In this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering L More
In this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering Lab at Arak University. The purpose of controlling the twin rotor system is to stabilize the system in the zero degree horizontal position. After modeling and obtaining the state space description, the PID controller is designed and implemented on the system. In this study, by reviewing meta-heuristic optimization methods such as particle swarm optimization algorithm, genetic algorithm, colonial competition algorithm and differential evolution algorithm, the optimization results were compared with the above-mentioned meta-heuristic methods. With the optimization performed by the teaching and learning algorithm, the stability and faster performance of the system compared to other meta-heuristic methods can be seen. The merit of TLBO is that it does not have control parameters, which makes it convenient to employ. The simulation results of the PID controller for a twin rotor system show the effectiveness of the proposed methods.
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