In this paper, a computationally lightweight approximate robust nonlinear model predictive control (NMPC) law is proposed based on a pair of input-to-state control Lyapunov function and robust control barrier function. The result builds upon and augments a recently introduced nominal infinitesimal- horizon NMPC scheme which permits small-sized quadratic programs to compute the feedback law for nonlinear constraint systems on embedded hardware in real time. Numerical experiments for nonlinear constrained spacecraft control and comparison to other robust NMPC schemes from the literature demonstrate the effectiveness of the proposed scheme.
Designing trajectory tracking controllers for nonlinear systems remains a significant challenge, traditionally requiring precise mathematical models and complex analytical derivations. While the Internal Model Principle (IMP) provides a robust theoretical foundation for such problems, its application is often hindered...
Sathya Aswath Govind Raju, Berk Altiner, Zong-Xuan Sun et al.· 0 citations
This article addresses the problem of designing neural feedback controllers for unknown nonlinear systems. We propose an indirect data-driven framework that uses offline data to identify the system dynamics, upon which a neural feedback controller and a neural Lyapunov function are jointly synthesized. Input constraint...
This paper presents a new iterative learning control (ILC) scheme for affine nonlinear systems of repetitive nature with unknown dynamics, combining model-free feedback linearization with a two-dimensional (2D) system framework. The method eliminates the need for prior model knowledge by employing model reference adapt...
Bo-Yu Wen, Xin Chen, Wojciech Paszke et al.· International Conference on...· 0 citations
Many practical dynamical models are inherently nonlinear and may exhibit complex growth conditions and uncertainties, which pose considerable challenges to controller design. In this paper, the tracking control issue for a category of high-order nonlinear systems with polynomial-type growth conditions is studied. Throu...
Zhuang Wen, Jing-Xing Li, Zhenguo Liu et al.· Actuators· 0 citations
Through rigorous mathematical analysis and numerical simulations, it can be concluded that the proposed control scheme can not only drive all system variables to converge to steady states within a prescribed time in probability, but also make the output track the desired signal without violating the output constraint.
Daohong Zhu, Lian-Di Fang, Hong-Yi Xia· Measurement and control (Lon...· 0 citations
This paper addresses the time-varying formation (TVF) control problem for linear multi-agent systems (MASs) with nonlinear dynamics, actuator bias and loss-of-effectiveness faults, and switching communication topologies with neural network approximation and Lyapunov stability theory.
Bo Wu, Zhang-Yi Zu, Xi-Sheng Zhan et al.· Transactions of the Institut...· 0 citations
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