be flown safely throughout simulation pilot which will be by validated and proven 6 DOF offline FORTRAN code ground tests need be to prove to clearance authorities, that the to aircraft can be be flown safely throughout simulation offline non-linear simulation FORTRAN code pilot input input willnon-linear beofused used bysimulation validatedCLAW and proven authorities, that the aircraft can ground tests need to be done done to flown prove safely to itthe the clearance simulation which alsowhich consists FORTRAN code.6 DOF The the entire flight envelope. For this purpose, isthroughout necessary simulation offline non-linear simulation FORTRAN code which also consists of FORTRAN CLAW code. The authorities, that the aircraft can be flown safely throughout the entire flight envelope. For this purpose, it is necessary which also consists of FORTRAN CLAW code. The simulation offline non-linear simulation FORTRAN the entire flight envelope. For this purpose, it is necessary authorities, that the aircraft can be flown safely throughout tool also reads FORTRAN generated output code files that the controller meets all the stability, performance and MATLAB which also consists of FORTRAN CLAW code. The MATLAB tool also reads FORTRAN generated output files the entire flight envelope. For this purpose, it is necessary that the controller meets all the stability, performance and MATLAB tool also reads FORTRAN generated output files which also consists of FORTRAN CLAW code. The that the controller meets all the stability, performance and the entire flight envelope. For this purpose, it is necessary results are analysed. The entire program automatically handling requirements for various symmetric and asymmetric and MATLAB tool also reads FORTRAN generated output files and results are analysed. The entire program automatically that the controller meets all the stability, performance and handling requirements for various symmetric and asymmetric and results are analysed. The entire program automatically MATLAB tool also reads FORTRAN generated output files handling requirements for various symmetric and asymmetric that the controller meets all the stability, performance and runs in batch mode. stores configurations. and results are analysed. The The entire entire program program automatically automatically runs results in batch batchare mode. handling requirements stores in mode. and analysed. stores configurations. configurations. handling requirements for for various various symmetric symmetric and and asymmetric asymmetric runs runs in batch mode. stores configurations. runs in batch mode. storesclearance configurations. The process for the flight control laws consists of Fighter aircraft capabilities includes carriage of wide variety The clearance process for the control laws consists of Fighter aircraft aircraft capabilities includes includes carriage of of wide wide variety variety The clearance the flight flight as control of Fighter two major stepsprocess broadlyforcategorized linearlaws and consists non-linear. of stores (bombs,capabilities missiles, pods, dropcarriage tanks, cameras etc.,) for The clearance process for the flight control laws consists of two major steps broadly categorized as linear and non-linear. Fighter aircraft capabilities includes carriage of wide variety of stores (bombs, missiles, pods, drop tanks, cameras etc.,) for two major steps broadly categorized as linear and non-linear. The clearance process for the flight control laws consists of of stores (bombs, missiles, pods, drop tanks, cameras etc.,) for Fighter aircraft capabilities includes carriage of wide variety In the linear domain, stability and performance including various mission requirements. Clearance of flight control laws two major steps broadly categorized as linear and non-linear. In the linear domain, stability and performance including of stores (bombs, missiles, pods, drop tanks, cameras etc.,) for various mission requirements. Clearance of flight control laws In the linear domain, stability and performance including two major steps broadly categorized as linear and non-linear. various mission requirements. Clearance of flight control laws of stores (bombs, missiles, pods, drop tanks, cameras etc.,) for quantitative handling qualities of the controlled airframe are for each store needs to be done for it to be airborne. Typically, In the linear domain, stability and performance including quantitative handling qualities of the controlled airframe are various mission requirements. Clearance of flight control laws for each store needs to be done for it to be airborne. Typically, quantitative handling qualities of the controlled airframe are In the linear domain, stability and performance including for each store needs to be done for it to be airborne. Typically, various mission requirements. Clearance of flight control laws evaluated across the flight envelope. MATLAB-Simulink is the number of flight conditions would exceed 25 thousand for quantitative handling qualities of controlled airframe are evaluated across across the flight flight envelope. MATLAB-Simulink is for store to be for it be