基于单一输入规则的半主动悬架模糊控制方法研究

摘要

经典模糊推理过程中随输入变量个数增加,规则制定难度加大、规则数量以指数方式增加,且输入变量对系统性能影响是同级的.基于单一输入规则的模糊推理模型是将多维模糊控制转化为一维模糊控制,同时引入输入变量重要度因子.为此,根据单一输入规则的模糊推理理论设计了半主动悬架新型模糊控制算法,并由此构成了基于悬架阻尼独立控制的四通道整车控制方式.研究表明,所设计的单一输入规则的半主动悬架模糊控制算法具有较好的控制效果,所提出的基于单一输入规则的模糊控制四通道整车控制方式,具有结构清晰、控制效果好、易于实现和鲁棒性强等特点.%In the conventional fuzzy inference model, all the input items of systems are usually put into the antecedent part of each fuzzy rule. Consequently, both the numbers of fuzzy rules and parameters increase exponentially; and defining fuzzy rule becomes extremely difficult for large-scale systems; and the same dynamic importance degree of each input item, this proposed new fuzzy model can be extended to systems with each single input rule modules corresponds separately to one of the n input items, and with plural output items is summarized the products of the dynamic importance degree and the fuzzy inference result of earh single input rule modules for all the input items. So, this paper presents the control algorithm construction of a semi-active suspension system for a quarter car model using fuzzy reasoning based on single input rule modules. On the basis of the algorithm, the four-channel vehicle control mode is designed with four damper controllers. The simulation results show that the designed semi-active suspension damping control algorithm has better system performance; the proposed four-channel vehicle control mode based on a new fuzzy control algorithm with single input rule modules has such advantages such as simple structure, easy realization, good control effect and strong robustness.