A Comprehensive Review on Optimization Techniques of Controller Based Vienna Rectifier used for Electric Vehicle Charging System

Optimization method helps to improve the performance of various control systems including PID, MPC, linear control, SMC and fuzzy logic control. In PID control, optimization studies focusing on proportional, integral and differential synchronization are achieved through methods such as Ziegler-Nichols and optimization models. MPC is based on functional models to predict future behaviors and optimization techniques such as quadratic functions and linear optimization to solve control problems, provide problem tracking, intervention and real time tracking of constraints. Adaptive control is characterized by the ability to recalibrate parameters in feedback to adapt to changes in power dynamics; this is based on the optimization process SMC, which aims to align the system state with a predefined sliding surface to increase resistance to interference and uncertainty. Optimization techniques such as Lyapunov-based analysis promote continuous synthesis, jitter reduction and rapid integration to effectively facilitate the control process. At the same time, fuzzy logic control is famous for its good knowledge of controlling nonlinear and uncertain systems through different words and fuzzy rules such as genetic and particle swarm algorithm to fine-tune policy and membership. Therefore enhance Robustness, stability and integrity (SDG 9) in an environment of complex uncertainty. In this process, optimization is the key to successfully monitoring performance, adjusting strategies to achieve desired goals, and solving real-world problems.