OPTIMAL DESIGN OF ADAPTIVE FUZZY PID TUNER

Abstract

Conventional proportional—integral—derivative(PID) controllers have been well developed and applied for about half a century, and are extensively used for industrial automation and process control today. The main reason is due to their simplicity of operation, ease of design, inexpensive maintenance, low cost, and effectiveness for most linear systems. Recently, motivated by the rapidly developed advanced microelectronics and digital processors, conventional PID controllers have gone through a technological evolution, from pneumatic controllers via analog electronics to microprocessors via digital circuits. However, it has been known that conventional PID controllers generally do not work well for nonlinear systems, higher order and time-delayed linear systems, and particularly complex and vague systems that have no precise mathematical models. To overcome these difficulties, various types of modified conventional PID controllers such as autotuning and adaptive PID controllers were developed lately. The present dissertation describes a methodology for the systematic design of Adaptive fuzzy PID tuner. It uses three SISO fuzzy controllers for tuning PID parameters. Each fuzzy controller is designed with three rules and at most two tuning parameters. By using optimization algorithms, the fuzzy PID tuner design problem is transferred to the parameter optimal problem and the fuzzy controller design parameters are optimized such that the minimum cost function can be achieved based on the given performance index. Here, nonlinear least square optimization is used for finding the optimum parameters. Simulation results show that the proposed Adaptive fuzzy PID tuner produces superior control performance than the conventional PID controllers, particularly in handling time-delay and nonlinear systems