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Decentralized filtering adaptive constrained tracking control for interconnected nonlinear systems
International Journal of Robust and Nonlinear Control ( IF 3.9 ) Pub Date : 2020-06-08 , DOI: 10.1002/rnc.5008
Tong Ma 1
Affiliation  

This paper presents a novel decentralized filtering adaptive constrained tracking control framework for uncertain interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, a piecewise constant adaptive law will generate total uncertainty estimates by solving the error dynamics between the host system and decentralized state predictor with the neglection of unknowns, whereas a decentralized filtering control law is designed to compensate both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. In the control scheme, the nonlinear uncertainties are compensated for within the bandwidth of low‐pass filters, while the trade‐off between tracking and constraints violation avoidance is formulated as a numerical constrained optimization problem which is solved periodically. Priority is given to constraints violation avoidance at the cost of deteriorated tracking performance. The uniform performance bounds are derived for the system states and control inputs as compared to the corresponding signals of a bounded closed‐loop reference system, which assumes partial cancelation of uncertainties within the bandwidth of the control signal. Compared with model predictive control (MPC) and unconstrained controller, the proposed control architecture is capable of solving the tracking control problems for interconnected nonlinear systems subject to constraints and uncertainties.

中文翻译:

互联非线性系统的分散滤波自适应约束跟踪控制。

本文为不确定的非线性系统提出了一种新型的分散滤波自适应约束跟踪控制框架。每个子系统都基于已建立的分散状态预测器拥有自己的分散控制器。对于每个子系统,分段常量自适应定律将通过解决主机系统与分散状态预测变量之间的误差动态(忽略未知数)来生成总不确定性估计,而分散式滤波控制定律旨在补偿其他局部和不匹配的不确定性子系统,以及实现对主机系统的本地目标跟踪。全局目标的实现取决于每个子系统的局部目标的实现。在控制方案中 非线性不确定性在低通滤波器的带宽内得到补偿,而跟踪和约束违规避免之间的权衡被公式化为一个数值约束的优化问题,该问题可以定期解决。优先考虑避免约束违规,但代价是跟踪性能会下降。与有界闭环参考系统的相应信号相比,得出系统状态和控制输入的统一性能范围,其中假定控制信号带宽内的不确定性被部分抵消。与模型预测控制(MPC)和无约束控制器相比,
更新日期:2020-06-08
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