Tuning and Assessment of Proportional–Integral–Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm

—This article presents an approach for obtaining proportional–integral–derivative controller parameters for an automatic voltage regulator system based on a local unimodal sampling optimization algorithm. A conventional integral time of squared error objective function and modified objective functions in terms of integral time of absolute error, integral of absolute error, integral of squared error, peak overshoot, and settling time with appropriate weighting factors are employed to tune the controller parameters. Different objective functions are employed to obtain optimized proportional–integral–derivative controller gains. Superiority of proposed technique over some recently published modern heuristic optimization techniques, such as artificial bee colony algorithm, particle swarm optimization algorithm, and differential evolution algorithm, for the same automatic voltage regulator system is demonstrated. Simulation results reveal that the proposed proportional–integral–derivative controlled automatic voltage regulator system tuned by the local unimodal sampling algorithm with modified objective function exhibits better performance in terms of settling time, peak overshoot, and stability. The robustness of the system tuned by the proposed algorithm is also studied satisfactorily by varying the time constants of the automatic voltage regulator system in the range of –50% to +50% in steps of 25%.