Expert Self-Tuning Using Fuzzy Reasoning for Proportional-Integral-Derivative Controller

Designing and tuning a proportional-integral-derivative (PID) controller appears to be conceptually intuitive, but can be hard in practice. This paper introduces a expert PID system utilizing fuzzy inference mechanism by defining TDR (rulei(-)s 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.