计及位置不确定的喷雾机喷杆系统仿形姿态渐近跟踪控制北大核心CSCD

针对喷雾机喷杆仿形系统中同时存在负载变化、未建模不确定项、物理参数摄动以及外部干扰等问题,提出了一种基于小波网络逼近的具有自适应性和鲁棒性的反步控制方法.首先,将含有不确定、未知和非线性项的喷杆仿形系统建立为完整的数学模型,将其等价转化为具有严格反馈的状态空间形式;其次,采用设计的小波基元去构造神经网络,在满足最优误差有界条件下逼近反步法中虚拟等效控制部分,选取自适应更新律估计系统中存在的未知参数,引入鲁棒补偿项减小复合干扰对系统的不利影响,降低了输入指令信号的阶次要求;最后,通过构造合适的Lyapunov函数,应用稳定性理论证明了闭环系统位置跟踪误差渐近收敛到原点.仿真结果表明,所提控制方法可实现喷雾机喷杆位置姿态快速升降机动调整,有效地增强了喷杆系统的鲁棒稳定性和控制精度.

Asymptotic Tracking Control on Profiling Posture of Sprayer Boom Systems With Position Uncertainties

An adaptive and robust backstepping method based on wavelet network approximation was proposed to solve the problems of load variation, unmodeled uncertainties, physical parameter perturbation and external disturbance in the sprayer boom profiling system. Firstly, a complete mathematical model for the boom system with uncertainties, unknowns and nonlinear terms was established and transformed into a state space form with strict feedback. Secondly, the designed wavelet primitive was used to construct the neural network, to approximate the virtual equivalent control part of the backstepping method under the condition that the optimal error is bounded. The adaptive update law was selected to estimate the unknown parameters. The robust compensation term was introduced to reduce the adverse effect of the composite interference on the system. The input command signal order requirement was reduced. Finally, suitable functions were constructed by means of the Lyapunov stability theory, to prove that the position tracking error of the closed-loop system asymptotically converges to the origin. The simulation results show that, the proposed control method can realize the rapid maneuver adjustment of the sprayer boom position and posture, and effectively enhance the robust stability and control accuracy of the boom system.