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142 Parameter-estimation and digital control in continuous-time models and application to a combustion-engine dynamometer
534
Abstracts
control of a general class of mknown discrete-time nonlinear systems which are treated as "black boxes" with multiple inputs and multiple outputs. A model of the MR_NNis described by • set of nonlinear difference equations, and a suitable analysis for the input-output dynamics of the model is performed to obufin the inverse dynamics. An equivalent enntrol concept is introduced to develop a model-based learning control architecture with simultaneous on-line identification and control for an unknown nonlinear plant. The potential of the proposed methods is demonstrated by simulation results.
138
Application of an Expert System to Hot Strip Mill Load Balance Control K. Kurihara, S. Murakaml, H. Umeda, G. Kameyama, pp 603-606
The draft schedule in a hot strip finisher mill is automatically determined by a computer, using a theoretical model. When roiling thin-gauge or hard material, operators must often adjust the load balance because of snaking or fluctuations. A draft-schedule expert system has beam introduced in the finisher mill set-up system at the NKK Fukyama Works No.2 hot strip mill. The operator's knowledge was summarized in the planning to vary the load distribution over the stands according to the rolling schedule, the restriction of main motor current distribution and the determination of roll gap difference. In a feasibility test, the prototype system proved to be 90% applicable to the actual process, with a real-time guidance system.
139
Non-Linear System Identification Using Neural Networks Oriented Speech Liu Huaqlang, DaI Guanzhong, Xu Nalplng, pp 607-610
Speech can be considered as the output of a time-varying nonlinear dynamic system. This paper researches how the signal during one cycle of a fundamental tone of speech is picked up from natural speech and produced by a non-time-varying system, employing the methods and results available from non-linear systems research. The signal during one cycle is regarded as the smallest trait of speech. Many signal-processing methods can easily be used here, and changes of speech are reflected in good time by those of the system panmaeters. Non-linear system identification using nenral methods is employed for drawing system parameters. Speech recognition can currently be achieved in this way.
140
Adaptive Control of Accelerated Cooling Plant Based on Distributed Observer V.I. Utkin, I.M. Kaliko, G. Bartolini, C. Ghlazza, pp 611-614
modelling uncertainties, the repetitive controller's gain is adjusted to reduce the infinite norm of the error in the frequency domain. Secondly, an alternative repetitive control system with higherorder repetitive function is analyzed and designed. Weightings of the higher-order repetitive function are determined such that the infinite norm of the relative error transfer function is minimized. Computer simulation results for a typical disk drive head positioning servo system validate the proposed methods.
142
A combustion engine dynamometer described by ordinary differential equations is identified by least-squares estimation and state variable filters. The estimated parameters of the dynamometer are compared with the parameters achieved from theoretical modelling. Based on the estimated parameters, a disturbance compensation, a PI-torque controller and a state-space controller are designed. The three control algorithms are compared.
143
141
Analysis and Design of Two Types of Digital Repetitive Control Systems Wou-Sok Chang, II Hong Sub, June-Dong Kim, pp 615-620
Two types of linear digital repetitive control systems are designed and analyzed to re.duce the error ~ , including harmonic and non-hanmonic components. In a novel gain-adjusting algorithm for conventional and modified repetitive control systems with
Discretlzatiou and Continualization of MIMO Systems S. Bingulac, H.F. Vanlandingham, pp 625-628
New, numerically robust algorithms are presented for converting linear continuous-time constant-parameter state models into equivalent discrete-time state models (discretization) as well as the reverse problem of determining continuous-time models to represent given discrete-time models (continualization). Two methods of discretizing linear uniformly sampled systems have been considered for their utility in computer-aided design. These methods are the standard zero-order hold method, which assumes that inputs are held constant at their previous sample value for the duration of the sample interval, and a method which assumes that the inputs are linearly interpolated between samples.
