An internal model control based tuning method for single input fuzzy PID controller

The first goal of control engineering is to analyze and process the knowledge of how a process can be controlled. However, with this structured control mechanism, reliable and accurate results can be obtained on processes that require high performance. Fuzzy control is a practical alternative for a variety of challenging control applications since it provides a convenient method for constructing nonlinear controllers via the use of heuristic information. Regardless of where the heuristic control knowledge comes from, fuzzy control provides a user-friendly formalism for representing and implementing the ideas we have about how to achieve high-performance control. Conventional proportional-integral-derivative (CPID) controllers may not perform well for the complex process, such as the high-order and time delay systems. Under this complex environment, it is well-known that the fuzzy controller can have a better performance due to its inherent robustness. Thus, over the past three decades, fuzzy controllers, especially, fuzzy proportional-integral-derivative (FPID) controllers have been widely used for industrial processes. Because their heuristic natures associated with simplicity and effectiveness for both linear and nonlinear systems. Even though industry shows growing interest in the applications of FPID, the tuning mechanism of scaling factors (SFs) and the stability analysis are still difficult tasks due to the complexity of the nonlinear control surface that is generated by FPID controllers. In literature, several studies have been presented where the design of the two input FPID (CFPID) controllers have been investigated. Because of the number of the design parameters of CFPID is relatively big, the systematic design is still a challenging problem. Besides of that the majority of the research focus on the two-input structures, it has been shown in various works that single input FPID (SFPID) provide greater flexibility and better functional properties. In the SFPID controller structure a new called "signed distance" variable is used as input signal. In this way, the number of rules and membership functions (MFs) is less than CFPID while both of the controllers have almost same control performance as showed in this thesis. This feature brings design simplicity to SFPID controller. There are several design methods in literature for tuning design parameters of controller. One of the most common used is internal model control based tuning method. Having a single parameter dependent to the close-loop time constant is effective for commanly used. In this thesis, firstly, a brief information will given about CPID controller and internal model control (IMC) based tuning method. Than, the CFPID structure will be analyzied in detail. By extraction the rules and MFs, the relationship between inputoutput of controller will shown. Present the an analytical tuning method based on IMC to tune SFPID controllers will proposed in this thesis. First, reduction process from CFPID structure to SFPID structure will be explaned. By examining the relationship between input-output and MFs, in order to design the desired control structure, the design rule template will be presented about how to set the membership function parameters. As a result of all the work done, it was said that, SFPID controller can be expressed as a linear proportional-integral-derivative (PID) controller plus a nonlinear compensation item. So, it is acceptable the IMC based tuning method is applicable to SFPID controller and the formulations for tuning process will be presented. Finally, by simulation studies it will be shown that the SFPID is capable to improve the transient state performance while providing an identical disturbance rejection performance of the CFPID structure.