模型预测控制
控制理论(社会学)
设定值
运动学
控制器(灌溉)
完整约束
完整的
控制工程
计算机科学
最优控制
二次方程
数学
控制(管理)
工程类
数学优化
人工智能
物理
几何学
经典力学
农学
生物
作者
Mario Rosenfelder,Henrik Ebel,Jasmin Krauspenhaar,Peter Eberhard
出处
期刊:Automatica
[Elsevier]
日期:2023-06-01
卷期号:152: 110972-110972
被引量:8
标识
DOI:10.1016/j.automatica.2023.110972
摘要
Non-holonomic systems are of immense practical value and increasingly subject to automation. However, controlling them accurately, e.g., when parking vehicles, is challenging for automatic control methods, including model predictive control (MPC). Combining results from MPC theory and sub-Riemannian geometry in the form of homogeneous nilpotent system approximations, this paper proposes the first comprehensive, ready-to-apply design procedure for MPC controllers to steer controllable, driftless non-holonomic systems into given setpoints. It can be ascertained that the resulting controllers nominally asymptotically stabilize the setpoint for a large-enough prediction horizon. The design procedure is exemplarily applied to four systems, including the kinematic car and a differentially driven mobile robot with up to two trailers. The controllers use a non-quadratic cost function tailored to the non-holonomic kinematics. Novelly, it is proven that a quadratic cost employed in an otherwise similar controller is insufficient to reliably asymptotically stabilize the closed loop for all considered vehicles. Since quadratic costs are the conventional choice in control, this highlights the relevance of the findings. To the knowledge of the authors, it is the first time that MPC controllers of the proposed structure are formulated and applied to non-holonomic systems beyond very simple ones, in particular (partly) on hardware.
科研通智能强力驱动
Strongly Powered by AbleSci AI