A novel PSIM and Matlab co-simulation approach to particle swarm optimization tuning of PID controllers

The classical PID algorithm has proven to be a consistently popular solution across a range of different control applications. This popularity can be attributed to the algorithm offering both flexibility and robustness whilst being relatively simple to implement. The PID algorithm is given as: 1( 1) One important consideration for the optimal use of the PID controller is the selection of the parameters Kp, Tr and Td in Eq 1. Although a number of methods have been proposed for the selection of these parameters, such as the Ziegler-Nichols approach, this tuning operation continues to be a research theme. One modern approach which has been shown to give good results is the use of evolutionary algorithms such as in (1) and (2). The Particle Swarm Optimization (PSO) algorithm has proven to be particularly popular thanks to its simplicity, suitability as a function approximator and the favorable results it produces (3). This paper presents a new modeling technique as shown in Fig 2, featuring Co-Simulation between Matlab and PSIM, a specialist control and power electronics simulation environment. The tuned PID is applied to a buck converter, driven by a PV cell as shown in Fig 1. The novel solution is compared with and evaluated against a system which is tuned using a traditional method. The simulation results indicate that the controller developed using the PSO algorithm achieves a faster response time without adversely affecting peak errors. There are added benefits of this new approach, in terms of a shorter time scale for conceptual model development.