Parallel Distributed Compensation-PID Controller Design for Maximum Power Point Tracking of Dynamic Loaded Photovoltaic System

Control issues come from the output voltage of PV installations and systems operating in a range of irradiance and temperature. By using a DC converter, such systems are able to maintain a constant output voltage despite fluctuations in the generated voltage and load. The design of a maximum power point tracking (MPPT) on DC converter controller is presented in this article for a system. Fractional Order-Proportional Integral Derivative (FO-PID) and Parallel Distributed Compensation-Proportional Integral Derivative (PDC-PID) controllers have been implemented to the system converter as a proposed control approach. Particle Swarm Optimization (PSO) is used as optimization technique for determining the optimal parameters of (FO-PID) and (PDC-PID) controllers for tracking the output voltage from trained Adaptive Neuro Fuzzy Inference System (ANFIS) that is corresponding to maximum power generated from (PV) module. The PV system with the dynamic load is modeled and simulated by using the MATLAB/Simulink environment. The system performance is displayed in the form of a family of curves under different operating conditions

Optimal PID control of a brushless DC motor using PSO and BF techniques

This paper presents a Particle Swarm Optimization (PSO) technique and bacterial foraging (BF) technique for determining the optimal parameters of (PID) controller for speed control of a brushless DC motor (BLDC) where the (BLDC) motor is modeled in simulink in Matlab. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot