Distributed Adaptive Neural Fixed-Time Tracking Control of Multiple Uncertain Mechanical Systems With Actuation Dead Zones
针对多个不确定机械系统在驱动死区下的固定时间跟踪控制问题，提出两种分布式自适应神经控制方案，使所有跟随者在预定时间内以足够精度跟踪领导者。
This article is mainly concerned with the fixed-time tracking control problem for multiple uncertain mechanical systems with actuation dead zones. As the dead zones and control gains are time varying and completely unknown, the control impact on mechanical system becomes completely unknown, making the achievement of fixed-time tracking control nontrivial. The existing studies on fixed-time tracking control cannot effectively estimate and compensate such dead zones, resulting in the upper bound of convergence time being uncertain and even system becoming unstable. To compensate the dead zones in a fixed time, we introduce a bound estimation method to estimate the impact of dead zones and design two fixed-time adaptive laws. Two cases on system uncertainties are considered. By introducing distributed control method, adaptive control method, neural networks and some skillful treatments, two novel distributed adaptive neural fixed-time tracking control schemes are proposed. It is confirmed that, with the proposed control schemes, all followers which are uncertain mechanical systems with completely unknown dead zones track the leader with sufficient precision in a predefined time.