论文标题
基于不确定性和未知非线性的悬架系统的生物启发的参考模型，无近似控制
Approximation-free control based on the bioinspired reference model for suspension systems with uncertainty and unknown nonlinearity
论文作者
论文摘要
在悬架系统中通常不可避免地是不可避免的，通常使用模糊逻辑系统（FLS）或神经网络（NNS）解决。但是，这些方法受控制器的结构复杂性和巨大的计算成本的限制。同时，此类近似值的估计误差会受到采用的自适应定律和学习收益的影响。因此，鉴于上述问题，本文提出了基于一类不明性非线性的不确定悬架系统的生物启发的参考模型的无近似控制。所提出的方法在无近似控制中整合了生物启发的参考模型的出色振动抑制和规定性能函数（PPF）的结构优势。然后，提高了振动抑制性能，减轻了计算负担，并改善了瞬态性能，本文理论上对此进行了分析。最后，模拟结果验证了该方法，并且比较在良好的振动抑制，快速收敛和减少计算负担方面显示了所提出的控制方法的优势。
Uncertainty and unknown nonlinearity are often inevitable in the suspension systems, which were often solved using fuzzy logic system (FLS) or neural networks (NNs). However, these methods are restricted by the structural complexity of the controller and the huge computing cost. Meanwhile, the estimation error of such approximators is affected by adopted adaptive laws and learning gains. Thus, in view of the above problem, this paper proposes the approximation-free control based on the bioinspired reference model for a class of uncertain suspension systems with unknown nonlinearity. The proposed method integrates the superior vibration suppression of the bioinspired reference model and the structural advantage of the prescribed performance function (PPF) in approximation-free control. Then, the vibration suppression performance is improved, the calculation burden is relieved, and the transient performance is improved, which is analyzed theoretically in this paper. Finally, the simulation results validate the approach, and the comparisons show the advantages of the proposed control method in terms of good vibration suppression, fast convergence, and less calculation burden.