airborne. Typically, the number of flight conditions would 25 thousand for evaluated the MATLAB-Simulink is quantitative handling qualities of the thecontrol controlled the number of needs flight(Mach conditions would exceed 25 Nz thousand for for each each store needs to be done done for it to toXexceed beAoA airborne. Typically, used for linear assessment ofenvelope. flight laws airframe and also are for conditions X altitude or grid) and evaluated acrossassessment the flight flight of envelope. MATLAB-Simulink is nominal used for for linear linear assessment ofenvelope. flight control control laws and and also also for for the number of flight conditions would exceed 25 thousand for nominal conditions (Mach X altitude X AoA or Nz grid) and used flight laws evaluated across the MATLAB-Simulink is nominal conditions (Mach X altitude X AoA or Nz grid) and the number of flight conditions would exceed 25 thousand for the analysis of results. First, the linear models (linear multiples thereof with tolerances and failures for a particular used for linear linearof assessment of flight flight control laws and also also for multiples the analysis analysis ofassessment results. First, First, thecontrol linearlaws models (linear nominal conditions (Mach X altitude X AoA or Nz grid) and multiples thereof with tolerances and failures for a particular the results. the linear models (linear used for of and for thereof with tolerances and failures for a particular nominal conditions (Mach X isaltitude X AoA orand Nz repetitive grid) and representation of aircraft) at different flight conditions are configuration. The clearance a very laborious the analysis of the linear (linear representation of results. aircraft) First, at different different flight models conditions are multiples thereof tolerances and failures for aa particular configuration. Thewith clearance is aa very very laborious and repetitive representation of aircraft) at flight conditions are the analysis of results. First, thewith linear models (linear configuration. The clearance is and repetitive thereof with tolerances andtolaborious failures for particular generated by interfacing MATLAB FORTRAN based 6 multiples process which takes several weeks complete. The entire representation of aircraft) at different flight conditions are generated by interfacing MATLAB with FORTRAN based 6 configuration. The clearance is a very laborious and repetitive process which takes several weeks to complete. The entire generated by interfacing MATLAB with FORTRAN based 6 representation of aircraft) at different flight conditions are process which takes several weeks to complete. The entire configuration. The clearance is a very laborious and repetitive DOF simulation software code. The latter code trims the process needs to be repeated for various stores configurations generated by interfacing MATLAB with FORTRAN based 6 DOF simulation software code. The latter code trims the process which takes several weeks to complete. The entire needs to be repeated for various stores configurations DOF simulation software code. The latter code trims the generated by interfacing MATLAB with FORTRAN based 6 process needs to be repeated for various stores configurations which takes several weeks to complete. The entire aircraft for a particular flight condition and generates a small separately which exhausts the time as well as resources to DOF simulation software code. The latter code trims the aircraft for aa particular flight condition and generates aa small process needs to be repeated for various stores configurations separately which exhausts the time as well as resources to aircraft for particular flight condition and generates small DOF simulation software code. The latter code trims the separately which exhausts the time as well as resources to process needs to be repeated for various stores configurations perturbation model by solving the 6 DOF motion equations of great extent. aircraft for a particular flight condition and generates a small perturbation model by solving the 6 DOF motion equations of separately which exhausts the time as well as resources to great extent. perturbation model by solving the 6 DOF motion equations of aircraft for a particular flight condition and generates a small great extent. separately which exhausts the time as well as resources to the aircraft. Those models are used to assess the Control perturbation model by solving the 6 DOF motion equations of the aircraft. Those models are used to assess the Control great extent. the aircraft. Those models are used to assess the Control perturbation model by solving the 6 DOF motion equations of great extent. the the aircraft. aircraft. Those Those models models are are used used to to assess assess the the Control Control Copyright © 2018 IFAC 381 Copyright © 2018, 2018 381 Copyright 2018 IFAC IFAC 381 Hosting by Elsevier Ltd. All rights reserved. 2405-8963 © IFAC (International Federation of Automatic Control) Copyright © 2018 IFAC 381 Peer review under responsibility of International Federation of Automatic Copyright © 2018 IFAC 381Control. 10.1016/j.ifacol.2018.05.051

