CONTROL OF DYNAMIC PROCESSES USING AN ONLINE RULE-ADAPTIVE FUZZY CONTROL-SYSTEM

In this paper, we present a detailed discussion on the design of a rule-adaptive fuzzy control system, along with simulation analysis demonstrating its usefulness in controlling plants of various dynamical natures. Conceived first by Wang, and further clarified in [8], the rule-adaptive fuzzy controller considered here generates the fuzzy control signal as a convex combination of the standard fuzzy inputs to the controller, the error and the error rate. Such a combination is automatically adjusted on-line in response to the varying control situations with certain updating scheme. This paper considers two different updating schemes. The first one is based on a fuzzy relationship, and is a revision of the rule presented in [11]. The present paper also proposes the second updating rule that is essentially a nonlinear differential equation. Both of the rules are applied to the simulations of several selected dynamical plants. The simulation results show that the controller is effective in controlling a wide range of dynamical plants. Especially, it shows better performance in controlling the plants found difficult to be controlled by the conventional means. The simulation also shows that the controller can be used to curb the effect of load disturbance in the control process.