具有非凸输入约束的不确定严格反馈系统有限时间自适应跟踪控制  

Finite-time adaptive tracking control of uncertain strict-feedback systems with nonconvex input constraint

作　　者：张腾飞 李明星 ZHANG Teng-fei;LI Ming-xingy(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China)

机构地区：[1]北京航空航天大学自动化科学与电气工程学院,北京100191

出　　处：《控制与决策》2025年第2期608-616,共9页Control and Decision

基　　金：国家自然科学基金项目(61703020)。

摘　　要：针对一类具有非凸输入约束和外界干扰的不确定多输入多输出严格反馈非线性系统,提出一种有限时间自适应神经网络动态面跟踪控制方案.首先,通过引入非凸约束算子,将所设计反馈控制输入转化为与其同方向具有最大幅值的实际输入向量,进而保证实际控制输入始终保持在非凸约束集合内;然后,采用径向基神经网络逼近不确定连续函数向量,以解决控制增益矩阵上下界未知情形下的控制问题,并利用不等式放缩处理未知有界干扰;接着,利用反步法设计有限时间自适应动态面跟踪控制器,保证闭环系统所有信号均为一致最终有界的,实现期望轨迹的有限时间跟踪控制;最后,给出数值仿真算例以表明所提出控制方案的有效性.A finite-time adaptive neural network dynamic surface tracking control scheme is proposed for a class of uncertain multiple-input multiple-output strict-feedback nonlinear systems with nonconvex input constraint and external disturbance.Firstly,by introducing a nonconvex constraint operator,the designed feedback control input is transformed into the actual input vector with the largest value in the same direction,thus the actual control input is always kept in the nonconvex constraint set.Secondly,the radial basis neural network is used to approximate the uncertain continuous function vector to solve the control problem with unknown upper and lower bounds of the control gain matrix,and the inequality reduction is utilized to deal with the unknown bounded disturbance.Then,a finite-time adaptive dynamic surface tracking controller using the backstepping approach is proposed to ensure that all signals of the closed-loop system are ultimately uniformly bounded,and to realize the finite-time tracking control of the desired trajectory.Finally,a numerical simulation is provided to illustrate the effectiveness of the proposed control scheme.

关 键 词：非凸输入约束 有限时间稳定 动态面控制 自适应神经网络 反步设计 不确定严格反馈系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]