Chaos evolution optimization with feasible region analysis for stability enhancement in cascaded converters

This paper presents an effective method for analyzing and optimizing the stability of a three-phase rectifier system cascaded with DC-DC converters under generalized PI control. The study focuses on non-smooth chaotic phenomena caused by boundary collision bifurcation. Through stroboscopic mapping and Floquet theory, the method analyzes bifurcation behavior with respect to both control and circuit parameters, accurately identifying feasible parameter regions with clear stability boundaries. This bifurcation-based approach provides clearer insights into chaotic mechanisms and requires less computational effort compared to conventional methods. To achieve optimal performance within this complex parameter space, a Chaotic Evolution Optimization (CEO) algorithm is developed. The algorithm efficiently explores high-dimensional parameter spaces using chaotic dynamics, suppresses PWM saturation, and improves stability by systematically minimizing a composite objective function. This transforms heuristic parameter tuning into a stability-constrained optimization process. The resulting methodology reduces dependence on empirical experience while enhancing resilience to load variations, enabling more reliable system operation across different working conditions.