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The results generated in both these major steps are automatically used by a plotting tool in MATLAB to generate photo ready outputs which includes contour maps and numerical data tables. This entire process is extremely time consuming. The obvious requirement is to accelerate the entire flight control law clearance process. The stores grouping of different stores is carried out to identify the worst case (with respect to aerodynamic behaviour and CG location influence) and carry on the detailed clearance process only for that worst case store. This helps to clear the entire stores group and reduces the results generation and analysis time significantly. The current paper explains the process of stores grouping concept from CLAW perspective with the objective of accelerating the flight control law clearance process. This paper also gives exposure about challenges involved and the volume of the data generation required in order to clear the flight control system. 2.

The current generation, high performance fighter aircraft cannot be flown directly by pilot as they are often designed to be naturally unstable to improve the performance across the flight envelope. Therefore, redundant electronic Flight Control System (FCS) with control algorithms running on digital computers are needed to provide the required stability, performance and handling characteristics. The design and development of FCS for a modern high performance fighter aircraft is a complex, multi-disciplinary task. The design and validation of the flight control laws (CLAW) is an important part of the FCS design. It involves many stages from concept to validation and the problems involved in the process make it lengthy and costly. The formal clearance process for flight control laws starts once the controller design is considered to be sufficiently mature.

CLAW FUNCTIONALITY

LINEAR ASSESSMENT HQ / STABILITY

NOMINAL

NONLINEAR ASSESSMENT PARAMETER EXCEEDANCE

FAILURE/TOLERANCE (Airdata/Aerodata)

NOMINAL and AOA FAIL

a) Generation of an analysis model- This involves establishing a full-size non-linear model which includes all parametric uncertainties. Small perturbation (linear) models are derived from the nonlinear model by trimming and linearizing.

c) Trend studies on the effect of uncertainties- This involves studying the effects of the various uncertain parameters on the stability and handling of the aircraft. d) Linear stability analysis- This involves the calculation of open-loop stability margins for a grid of flight envelope points and for different uncertainties and under failures. e) Linear handling analysis- This consists of evaluation of the appropriate time and frequency domain criteria. f) Offline nonlinear simulation analysis- This involves assessing the general flying characteristics with and without uncertainties and failures and the derivation of manoeuvre limitations. g) Real time evaluation analysis- Pilot in loop evaluation of handling qualities in real time environment enables the designer to identify deficiencies in the total flight control system (including the pilot) prior to actual flight.

Industrial flight clearance process was described by Andras Varga et.al.(2002). A formal clearance of CLAW is required before flight testing. Clearance of flight control laws needs to be done for combination of different store configurations and large number of parameter variations such as mach, altitude, load factor, mass and CG variations due to fuel depletion, etc., and uncertainties over a large flight envelope. AERO DATABASE and UPDATES

The current industrial process of clearance of CLAW has the following steps:

b) Identifying the airframe characteristics including deficiencies- Studies are carried out to produce the plots of aerodynamic stability and control derivatives of the unaugmented aircraft, plots of open-loop eigenvalues etc. to provide the designer with a good appreciation of the plant (uncontrolled aircraft).

INDUSTRIAL CLEARANCE PROCESS

HARDWARE ASSUMPTIONS

The clearance provides the information about the flight envelope limits regarding speed, altitude, angle of attack and load factor and also about the allowed manoeuvres that can be flown and restrictions under nominal as well as various failure scenarios. The control law clearance process pictorially is given in Fig.1.

h) Clearance report- This contains the derivation and visualization of manoeuvre and flight envelope limitations based on the linear, nonlinear and real time simulation analysis results. This is a summary report consisting of all the clearance criteria and any CLAW restrictions based on the assessment.

MASS CG DATA

3.

REAL TIME EVALUATION BY BY PILOT IN SIMULATOR - NOMINAL - FAILURE

CLAW CLEARANCE CRITERIA AND TASKS

The basic aim of the clearance is to prove that the aircraft is stable over the entire flight envelope with sufficient stability margins for a given set of uncertainties and various failure scenarios.

CO-ORDINATION OF ALL CLEARANCE DOCUMENTS RELEASE OF FINAL COMPLIANCE DOCUMENT

Fig.1. Industrial Flight Control Law Clearance Process

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Level 3 Controllable

Level 2 Acceptable

Level 1

Satisfactory

1 2 3

4. The closeness parameter which quantifies gain and phase margin stability margin requirement together is calculated breaking the loop at the input of controller as shown in Fig 4. The open loop frequency response (L=P*C) is plotted as Nichols plot in Figure 9. The ellipse corresponds to closeness parameter 1 and it assures gain margin of 6dB and phase margin of 35° [Girish Deodhare et.al (1998)].

