ICOPE-15-1183 Design and Implementation of Particle Swarm Optimization Algorithm-Based Finite-Time Convergent Sliding Mode Control for Solar Inverters

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Abstract

This paper proposes a particle swarm optimization algorithm-based finite-time convergent sliding mode control for the application of solar inverters. Though classic sliding mode control (SMC) is insensitive to parameter variations and disturbances, it has an infinite system-state convergence time. For high-accuracy tracking control, finite-time convergent sliding mode control (FTCSMC) is developed and provides finite system-state convergence time. But, the chatter problem still exists in FTCSMC, and such problem will incur high solar inverter voltage harmonics and slow dynamic response. To obtain high-quality solar inverter output voltage, the particle swarm optimization (PSO) algorithm is applied to optimally tune the control gains of the FTCSMC for eliminating the chatter. By combining a FTCSMC with PSO algorithm, a closed-loop solar inverter yields good performance under various loading. Simulation and experimental results show that the proposed control can achieve low total harmonic distortion (THD) under nonlinear loading conditions and fast dynamic response under transient loading conditions. Because the proposed control is simpler to implement than prior techniques and offers more exact and rapid convergence, this paper will be of interest to designers of related sustainable energy systems.

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