Expert Self-tuning Using Fuzzy Reasoning for PID Controller

This paper introduces a expert PID system utilizing fuzzy inference mechanism by defining TDR (rules degree of trigging) and TDS (targets degree of satisfaction), whose inference rulers are brief. The rules can be trigged simultaneously and even in the case of the failure of reasoning, can also alternate the suboptimal parameters to overcome the general PID expert systems short coming that be fail to settle the optimal parameter. The article makes simulation on a typical plant to verify the effectiveness of this method.

[1]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[2]  Tore Hägglund,et al.  Automatic tuning of simple regulators with specifications on phase and amplitude margins , 1984, Autom..

[3]  Peter Jackson,et al.  Introduction to expert systems , 1986 .

[4]  R. Devanathan,et al.  Expert PID controller for an industrial process , 1989, Fourth IEEE Region 10 International Conference TENCON.

[5]  C.C. Hang,et al.  A comparative performance study of PID auto-tuners , 1991, IEEE Control Systems.

[6]  William S. Levine,et al.  The Control Handbook , 2010 .

[7]  Yun Li,et al.  PID control system analysis, design, and technology , 2005, IEEE Transactions on Control Systems Technology.