Uncontrollable

or

Unacceptable

or Unsatisfactory or

4 5 6

7 8 9

5. Some of the handling qualities parameters used for the clearance considered from MIL-9490D (1975), MIL1797A (1990) are outlined. Average Phase Rate (which accounts for the additional phase lag introduced by FCS models), Pitch rate sensitivity (which is the pitch rate amplitude per pound of stick force), Maximum Pitch Acceleration (maximum pitch acceleration evaluated for unit step pitch stick input), Control Anticipation Parameter (CAP), Flight path time delay (Flight path time delay is calculated from flight path angle step response), Pitch Attitude Drop back (pitch attitude drop back measured from the pitch attitude time response). Heavy

10

Fig. 2. Pilot Decision Rating Sequential Apart from the stability requirements, the aircraft must fulfil the requirement of good handling, and, the clearance assessment should show that the pilot can control the aircraft precisely and easily to accomplish the mission. Handling qualities are quantitative performance specifications extracted from documents like the MIL-F-8785C (1980), MIL-1797A (1990) standards. These handling qualities indirectly serve as a measure for the mental and physical workload encountered by the pilot during the execution of a particular task. As per the MIL-STD-1797A (1975), there are 3 levels of analytical flying qualities as described in Fig.2.

Heavy Mass Mid Mass (Aft CG)

Level 1- Handling clearly adequate for the mission flight phase.

Mid Mass

FUEL FLOW with DIFFERENT FUEL SLOSHING ANGLES

MASS (Forward

Level 2- Handling adequate but some increase in the pilot workload and / or degradation in the mission effectiveness exists.

CG)

Light Mass NORMAL

FUEL Light CG FWD AFT Fig.3. Typical Mass CG Configuration with different fuel pitch angles.

Level 3- Aircraft can be controlled but pilot workload is excessive and / or mission effectiveness is inadequate. Nonlinear, non-real time simulation is used for the detailed investigation of problem areas found in the linear evaluation. It is also used to check the effect of nonlinearities such as rate and position saturation, dead zones etc., on aircraft stability, to ensure that the aircraft angular rates and accelerations are within structural limits and to decide whether the CLAW is cleared from the designer’s side. Different stability and handling (frequency domain and time domain) criteria that are used for the clearance purpose are,

For control law clearance in linear and nonlinear domains of a particular store configuration, some fuel states (name so because of mass change due to fuel depletion) are considered based on mass-CG properties with different fuel pitch angles (based on fuel sloshing). Generally, for clearance of nominal configuration, at least four fuel states are considered. Typical mass centre of gravity (CG) variation of one stores for different fuel pitch angle is given in Fig.3. Selected fuel states (Take off CG, Aft CG, Landing CG and Forward CG) for nominal clearance are marked in Fig.7.

1. Gain Margin (GM) in pitch, roll and yaw axes - Gain Margin of at least ±6 dB 2. Phase Margin (PM) in pitch, roll and yaw axes - Phase Margin greater than 35° 3. Closeness Parameter (CLPAR) in pitch, roll and yaw axes- This parameter is introduced to automate the assessment of the gain and phase margins at a large number of flight conditions. This single parameter gives complete information about both the gain and phase margins. The definition of “Closeness parameter” is described in Girish Deodhare et.al (1998).

367

4.

STORES GROUPING PROCESS

Break the loop for Closeness parameter (Clpar) calculation

C2 Command I/P

C1

P2 P1

Uncertainties

Sensor Feedback Fig. 4. Plant and Controller Block Diagram

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4.1 Aerodynamic pre-processing with respect to station

The P1 in Fig.4. represents Plant without external stores configuration, however it has uncertainties due to fuel consumption, missile fired (CG, inertia and aerodynamic configuration). C1 is the corresponding Controller which meets the stability requirement with uncertainties. When a new store is added at any station, e.g., at midboard, then plant aerodynamics changes from P1 to P2. Since C1 is designed to handle the uncertainties on P1, it will not able to give same performance and robustness on P2. Therefore, a need arises to reconfigure at least few gains of C1 to extract maximum performance benefits without affecting handling quality requirements with external stores such as tighter limits on ‘g’, lower Angle of Attack (AoA) envelope due to external stores etc. Thus, C1 is reconfigured as C2 with the help of certain events which are set based on presence of external stores. The reconfigured controller C2 can handle variation of plant P2 due to different stores at midboard location which are grouped based on their aerodynamics or mass CG, inertia variation.

