Self-learning salp swarm optimisation based controller design for photovoltaic reverse osmosis plant

In this work, a self-learning salp swarm optimisation (SLSSO) based controller design is proposed for a photovoltaic reverse osmosis (RO) desalination unit. The SLSSO algorithm is proposed in order to improve the performance of salp swarm optimisation. The photovoltaic RO model considered is basically an interacting two-input-two-output (TITO) system. The interacting TITO system is first converted into two non-interacting sub-systems by designing an appropriate decoupler. Then, two proportional-integral-derivative (PID) controllers are designed by minimising the integral-of-squared-error (ISE) of respective non-interacting sub-system. The ISE is designed in terms of alpha and beta parameters for ease of simulation. The designed ISE is minimised using the proposed SLSSO algorithm. For showing the efficacy of SLSSO assisted PID controllers, other PID controllers are also obtained using some state-of-art optimisation algorithms. The results prove that SLSSO assisted PID controllers outperform other PID controllers.