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Near-optimal control laws based on Heuristic Dynamic Programming iteration algorithm

机译:基于启发式动态规划迭代算法的近最优控制律

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摘要

In this paper, the near-optimal control problem for a class of nonlinear time-delay systems with control constraints is solved by a novel Heuristic Dynamic Programming (HDP) iteration algorithm. First, a nonquadratic performance functional is introduced to overcome the control constraints, and then a new iterative HDP algorithm which contains local and global optimization searching processes, is developed to solve the optimal feedback control problem of the original constrained for time-delay system with convergence analysis. In the present control scheme, there are three neural networks used as parametric structures for facilitating the implementation of the iterative algorithm. One example is given to demonstrate the convergence and feasibility of the proposed optimal control scheme.
机译:本文通过一种新颖的启发式动态规划(HDP)迭代算法解决了一类具有控制约束的非线性时滞系统的近似最优控制问题。首先,引入非二次性能函数来克服控制约束,然后开发一种包含局部和全局优化搜索过程的新的迭代HDP算法,以解决具有收敛性的时滞系统的原始最优反馈控制问题。分析。在本控制方案中,存在三个神经网络用作参数结构,以促进迭代算法的实现。给出了一个例子来说明所提出的最优控制方案的收敛性和可行性。

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