144
Parameter Identification and Adaptive Control of Continuous Systems with Zero-Order Hold S. Sagara, Zi-Jiang Yang, K. Wade, T. Tsuji, pp 629-632
This paper discusses the digital implementation techniques of paramemr identification and adaptive control for continuous systems with zero-order hold (ZOH), focusing on the bilinear transformation based on the block pulse functions (BPFs). It is found that the emphasized discreti~-~g method yields excellent performances of parameter identification and adaptive control, even in the case of large sampling intervals.
145 The process of accelerated cooling of stoel plates is under consideration. A control algorithm is developed, taking into account temperature distribution within plate thickness and the essential temperature dependence of the coefficients in the motion equation. The proposed control approach provides precise average temperature tracking in the oomplete information case. The method is based on ordinary differential equations describing the dynamics of the scalar variable under control. For real-life situations with entry and exit surface temperature measurements and uncertain plant parameters, the developed method implies the application of a distributed state observer associated with an adaptation loop.
Parameter Estimation and Digital Control with Continuous-Time Models and Application to a Combustion.Engine Dynamometer R. lsermann, K.U. Voigt, K. Pfeiffer, pp 621-624
Joint State and Parameter Estimation in ContinuousTime MIMO System S. Mukhopadhyay, pp 633-636
This paper considers state estimation in a linear multi-input multioutput (MIMO) system with significant parameter uncertainty. The method proposed is based on parameter estimation in continuous-time models (CTMs). It involves simultaneous recursive estimation of a transformed version of the model parameters, as well as the dynamic state vector. The method is computationaHy simple and suited to real-time implementation. It may be adopted for adaptive control, state estimation of timevarying and nonlinear systems, fault detection and diagnosis, etc.
146
Bias Distribution in Continuous-Time Transfer Function Estimates by Prediction Error Method V.N. Bapat, S. Mukhopadyay, A. Patra, D.C. Saha, pp 637-641
Estimation of simple transfer function models of complex dynamic systems is an important issue for robustness of all subsequent application stages of the models, such as control, fault detection, etc. This paper considers an R L S approach to s-transferfunction
Abstracts
control of a general class of mknown discrete-time nonlinear systems which are treated as "black boxes" with multiple inputs and multiple outputs. A model of the MR_NNis described by • set of nonlinear difference equations, and a suitable analysis for the input-output dynamics of the model is performed to obufin the inverse dynamics. An equivalent enntrol concept is introduced to develop a model-based learning control architecture with simultaneous on-line identification and control for an unknown nonlinear plant. The potential of the proposed methods is demonstrated by simulation results.
138
Application of an Expert System to Hot Strip Mill Load Balance Control K. Kurihara, S. Murakaml, H. Umeda, G. Kameyama, pp 603-606
The draft schedule in a hot strip finisher mill is automatically determined by a computer, using a theoretical model. When roiling thin-gauge or hard material, operators must often adjust the load balance because of snaking or fluctuations. A draft-schedule expert system has beam introduced in the finisher mill set-up system at the NKK Fukyama Works No.2 hot strip mill. The operator's knowledge was summarized in the planning to vary the load distribution over the stands according to the rolling schedule, the restriction of main motor current distribution and the determination of roll gap difference. In a feasibility test, the prototype system proved to be 90% applicable to the actual process, with a real-time guidance system.
139
Non-Linear System Identification Using Neural Networks Oriented Speech Liu Huaqlang, DaI Guanzhong, Xu Nalplng, pp 607-610
Speech can be considered as the output of a time-varying nonlinear dynamic system. This paper researches how the signal during one cycle of a fundamental tone of speech is picked up from natural speech and produced by a non-time-varying system, employing the methods and results available from non-linear systems research. The signal during one cycle is regarded as the smallest trait of speech. Many signal-processing methods can easily be used here, and changes of speech are reflected in good time by those of the system panmaeters. Non-linear system identification using nenral methods is employed for drawing system parameters. Speech recognition can currently be achieved in this way.
