一类非线性大系统分散自适应预设性能有限时间跟踪控制

研究一类非线性互联大系统的分散自适应预设性能有限时间跟踪控制问题.结合神经网络自适应技术、实际有限时间控制理论和预设性能控制方法,提出一种新的预设性能控制设计方法,以解决传统预设性能方法难以实现分散控制的问题.所设计的控制器能够保证大系统中各个子系统的跟踪误差被有限时间性能函数约束,在任意给定的停息时间内收敛到平衡点的一个给定的邻域内,且该闭环大系统的所有信号是实际有限时间稳定的.特别地,该停息时间与系统初始状态无关.两个仿真例子验证了所提出控制方法的有效性和优越性.

Decentralized adaptive prescribed performance finite-time tracking control for a class of large-scale nonlinear systems

The decentralized adaptive prescribed performance finite-time tracking control problem is studied for a class of nonlinear interconnected large-scale systems. A new prescribed performance control design method is proposed combining the neural network adaptive technology, the practical finite-time control theory and the prescribed performance control method. The problem of that the traditional prescribed performance method is hard to realize decentralized control is solved. The designed controllers can guarantee that the tracking errors of all the subsystems in the large-scale system are constrained by a finite-time performance function, and the tracking errors can converge to a predetermined neighbourhood of the equilibrium within an arbitrarily given settling time. And all of the signals in the closed-loop large-scale system are practically finite-time stable. Especially, the settling time is irrelevant to the initial system states. Two simulation examples are given to illustrate the effectiveness and superiority of the proposed control method.