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Multivariable control of nonlinear process using soft computing techniques

N. Kamala1, T. Thyagarajan2, and S. Renganathan3
1. Department of EEE, RRASE college of Engineering, Chennai, India
2. Department of EIE, M.I.T, Anna University, Chennai, India
3. Former Director, Anna University, Chennai, India
Abstract - In this paper, Particle Swarm Optimization is utilized to optimize the coefficients of a decentralized PID controller for a nonlinear process by minimizing the Integral Square Error (ISE).The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using a Fuzzy Gain scheduler. The effectiveness of the proposed control scheme has been demonstrated by conducting simulation studies on a Continuous Stirred Tank Reactor (CSTR) process which exhibits dynamic nonlinearity. It is shown that the proposed controller provides better set point tracking and load disturbance rejection than the Internal Model Control (IMC) based conventional control scheme.

Index Terms - CSTR, Decentralized control, PSO, IMC, PID, Integral Square Error, Fuzzy Gain scheduling

Cite: N. Kamala, T. Thyagarajan, and S. Renganathan, "Multivariable control of nonlinear process using soft computing techniques," Journal of Advances in Information Technology, Vol. 3, No. 1, pp. 48-56, February, 2012.doi:10.4304/jait.3.1.48-56
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