Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty

This paper presents a new method for tuning the weighing functions to design an H 4 controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. The PSO algorithm is used to minimize the infinity norm of the transfer functions matrix of the nominal closed loop system to obtain the optimal parameters of the weighting function. This method is applied to a typical industrial pneumatic servo actuator controlled by a jet pipe valve. The pneumatic system nonlinearity and system parameters uncertainty are the main problems in the design of a desired controller for this plant. A linear model of the plant at certain operating point is derived and the structured (parametric) perturbations in the plant coeficients are taken into account. This method ensures an optimal robust stability and robust performance for the pneumatic servo actuator system. Simulation results are presented to verify the objectives of this method.

[1]  Djordje Dihovicni,et al.  Simulation, animation and program support for a high performance pneumatic force actuator system , 2008, Math. Comput. Model..

[2]  S. M. Bashi,et al.  Robust Controller Design For Positioning A pneumatic Servo Actuator , 2009 .

[3]  Mohammad Hamiruce Marhaban,et al.  A Review of Pneumatic Actuators (Modeling and Control) , 2009 .

[4]  Naresh K. Sinha,et al.  Modern Control Systems , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Anselmo Bittar,et al.  H/sub 2/ and H/sub /spl infin// control for MagLev vehicles , 1998 .

[6]  J. Doyle,et al.  Essentials of Robust Control , 1997 .

[7]  A. Sinha Linear systems : optimal and robust control , 2007 .

[8]  Jia Ke,et al.  Tracking control of nonlinear pneumatic actuator systems using static state feedback linearization of the input–output map , 2007, Proceedings of the Estonian Academy of Sciences. Physics. Mathematics.

[9]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .

[10]  Petko H. Petkov,et al.  Robust control design with MATLAB , 2005 .

[11]  Nasser Sadati,et al.  Design of an H∞ PID controller using particle swarm optimization , 2009 .

[12]  Peter Beater,et al.  Pneumatic Drives: System Design, Modelling and Control , 2007 .

[13]  She-Xiong Su,et al.  A Modified Particle Swarm Optimization Algorithm and Application , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[14]  M. Karpenko,et al.  QFT design of a PI controller with dynamic pressure feedback for positioning a pneumatic actuator , 2004, Proceedings of the 2004 American Control Conference.