Nonlinear Excitation Control of Diesel Generator: A Command Filter Backstepping Approach

This article proposes an alternate approach following command-filtered backstepping (CFBS) principle to control the terminal voltage and stabilize the speed of a diesel generator through the excitation system. This controller eliminates the errors introduced due to differentiation of input signal and is, therefore, better compared to the conventional backstepping control technique. The global stability conditions of the overall closed-loop system are established using Lyapunov criteria. The parameters of the controller are optimized using a comprehensive learning particle swarm optimization technique. The performance of the proposed controller is compared with two other controllers, which include a classical proportional integral derivative (PID) and $\Delta \Sigma$–based PID controllers. The performance comparison using percentage overshoot and settling time demonstrate that the proposed controller is superior and could effectively control the terminal voltage and stabilize the speed under various fault conditions.