Hybrid algorithm DE–TLBO for optimal H∞ and PID control for multi-machine power system

This paper propose, a robust excitation controller designed by a coordination of the optimal H ∞ tracking control and the proportional integral derivative (PID) controller optimized by the hybrid differential evolution and teaching–learning based optimization algorithm (DE–TLBO). These two controllers are used in order to guarantee the transient stability during a change in the operating conditions and the uncertainties in parameters. We have applied a method based on the modified tracking error by using the optimized exponential function, to avoid the compromise between the high gain in the control input and the H ∞ tracking performance with the variation in the system parameter. A new hybrid algorithm (DE–TLBO) is employed in this study to adjust optimally the parameters of the (PID–PSS) controller and the exponential form of the tracking error modified. The purpose of the suggested approach is to ensure a good tracking accuracy and to enhance the level of the oscillations damping in the multi-machine power system with an optimal choice of the parameters of all proposed controllers. The results of simulation demonstrate the efficient, and the robustness of the proposed approach (H ∞ and DE–TLBO–PID–PSS) under the different operation conditions.