Hardware in the Loop Simulation of Control Optimal of DC Motor Base on Modified Quantum-Behaved Particle Swarm Optimization

Abstract

Proportional, Integral, Dervative (PID) controller is a simple and very reliable controller, but to determine the optimal control system parameters on the PID controller (Kp, Ki, and Kd) is not easy. This paper aims to determine the optimal parameters of the PID controller using Modified Quantum Behave Particle Swarm Optimization (MQPSO) to regulate the speed control of a DC motor. MQPSO is a method that has particle search behavior that is more detailed than its predecessor methods, namely Particle Swarm Optimization (PSO) and Quantum-Behaved Particle Swarm Optimization (QPSO). The test is done through Software In the Loop Simulation (SILS) by representing a DC motor in the transfer function, after the optimal control parameters are obtained then applied to the Hardware In the Loop Simulation (HILS) test using the actual DC motor. The test results show that the PID controller that has been optimized using MQPSO results in achieving DC motor response under steady conditions and is faster than the PID controller that is optimized using Ziegler-Nichols (ZN), PSO and QPSO. The completion time obtained by MQPSO is 41.0201 ms, which is also faster than using QPSO 42.8276 ms, PSO 43.7008 ms and ZN 61.8571ms.