The following aspects with respect to external stores have to be considered as part of aerodynamic pre-processing. Especially in transonic regions small differences might have large implications due to different shock shapes/shock interactions  Stores on one station might suppress effects of other stores, depending on size and shape of the stores  The store grouping should also cover asymmetric configurations along with release sequences  Similarity has to be proven within the entire relevant speed/Mach range  Tolerances, which are applied within the clearance processes, may give an indication, which stores can be grouped For a typical fighter aircraft IB (inboard), OB (outboard), MB (mid board), UF (under fuselage) are the stations, where stores are allowed to be carried. Stores grouping basically is done based on the location of the store on aircraft. Stores which cannot be combined due to too different aerodynamic characteristics will be handled by store adaptation within the flight control laws. Flight mechanic parameters such as pitching moment coefficient as a function of angle of attack, rolling moment and yawing moment coefficients as a function of angle of sideslip (beta), etc., study of different stores configurations at different stations are compared.

The open loop bode plot for q to δe transfer function for a particular flight condition is shown in Fig. 5a (Magnitude) and Fig. 5b (Phase). The frequency response shows significant variation for plant P2 due to CG as well as aerodynamics.

Typical classification of stores grouping based on the station is shown in Fig.6. There are different types of configurations like clean (no stores), normal stores and heavy stores. It is grouped as per the station position with similar aerodynamic properties. For e.g., in the mid board station, M1, M2 and M3 are considered based on flight mechanics study from M1 to M10 store configurations. 4.2 Based on Mass- CG scaling Fig. 5a. Magnitude plots of q to δe Open Loop Transfer Frequency Response

Gain scaling with availability of stores is carried out for store adaptation in the control law. Following are the reasons for gain scaling for store adaptation.  Inertia adaptation for disturbance moment compensation.  Transformation of load factor signals to flow angle signals for feedback or schedule application for mass variation. Compensate CG effects on the aircraft to optimise/normalise handling and agility. Grouping of stores at single location is basically done with mass-CG variations and study of flight mechanics parameters of similar category of stores at a single station for stores control law clearance. Some fuel states (particular mass CG information) are considered for stores grouping from massCG variation study, flight mechanics study, linear analysis and nonlinear analysis.

Fig. 5b. Phase plots of q to δe Open Loop Transfer Frequency Response 384

5th International Conference on Advances in Control and Optimization of Dynamical Systems Sreelalitha B et al. / IFAC PapersOnLine 51-1 (2018) 365–370 February 18-22, 2018. Hyderabad, India

in longitudinal and lateral directions given in Fig.8 for M1, M2, M3 and M4 configurations.

Types of Stores Clean (no Stores) F1

F2

normal Stores Wing Stores

U1

M1 M2

F3 U3 F4

All Stores populated

Fuselage Stores

U2

369

M3

U4

H1 H2

H3

H4

M4

Fig.6. Stores classification based on station for stores grouping

Fig.8. Comparison of typical flight mechanics parameters used for stores grouping

4.2.1 Study of Mass CG variation

4.2.3 Linear Assessment Study

Take off mass CG, most aft mass CG, landing mass CG and most forward mass CG should be derived from mass CG variation. Typical mass CG variation for M1, M2, M3, M4 configurations which are considered for study of stores grouping and is given in Fig.7

Thousands of small perturbation linear models of the aircraft are generated for clearance of CLAW over the entire flight envelope. Fourth order state space models are considered with angle of attack, pitch rate, pitch attitude and forward speed as states and elevator deflection as input for Longitudinal axis. Fourth order state space models with roll rate, yaw rate, sideslip angle and roll angle as states and aileron and rudder deflections are inputs for Lateral / directional axes. The fighter control law schematic is given in Shyam Chetty et.al.(2002). Based on the obtained worst stability margins and handling quality parameters, stores grouping in terms of flight conditions (Mach, altitude, angle of attack) are obtained.

Take off (Heavy)

M1 M2 M3 M4

Mid (Aft)

MASS Landing (Light)

Mid (Forward)

Typical margins (elevator closeness parameter- Nichols Plot) for fuel states (aft CG and forward CG) of all store (M1, M2, M3, M4) configurations for one flight condition is given in Fig.9. The closeness parameter as a function of AoA for forward CG and aft CG in the entire AoA flight envelope is shown in Fig. 10. We see that closeness parameter for few flight conditions is lower than 1.0, which indicates deterioration of stability, which is in localized AoA region and recovers within the prescribed limit to Level-1 and hence they can be cleared.