140
Adaptive Control of Accelerated Cooling Plant Based on Distributed Observer V.I. Utkin, I.M. Kaliko, G. Bartolini, C. Ghlazza, pp 611-614
modelling uncertainties, the repetitive controller's gain is adjusted to reduce the infinite norm of the error in the frequency domain. Secondly, an alternative repetitive control system with higherorder repetitive function is analyzed and designed. Weightings of the higher-order repetitive function are determined such that the infinite norm of the relative error transfer function is minimized. Computer simulation results for a typical disk drive head positioning servo system validate the proposed methods.
142
A combustion engine dynamometer described by ordinary differential equations is identified by least-squares estimation and state variable filters. The estimated parameters of the dynamometer are compared with the parameters achieved from theoretical modelling. Based on the estimated parameters, a disturbance compensation, a PI-torque controller and a state-space controller are designed. The three control algorithms are compared.
143
141
Analysis and Design of Two Types of Digital Repetitive Control Systems Wou-Sok Chang, II Hong Sub, June-Dong Kim, pp 615-620
Two types of linear digital repetitive control systems are designed and analyzed to re.duce the error ~ , including harmonic and non-hanmonic components. In a novel gain-adjusting algorithm for conventional and modified repetitive control systems with
Discretlzatiou and Continualization of MIMO Systems S. Bingulac, H.F. Vanlandingham, pp 625-628
New, numerically robust algorithms are presented for converting linear continuous-time constant-parameter state models into equivalent discrete-time state models (discretization) as well as the reverse problem of determining continuous-time models to represent given discrete-time models (continualization). Two methods of discretizing linear uniformly sampled systems have been considered for their utility in computer-aided design. These methods are the standard zero-order hold method, which assumes that inputs are held constant at their previous sample value for the duration of the sample interval, and a method which assumes that the inputs are linearly interpolated between samples.
144
Parameter Identification and Adaptive Control of Continuous Systems with Zero-Order Hold S. Sagara, Zi-Jiang Yang, K. Wade, T. Tsuji, pp 629-632
This paper discusses the digital implementation techniques of paramemr identification and adaptive control for continuous systems with zero-order hold (ZOH), focusing on the bilinear transformation based on the block pulse functions (BPFs). It is found that the emphasized discreti~-~g method yields excellent performances of parameter identification and adaptive control, even in the case of large sampling intervals.
145 The process of accelerated cooling of stoel plates is under consideration. A control algorithm is developed, taking into account temperature distribution within plate thickness and the essential temperature dependence of the coefficients in the motion equation. The proposed control approach provides precise average temperature tracking in the oomplete information case. The method is based on ordinary differential equations describing the dynamics of the scalar variable under control. For real-life situations with entry and exit surface temperature measurements and uncertain plant parameters, the developed method implies the application of a distributed state observer associated with an adaptation loop.
Parameter Estimation and Digital Control with Continuous-Time Models and Application to a Combustion.Engine Dynamometer R. lsermann, K.U. Voigt, K. Pfeiffer, pp 621-624
Joint State and Parameter Estimation in ContinuousTime MIMO System S. Mukhopadhyay, pp 633-636
This paper considers state estimation in a linear multi-input multioutput (MIMO) system with significant parameter uncertainty. The method proposed is based on parameter estimation in continuous-time models (CTMs). It involves simultaneous recursive estimation of a transformed version of the model parameters, as well as the dynamic state vector. The method is computationaHy simple and suited to real-time implementation. It may be adopted for adaptive control, state estimation of timevarying and nonlinear systems, fault detection and diagnosis, etc.
146
Bias Distribution in Continuous-Time Transfer Function Estimates by Prediction Error Method V.N. Bapat, S. Mukhopadyay, A. Patra, D.C. Saha, pp 637-641
Estimation of simple transfer function models of complex dynamic systems is an important issue for robustness of all subsequent application stages of the models, such as control, fault detection, etc. This paper considers an R L S approach to s-transferfunction