A Single State Sliding Mode Controller Design Using Intelligent Optimization Algorithms for the Chaotic WINDMI System

In this study, a new single-state sliding mode controller is proposed that can be used in multi-input dynamic systems that require the system dynamics to be controlled by a single state variable. The proposed controller is compared with the single state sliding mode controller, which is effective according to a linear feedback controller and a passive controller. To demonstrate the effectiveness of the controllers, the model WINDMI, which is defined as a complex driven damped dynamic system, is preferred as an exemplary model. For the system's dynamics to reach reference in the shortest settling time with minimum overshoot, the sliding surface coefficient and the controller coefficients are optimized according to the sliding surface using Particle Swarm Optimization, Genetic Algorithm, and Pattern Search algorithm. The best values of optimization coefficients are determined by comparing the obtained results. Finally, verifying the effectiveness and reliability of the proposed controller is demonstrated with simulations and numerical analysis.