Optimization of multiple controller parameters with heuristic algorithm

Numerical optimization methods are preferred for solving engineering problems particularly for determination of the controller parameters. In this thesis, many controllers were designed with numerical optimization method for many systems. Firstly, fractional order mathematical equations were solved with Homotopy Perturbation Method (HPM). Then, a stochastic multi parameter divergence optimization method (SMDO), which can determine fractional order and integer order controller parameters for the many systems, was proposed. Controllers, which were obtained by means of this method, was used for experimental systems and obtained responses were presented comparatively. In the following part of the thesis, tuning of fractional order controller parameters by Tabu Search Algorithm (TSA) was demonstrated. The results were compared with methods in literature. Then, Artificial Physics Optimization (APO) Algorithm method, which exists in literature but not used in controller design, was modified for controller design and coded for computer aided design. Thus, integer order and fractional order controller were designed for mathematical models that exist in the literature. Moreover, the structures, which affects the working mechanism of this algorithm, are separately examined in the optimization processes, and the configuration, where the algorithm can work with the maximum performance for the related system, was determined. In general, single objective function is used in optimization processes. However, in the last part of this thesis, Big Bang Big Crunch (BB-BC) Optimization Algorithm and Tabu Search Algorithm (TSA) were used to show that the optimization process can be performed by using multiple objective functions.