基于自适应遗传算法的半主动悬架模糊控制研究

模糊规则的正确选择是半主动悬架模糊控制器设计的关键和难点，本文提出一种自适应地选择交叉概率和变异概率的遗传算法，以车身垂直加速度均方根值为优化目标,对汽车半主动悬架模糊控制规则进行优化，以达到提高半主动悬架模糊控制器的控制效果，改善汽车行驶平顺性的目的。为了证明该优化方法的可行性，将该自适应遗传算法优化的模糊控制器对汽车半主动悬架进行控制，并建立Matlab文本与Simulink相结合的仿真模型。仿真结果表明：优化后的半主动悬架车身垂直加速度均方根值减小,汽车行驶的平顺性得到了提高。

Research on Semi-active Suspension Fuzzy Control Based on Adaptive GA

The correct choice of the fuzzy rules is the key and difficult in fuzzy controller design, this paper applies an genetic algo- rithm that can adaptively select crossover probability and mutation probability. RMS value of the body vertical acceleration are opti- mization goals, the ear semi-active suspension fuzzy control rules are optimized, to improve the semi-active suspension control effect of the fuzzy controller, to achieve the purpose of improving vehicle ride comfort. To demonstrate the feasibility of this optimization, applying an optimized fuzzy control method based on improved genetic algorithm, a vehicle semi-active suspension is controlled and an associated simulation model is established using Maflab code and Simulink diagram. Simulation results show that optimized semi- active suspension body vertical acceleration RMS values are significantly reduced, the car ride comfort is improved.