Adana Science and Technology University, Electrical and Electronic Engineering, Adana, Turkey.
Yeditepe University, Electrical and Electronic Engineering, Istanbul, Turkey.
ISA Trans. 2018 May;76:67-77. doi: 10.1016/j.isatra.2018.03.002. Epub 2018 Mar 14.
In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided.
本文针对离散时间线性系统，开发了一种自适应控制器，该控制器考虑了参数不确定性、内部-外部非参数随机不确定性和时变控制信号延迟。此外，所提出的自适应控制以完全无模型的方式设计。尽管这些特性在文献中分别进行了研究，但在自适应控制文献中并未全部考虑。Q 函数用于估计所提出的自适应控制器的长期性能。控制策略基于长期预测值生成，该策略为不确定和不稳定系统搜索最优稳定控制信号。与最近文献中的控制律不同，所导出的控制律不需要初始稳定控制假设。学习误差、控制信号收敛性、最小化 Q 函数和瞬时奖励进行了分析，以在仿真环境中证明所提出的自适应控制器的稳定性和有效性。最后，提供了关于学习和控制信号参数收敛的关键见解。