CG

Fig.7. Typical Mass CG variation of configurations considered for stores grouping

mid

board

4.2.2 Flight Mechanics Parameters Study A basic set of relevant flight mechanics parameters are used for identification of the critical regions of aircraft stability and control. Some regions are identified based on the flight mechanics parameters study for critical assessment for each stores M1, M2, M3 and M4. Grouping of the stores is done based on the variation study of flight mechanics parameters. Study of flight mechanic parameters includes the study of variation of longitudinal static stability derivative(Cmα), elevon control power (Cmδe), pitch acceleration( q̈ ), rolling moment due to sideslip(Clβ), Yawing moment coefficient due to sideslip (Cnβ), Time to double, dynamic directional stability parameter (Cnβ dyn). Typical flight mechanics parameters like pitching moment coefficient due to alpha (Cmα), yawing moment coefficient due to sideslip beta (Cnβ)

Fig.9. Nichols plot at one flight condition for M1, M2, M3 and M4 configurations used for stores grouping 385

5th International Conference on Advances in Control and 370 Sreelalitha B et al. / IFAC PapersOnLine 51-1 (2018) 365–370 Optimization of Dynamical Systems February 18-22, 2018. Hyderabad, India

most aft mass CG of M1, landing mass CG of M1, most forward mass CG of M4) are considered from mass C.G variation marked in Fig.7. These fuel states are considered based on the extreme mass CG coverage. Based on the aerodynamic characteristics given in Fig.8, according to the longitudinal stability margins given in Fig.9, Fig.10 and also based on the nonlinear responses of AoA, Nz with full stick input given in Fig.11, it shows that grouped fuel states obtained using stores grouping process from mass CG configurations has the worst variation than other store configurations. 6. Fig.10. Closeness parameter of M1, M2, M3 and M4 configurations used for stores grouping

CONCLUSIONS AND FUTURE WORK

In this paper ‘stores grouping concept’ is evolved, in order to reduce the manual effort of going through critically the entire set of results generated for the entire flight envelope for various stores. The results generation process is automated, however, the process itself is routine and time consuming in nature. Flight mechanics parameters study is done which itself is some kind of pre-processing like creating similar class stores families, showing identical or at least very similar aerodynamic characteristics. Remaining small differences could be handled with so called grouping tolerances. For a particular store location, mass and CG variation is carried out for further stores grouping. It gives one set of fuel states (take-off mass cg, aft cg, landing cg and fwd cg) of mass CG. These fuel states are verified through flight mechanics parameters study, linear assessment study and nonlinear assessment study. From the above generated results and detailed study, it is revealed that it is good enough to check set of fuel states based on mass cg variation study. To conclude, overall, for control law clearance, stores grouping concept helps in reducing the time and effort. It also help in defining events to reconfigure flight control laws in order to improve both stability and performance.

4.2.4 Nonlinear assessment study For flight control law clearance in nonlinear domain, 6DOF offline simulation studies are done at several grid points (flight conditions) in the flight envelope and the maximum / minimum values of the longitudinal and lateral-directional parameters are observed with maximum stick or pedal inputs. Full stick rapid pulls/ pushes are given as inputs to check whether responses are within the limits for the nominal case. Maximum roll rates/ overshoots, maximum sideslip generated during roll, roll angle overshoot when trying to stop the roll are some parameters which are checked for full roll stick inputs. Control surface position / rate saturations should not occur during flight and if the saturation is encountered, it must not lead to control problems or PIO. This is checked offline by giving fast inputs. Typical AoA and Nz variation with full pitch stick input for M1, M2, M3 and M4 configurations is given in Fig.11.

7.

REFERENCES

Andras Varga, Samir Bennani, Michiel Selier (Eds.) (2002), Advanced Techniques for Clearance of Flight Control Laws”, Christopher Fielding, Springer. Shyam Chetty, Girish Deodhare, B.B. Misra (2002), Design, Development and Flight Testing of Control Laws for the Indian Light Combat Aircraft”, AIAA Guidance, Navigation and Control Conference, Monterey, CA, August 2002. Girish Deodhare and Vijay V. Patel (1998) , A Modern Look at Gain and Phase Margin: An H Approach. AIAA Guidance Navigation and Control Conference, Control Theory Analysis and Design, Boston, AIAA-98-4134

Fig.11. Typical longitudinal time response plot for M1, M2, M3 and M4 5.

MIL (1975), Military specification flight control systems— design, installation and test of piloted aircraft,” Tech. Rep. MIL-F-9490D

STORES GROUPING ANALYSIS

Based on the mass CG variation for four different stores configurations at midboard (wing stores) given in Fig.6, stores grouping was done. In all the four different store configurations, four fuel states (take off mass CG of M1,

MIL (1980), Military specification flying qualities of piloted airplanes. Tech. Rep. MIL-F-8785C 386