Closed-loop stability of systems driven by real-time, dynamic optimization algorithms
Closed-loop stability of systems driven by real-time, dynamic optimization algorithms
复制标题
由实时动态优化算法驱动的系统闭环稳定性
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
Eric Feron
中科院分区：
文献类型：
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作者：
Lawrence K. McGovern;Eric Feron
滚动时域控制（RHC）方案使用在线优化来找到有限时域控制输入到受约束的动态系统。本文研究了RHC中优化算法与闭环动态系统之间的关系。过去的研究RHC假设的优化算法提供了一个最佳的解决方案，在一个固定的时间间隔。由于RHC通常采用二次规划，通常只能近似求解，因此这个前提是无效的。而不是传统的最优性假设，本文假设所提供的解决方案是次优的。给出了闭环系统稳定的一个充分条件，该条件是给定的控制序列是最优的，具有容差/spl epsiv/。此外，一个边界推导出的计算数量，找到一个/spl epsiv/-最优解从一个温暖的开始，使用一个通道点的方法。只要这个数量的计算可以在小于动态系统的时间步长内进行，就可以保证闭环是稳定的。
The receding horizon control (RHC) scheme uses online optimization to find a finite-horizon control input to a constrained dynamic system. This paper examines the relationship between the optimization algorithm and the closed-loop dynamic system in RHC. Past research on RHC has assumed that the optimization algorithm provides an optimal solution in a fixed time interval. Since RHC typically employs quadratic programming, which is usually solved only approximately, this presupposition is not valid. Instead of making the traditional optimality assumption, this paper supposes that the provided solutions are only suboptimal. A sufficient condition is derived for closed-loop stability given control sequences which are optimal with tolerance /spl epsiv/. Also, a bound is derived for the number of computations to find an /spl epsiv/-optimal solution from a warm start using an interior-point method. As long as this number of computations can be carried out in less than the time step of the dynamic system, the closed-loop is guaranteed to be stable.