Hideyuki Nishida

Development of PSO-based PID tuning method

This paper proposes a new PID parameter tuning method using particle swarm optimization (PSO) without tuning operatorpsilas know-how. The method searches the PID parameter that realizes the expected step response of the plant. The expected response is defined by the overshoot ratio, the rising time, the settling time. The method is implemented into the PID tuning tool on a personal computer. The plant model represented by the transfer function is obtained by system identification on the PID tuning tool. The PID parameter is computed by PSO-based PID tuning method according to the obtained model. The numerical result and the experiment result show the effectiveness of the proposed tuning method and the developed tool.

PID optimal tuning method by Particle Swarm Optimization

This paper proposes a new PID parameter tuning method by particle swarm optimization (PSO) without tuning operatorpsilas know-how. The method searches the PID parameter that realizes the expected step response of the plant. The response is defined by the overshoot ratio, the rising time, the settling time and so on. The method is implemented into the PID tuning tool on a personal computer. The plant model represented by the transfer function is obtained by system identification on the PID tuning tool. The PID parameter is computed by PSO-based PID tuning method according to the obtained model. The numerical results show the effectiveness of the proposed tuning method and the developed tool.

Auto-tuning of motor drive system by simple adaptive control approach

The paper is concerned with an auto-tuning method to adjust the parameters in the feedforward and feedback PI controllers for a motor drive system, according to identified physical parameters such as a motor time constant, viscous friction terms proportional to motor velocity and squared velocity, and Coulomb friction. These physical parameters can be obtained by specially setting up a suitable reference model and plug-in models in the simple adaptive control (SAG) algorithm. Digital implementation for the proposed adaptive algorithm is also presented, in which the relative degree problem is solved by a serial compensation scheme for a non-ASPR system. The effectiveness of the proposed auto-tuning algorithm is examined in experimental studies in velocity control of an AC synchronous servo motor. It is clarified that the proposed scheme can simultaneously give perfect tracking to the reference output and the specified attenuation performance of the closed-loop system, even if the load mass largely changes uncertainly.

Speed control of two-mass resonant system by new simple adaptive control scheme

A new simple adaptive control scheme is introduced for torsional vibration control in a two-mass motor drive system, in which a motor and load are connected via a flexible shaft. It is clarified that only three adjustable parameters can successfully compensate for variations in load, modeling error and stepwise torque disturbances, even without using a velocity sensor of the load. The validity of the proposed algorithm is examined in simulation and experimental studies.

Particle Swarm Optimization for Optimal Operational Planning of Energy Plants

This paper proposes dependable multi-population differential evolutionary particle swarm optimization (DEEPSO) for optimal operational planning of energy plants. The problem can be formulated as a mixed integer nonlinear optimization problem (MINLP). Optimal operational planning of numbers of energy plants are calculated simultaneously in a data center. Therefore, the problem is required to generate optimal operational planning as rapidly as possible considering control intervals and numbers of treated plants. One of the solutions for this challenge is speeding up by parallel and distributed processing (PDP). However, PDP utilizes numbers of processes and countermeasures for various faults of the processes should be considered. The problem requires successive calculation at every control interval for keeping customer services. Therefore, sustainable (dependable) calculation keeping appropriate solution quality are required even if some of the calculation results cannot be returned from distributed processes. The results indicate that the proposed method can improve solution quality compared with the conventional parallel DEEPSO based method using a master-slave model even if some of the calculation results cannot be returned from distributed processes.

New simple adaptive control subject to disturbances and application to torsional vibration suppression

The present paper proposes a new simple adaptive control scheme taking into account of disturbances for a non-ASPR system, and investigates the global stability of the obtained adaptive algorithm. Two schemes for rejecting disturbance effects are discussed from feedback and adaptive feedforward points of view. The validity of the proposed algorithm is examined in numerical simulation and experimental study in which the adaptive torsional vibration control of an induction motor connected with a load by a flexible shaft can be achieved in the presence of torque disturbance without using any sensor for the load.

Moving horizon simultaneous estimation of process gain and disturbances for an oxygen converter gas recovery process model

Abstract This paper proposes a moving horizon simultaneous estimation of process gain and disturbances for discrete-time linear systems with unknown process gain so as to minimize a moving-horizon performance index. The proposed method uses discrete-time Euler-Lagrange equations in order to derive the proposed adaptive disturbance estimator. A numerical simulation for an oxygen converter gas recovery process shows the efficiency of the proposed method.

On-Line Tuning of One-Mass Motor Drive System by Simple Adaptive Control

Abstract A new auto-tuning algorithm for motor velocity control is presented to adjust the parameters in the feedforward and feedback PI controllers, according to identified physical parameters such as a motor time constant, viscous friction terms proportional to motor velocity and squared velocity, and Coulomb friction. The physical parameters are identified by the proposed adaptive algorithm which appropriately set up a reference model and use its state variables to adjust the feedforward controller parameters. The proposed scheme is robust to disturbance torque, compared to ordinary closed-loop identification using the motor output directly. Its effectiveness is investigated in velocity control experiment using an AC synchronous servo motor.