论文标题
具有国家依赖性不确定性的受约束系统的综合自适应控制和参考调查员
Integrated Adaptive Control and Reference Governors for Constrained Systems with State-Dependent Uncertainties
论文作者
论文摘要
本文为线性系统提出了一个自适应参考调速器（RG）框架，其匹配的非线性不确定性可以依赖于时间和状态，但均受状态和输入约束。所提出的框架利用L1自适应控制器（L1AC），该框架估算并补偿了不确定性，并根据统一的界限对实际状态和输入之间的误差以及名义（即不确定的无用）系统的误差提供了保证的短暂性能。 L1AC提供的均匀性能边界用于拧紧预先指定的状态和控制约束。然后，使用加强约束为标称系统设计了参考调查员，并保证了强大的约束满意度。此外，通过调整L1AC中的某些参数，可以系统地降低约束拧紧的保守主义。与现有解决方案相比，由于沿预测范围的不确定性传播，由于固有的不确定性补偿机制，由于去除了不确定性传播，因此提出的自适应RG框架可能会产生较少的保守结果，从而为约束执行而产生较少的保守性结果。飞行控制示例的仿真结果说明了提出的框架的功效。
This paper presents an adaptive reference governor (RG) framework for a linear system with matched nonlinear uncertainties that can depend on both time and states, subject to both state and input constraints. The proposed framework leverages an L1 adaptive controller (L1AC) that estimates and compensates for the uncertainties, and provides guaranteed transient performance, in terms of uniform bounds on the error between actual states and inputs and those of a nominal (i.e., uncertainty-free) system. The uniform performance bounds provided by the L1AC are used to tighten the pre-specified state and control constraints. A reference governor is then designed for the nominal system using the tightened constraints, and guarantees robust constraint satisfaction. Moreover, the conservatism introduced by the constraint tightening can be systematically reduced by tuning some parameters within the L1AC. Compared with existing solutions, the proposed adaptive RG framework can potentially yield less conservative results for constraint enforcement due to the removal of uncertainty propagation along a prediction horizon, and improved tracking performance due to the inherent uncertainty compensation mechanism. Simulation results for a flight control example illustrate the efficacy of the proposed framework.
