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066 The “symmetrische optimum” and the autocalibration of PID controllers
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Abstracts
061 Dominant Pole Design - a Unified View of PID Controller Tuniqg P. Persson, K.J. Astr6m, pp 377-382
065 A Position Control Autotuner for Handling Systems L. Schmltt, M. M'Saad, pp 401-405
The majority of industrial control is still done by PID controllers. This paper presents a new method for tuning such controllers based on placement of a few dominant poles. The method makes it possible to consider specifications on set point response, load disturbance response, measurement noise and plant uncertainty. The method is a little more complicated than traditional tuning rules. The method is described. Its properties are illustrated on several examples. Comparisons with conventional tuning methods are also given.
This paper describes an autotuning approach for position control in handling systems. The main features of the autotuning system are simplicity of use and high degree of performance. The simplicity is provided by an appropriate pretuning procedure using a relay experiment. The high performances are achieved by a partial state reference model controller. An experimental evaluation using a realistic pilot scheme is reported to emphasize the applicability of the proposed approach.
066 The "Symmetrische Optimum" and the AutoCalibration of PID Controllers I.D. Landau, A. Voda, pp 407-412 062 The Normal-Mode-Inaction Adaptive PID Controller Chang Chleh Hang, Shi-Zhong He, TongHeng Lee, pp 383-388 This paper presents a new adaptive PID controller called the normal.mode-inaction (NMI) adaptive PID controller. Unlike the conventional adaptive PID controller, its control parameters are normally fixed, and adaptation occurs only when there is a significant change in the magnitude or phase of a certain point on the Nyquist plot that is being tracked continuously. In the proposed NMI adaptive PID controller, a relay tuning procedure is used to initialize the adaptive controller. The adjustment of the PID controller parameters is based on the refined Ziegler-Nichols turfing formula. Simulation results and analysis have confu'med that the NMI adaptive PID controller has improved robustness properties.
063 Use of Intelligent Tuning in a Hierarchical Control System for Automated Fish Processing C.W. de Silva, N. Wickramarachchi, pp 389.394 This paper considers a hierarchical control structure for a fish-processing workcell. The system consists of local controllers for the system components, and a number of sensing devices including an imaging system at the lowest level. Several higher levels can be introduced. Particular attention is given to the system-monitoring and quality-control level, which receives information from lower-level sensors, tunes the servo controllers and makes adjustments to the operation of the control components through a knowledge-based inferencing system. The paper describes the hierarchical control system that has been developed. Typical results, obtained during system operation, are presented.
The paper presents a method for the auto-calibration of PI and PID controllers when one point of the frequency characteristics (gain and phase) of the controlled plant is identified (for example using a closed loop relay experiment). The turning rules are inspired from the "Symmetrische Optimum" (the symmetrical optimum) principles introduced by Kessler. They have the advantage of taking into account both robusmess aspects (phase margin, gain margin, neglected dynamics) and desired closed-loop characteristics. Comparisons with the Ziegler-Nichols tuning rules are provided (theoretically and experimentally). Simulations on various examples and experiments on an air heater conclude the paper.
067 Hardware Implementation and Evaluation of a Knowledge-Based Tuner for a Servo Motor C.W. de Silva, S. Barley, pp 413-418 A commercially available servo motor system (DC motor, optical encoder, power driver/amplifier, and digital feedback controller) is considered. The controller contains a lead compensator and an integrator. A knowledge-based system is developed and implemented for tuning the controller to meet the performance requirements. A reference model is utilized. Additional knowledge and experience are obtained through operation of the system under different tuning conditiens. The knowledge base obtained in this manner is fuzzy in general. The relationships of controller attributes, with the actual tuning parameters, also have to be established. Tuning inferences are determined using the compositional rule of inference. The performance of the digital servo system is evaluated experimentally.
068 Knowledge Based Adaptive Control with Learning and Intelligent Abilities H. Keller, T. Knapp, U. Raab, pp 419-424
Intelligence and learning are keywords which are 064 Multlvarlable Control Tuning with an Expert System J. Lieslehto, H.N. Koivo, pp 395-400 In this paper a software package for the design of centralized and decentralized multivariable controllers is presented. The software package consists of numerical calculation programs and an expert system. The paper first describes the general structure of the expert system. Next a design example is given. This example demonstrates how the expert system helps the user to design and tune a multivariable controller for a distillation column.
increasingly common in the area of adaptive control. From a control engineering point of view, they could be characterized by automatically finding both an accurate process model and an optimal control algorithm, and by features like fault detection and supervision of the process and its control. This also includes start-up of an adaptive controller. In this paper different methods are presented to deal with simple and complex processes. A knowledge-based adaptive controller is discussed, which leads the control engineer to the optimal control algorithm, independent of the type of process. Several simulation and experimental results are shown for critical processes.
