This work is concerned with the prescribed performance tracking control for a family of nonlinear nontriangular structure systems under uncertain initial conditions and partial measurable states. By combining neural network and variable separation technique, a state observer with a simple structure is constructed for output-based finite-time tracking control, wherein the issue of algebraic loop arising from a nontriangular structure is circumvented. Meanwhile, by using an error transformation, the developed control scheme is able to ensure tracking with a prescribed accuracy within a pregiven time at a preassigned convergence rate under any bounded initial condition, eliminating the long-standing initial condition dependence issue inherited with conventional prescribed performance control methods, and guaranteeing the predeterminability of convergence time simultaneously. Two simulation examples also demonstrate the effectiveness of the presented control strategy.

中文翻译：

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不确定初始条件下的规定性能跟踪控制：神经自适应输出反馈方法。

这项工作涉及在不确定的初始条件和部分可测状态下对一族非线性非三角结构系统进行规定的性能跟踪控制。通过结合神经网络和变量分离技术，构造了一种结构简单的状态观测器，用于基于输出的有限时间跟踪控制，避免了非三角形结构引起的代数环问题。同时，通过使用误差变换，所开发的控制方案能够确保在任何有界初始条件下在给定时间内以预定收敛速度以预定精度进行跟踪，消除了传统规定性能所继承的长期存在的初始条件依赖性问题控制方法，同时保证收敛时间的可预定性。两个仿真例子也证明了所提出的控制策略的有效性。