基于改进遗传算法的汽车主动悬架控制器设计

Design of Controller of Active Suspension Based on Improved Genetic Algorithms

摘要:

为解决在汽车主动悬架系统中所采用的一般模糊控制策略自适应能力差的特点,提出了一种可以自适应调节的模糊控制策略,采用解析式模糊规则法;利用新型的改进遗传算法优化不同状态下误差与误差变化率的修正因子,从而找到最优的模糊规则,匹配当前状态下最佳模糊控制器的参数;利用Matlab/Simulink对主动悬架系统进行了仿真,结果表明该控制器相较于一般模糊控制器可以有效地改善汽车悬架在不同行驶状态下的稳定性和平顺性,通过优化过后的控制系统有较强的鲁棒性和较好的适应性。

Abstract:

To solve poor self-adaptive of common fuzzy logic strategy adopted by the active suspension of vehicle,the paper puts forward the fuzzy logic strategy with adaptive control characteristics,which use fuzzy control rule of analytical formula. The correction of error and error rate which is two input of fuzzy controller in different state is optimized by the new improved genetic algorithm,in that the optimal fuzzy control rule of the controller is found. The active suspension system with improved fuzzy logic controller was simulated by Matlab/Simulink. The simulation results demonstrate that the suspension with the fuzzy logic controller can effectively improve vehicle’s riding performances and handling performance compared with conventional passive suspension and the active suspension with common fuzzy logic controller. The controller by optimized has strong robustness and stability.