In this paper water cycle algorithm based fractional order PI controller (FOPI) is proposed for virtual flux oriented control of three phase grid connected PWM rectifier. FOPI controller makes the PWM rectifier control more robust due to the fractional behavior. Fractional order controllers have additional degree of freedom and so wider range of parameters is available to provide better control and robustness in the plant. The optimization and design of FOPI controller is done using water cycle algorithm (WCA). WCA is an optimization method inspired by monitoring the water cycle operation and flow of water bodies like streams and rivers in the direction of sea. The performance of FOPI controller is compared with classical integer order PI controller. The parameters of PI and FOPI controllers are optimized and designed using WCA technique leading to WCA-PI and WCA-FOPI controllers. The system is tested using MATLAB/Simulink. The simulati on results verify the better performance of WCA-FOPI in terms of settling time, rise time, peak oversh oot and Total Harmonic Distortion (THD) of grid current. A robustness measurement with line filter parametric variations and non ideal supply voltage (unbalance and distorted supply voltage) is carried out. The WCA-FOPI demonstrates more robustness as compared to WCA-PI. Simulation findings validate the WCA-FOPI controller outcomes as compared to WCA-PI in terms of control effect and robustness.

No abstract

The high-performance grid-interfaced inverters are in demand as they are rapidly used in renewable energy systems. The main objective of grid-interfaced inverters is to inject high-quality active and reactive power with sinusoidal current. Many control schemes have been proposed earlier in the literature, but the operation under parametric uncertainties has not been given much attention. In this article, an adaptive network–based fuzzy inference control algorithm for a three-phase grid-interfaced inverter under parametric uncertainties is proposed. The main purpose of the proposed technique is to enhance the response time, decrease the steady-state oscillation in the injected active and reactive power and enhance the power quality even with parametric uncertainties. For assessment and evaluation reason, the conventional proportional–integral control is compared with the proposed controller. For a fair comparison, the gain setting for the proportional–integral control is obtained by Particle swarm optimization algorithm. The suggested system is developed and simulated in MATLAB/Simulink. Simulation results demonstrate that both the controllers work well to regulate the powers to required values, even with parametric variations. However, the proposed control demonstrates superiority in comparison to conventional proportional–integral control in terms of speedy response, decreased steady-state fluctuations, better power quality and increased robustness. The rise time and fluctuations in the per-unit active and reactive power are much less with the proposed control. Total harmonic distortion of the injected current and grid current are significantly better than the conventional proportional–integral control.

No abstract

No abstract