Smart Intelligent Suspension Control System Based on Soft and Quantum Computing: Part Ⅰ. Optimization with a new type of fitness function

摘要

A mathematical model-based design methodology for a robust intelligent semi-active suspension control system for passenger cars based on soft and quantum computing was developed. A globally optimized teaching signal for damper control was generated by genetic algorithm, the fitness function of which is set to satisfy conflicting requirements such as riding comfort and stability of the car body. Running condition was also varied between flat and undulated surface. The control performance of optimized knowledge base were evaluated and compared by computer simulations and field tests. Robust knowledge base design with quantum optimization is suggested.