Abstracts
061 Dominant Pole Design - a Unified View of PID Controller Tuniqg P. Persson, K.J. Astr6m, pp 377-382
065 A Position Control Autotuner for Handling Systems L. Schmltt, M. M'Saad, pp 401-405
The majority of industrial control is still done by PID controllers. This paper presents a new method for tuning such controllers based on placement of a few dominant poles. The method makes it possible to consider specifications on set point response, load disturbance response, measurement noise and plant uncertainty. The method is a little more complicated than traditional tuning rules. The method is described. Its properties are illustrated on several examples. Comparisons with conventional tuning methods are also given.
This paper describes an autotuning approach for position control in handling systems. The main features of the autotuning system are simplicity of use and high degree of performance. The simplicity is provided by an appropriate pretuning procedure using a relay experiment. The high performances are achieved by a partial state reference model controller. An experimental evaluation using a realistic pilot scheme is reported to emphasize the applicability of the proposed approach.
066 The "Symmetrische Optimum" and the AutoCalibration of PID Controllers I.D. Landau, A. Voda, pp 407-412 062 The Normal-Mode-Inaction Adaptive PID Controller Chang Chleh Hang, Shi-Zhong He, TongHeng Lee, pp 383-388 This paper presents a new adaptive PID controller called the normal.mode-inaction (NMI) adaptive PID controller. Unlike the conventional adaptive PID controller, its control parameters are normally fixed, and adaptation occurs only when there is a significant change in the magnitude or phase of a certain point on the Nyquist plot that is being tracked continuously. In the proposed NMI adaptive PID controller, a relay tuning procedure is used to initialize the adaptive controller. The adjustment of the PID controller parameters is based on the refined Ziegler-Nichols turfing formula. Simulation results and analysis have confu'med that the NMI adaptive PID controller has improved robustness properties.
063 Use of Intelligent Tuning in a Hierarchical Control System for Automated Fish Processing C.W. de Silva, N. Wickramarachchi, pp 389.394 This paper considers a hierarchical control structure for a fish-processing workcell. The system consists of local controllers for the system components, and a number of sensing devices including an imaging system at the lowest level. Several higher levels can be introduced. Particular attention is given to the system-monitoring and quality-control level, which receives information from lower-level sensors, tunes the servo controllers and makes adjustments to the operation of the control components through a knowledge-based inferencing system. The paper describes the hierarchical control system that has been developed. Typical results, obtained during system operation, are presented.
The paper presents a method for the auto-calibration of PI and PID controllers when one point of the frequency characteristics (gain and phase) of the controlled plant is identified (for example using a closed loop relay experiment). The turning rules are inspired from the "Symmetrische Optimum" (the symmetrical optimum) principles introduced by Kessler. They have the advantage of taking into account both robusmess aspects (phase margin, gain margin, neglected dynamics) and desired closed-loop characteristics. Comparisons with the Ziegler-Nichols tuning rules are provided (theoretically and experimentally). Simulations on various examples and experiments on an air heater conclude the paper.
067 Hardware Implementation and Evaluation of a Knowledge-Based Tuner for a Servo Motor C.W. de Silva, S. Barley, pp 413-418 A commercially available servo motor system (DC motor, optical encoder, power driver/amplifier, and digital feedback controller) is considered. The controller contains a lead compensator and an integrator. A knowledge-based system is developed and implemented for tuning the controller to meet the performance requirements. A reference model is utilized. Additional knowledge and experience are obtained through operation of the system under different tuning conditiens. The knowledge base obtained in this manner is fuzzy in general. The relationships of controller attributes, with the actual tuning parameters, also have to be established. Tuning inferences are determined using the compositional rule of inference. The performance of the digital servo system is evaluated experimentally.
068 Knowledge Based Adaptive Control with Learning and Intelligent Abilities H. Keller, T. Knapp, U. Raab, pp 419-424
Intelligence and learning are keywords which are 064 Multlvarlable Control Tuning with an Expert System J. Lieslehto, H.N. Koivo, pp 395-400 In this paper a software package for the design of centralized and decentralized multivariable controllers is presented. The software package consists of numerical calculation programs and an expert system. The paper first describes the general structure of the expert system. Next a design example is given. This example demonstrates how the expert system helps the user to design and tune a multivariable controller for a distillation column.
increasingly common in the area of adaptive control. From a control engineering point of view, they could be characterized by automatically finding both an accurate process model and an optimal control algorithm, and by features like fault detection and supervision of the process and its control. This also includes start-up of an adaptive controller. In this paper different methods are presented to deal with simple and complex processes. A knowledge-based adaptive controller is discussed, which leads the control engineer to the optimal control algorithm, independent of the type of process. Several simulation and experimental results are shown for critical processes.