弹道
控制理论(社会学)
轨迹优化
非线性系统
计算机科学
线性化
理论(学习稳定性)
反馈线性化
点(几何)
趋同(经济学)
数学
最优控制
数学优化
控制(管理)
人工智能
天文
机器学习
物理
量子力学
经济
经济增长
几何学
作者
M.J. van Nieuwstadt,Richard M. Murray
标识
DOI:10.1002/(sici)1099-1239(199809)8:11<995::aid-rnc373>3.0.co;2-w
摘要
This paper considers the problem of real-time trajectory generation and tracking for nonlinear control systems. We employ a two-degree-of-freedom approach that separates the nonlinear tracking problem into real-time trajectory generation followed by local (gain-scheduled) stabilization. The central problem which we consider is how to generate, possibly with some delay, a feasible state space and input trajectory in real time from an output trajectory that is given online. We propose two algorithms that solve the real-time trajectory generation problem for differentially flat systems with (possibly non-minimum phase) zero dynamics. One is based on receding horizon point to point steering, the other allows additional minimization of a cost function. Both algorithms explicitly address the tradeoff between stability and performance and we prove convergence of the algorithms for a reasonable class of output trajectories. To illustrate the application of these techniques to physical systems, we present experimental results using a vectored thrust flight control experiment built at Caltech. A brief introduction to differentially flat systems and its relationship with feedback linearization is also included. © 1998 John Wiley & Sons, Ltd.
科研通智能强力驱动
Strongly Powered by AbleSci AI