![]() ![]() The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional integral controller through some performance indices A two area interconnected system is assumed for demonstrations. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral coefficient of the PID type fuzzy logic controller in an on-line manner. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. Self tuning fuzzy PID type load and frequency controller Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. The dynamic effects of process deadtime and noise are also considered. The STPI algorithms' performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. A brief theory of operation of these three STPI control algorithms is given. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. Several process identification and parameter adjustment methods are discussed. The methods discussed include gain scheduling, self-tuning, auto- tuning, and model-reference adaptive control systems. International Nuclear Information System (INIS)Ī brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The estimator.Ī comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller In the thesis an algorithm for estimating abruptly changing parameters is presented. ![]() It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. A special self tuning controller has been developed to regulate plant with changing time delay.The present thesis concerns robustness properties of adaptive controllers. has several operation modes and a detector for controlling the mode. ![]() The present thesis concerns robustness properties of adaptive controllers. ![]()
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