无人机全电式自主刹车系统滑模极值搜索控制

常规主动刹车系统采用在线辨识跑道特征的算法,但仍需依赖摩擦模型先验知识,难以应对复杂跑道工况.为克服上述问题,提出一种滑模极值搜索控制策略并应用于无人机全电式自主刹车系统.考虑电动作动机构非线性特性,建立系统的状态空间模型并合理简化为严格反馈形式,采用超扭曲算法估计结合系数的梯度,结合反馈线性化控制律得到刹车压力参考值,证明此控制作用下可实现对未知最优滑移率的渐近跟踪.采用反演控制的思想设计无抖振滑模控制器实现对参考刹车压力的跟踪.利用Lyapunov方法获得系统的渐近稳定性条件并分析控制参数对系统的影响.半实物仿真试验结果表明控制策略的有效性.

Sliding-mode extremum-seeking control for all-electric active braking system in unmanned aerial vehicle

Given the online identification of the runway characteristics and the prior knowledge about the friction model, the conventional active braking system is still unable to handle complicate runway conditions. To tackle this problem, we propose a sliding-mode extremum-seeking controller for the all-electric active braking system in unmanned aerial vehicle. For this controller, we develop a nonlinear state space model by considering nonlinearities and uncertainties in electromechanical actuators, and then, this controller is simplified into a strict feedback linearization form, in which the gradient of the friction coefficient is directly estimated by using a modified generalized Super-Twisting algorithm, and the feedback linearization control law is employed to generate the reference braking pressure for the braking pedal to realize the asymptotic tracking for the unknown optimal slip rate. The inverse control concept is adopted in the design of the chatter-free sliding-mode controller to realize the tracking of the reference breaking pressure. By using Lyapunov theory, we derive the asymptotic stability conditions for the control system, and determine the effects of the controller parameters upon the system. Hardware-in-the-loop experimental results show that the proposed control approach is highly robust with respect to the various runway surface conditions.