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Synergetic structure-control design via a hybrid gradient-evolutionary algorithm

机译:混合梯度进化算法的协同结构控制设计

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This paper proposes a synergetic approach to design a planar parallel robot with its control system. In this proposal, the design problem is stated as a dynamic optimization problem with dynamic and static constraints on both the robot parameters and the control input to the robot. Control parameterization via PID controllers is used to rewrite the dynamic optimization problem as a nonlinear programming problem, which is solved by using a hybrid gradient-evolutionary optimization technique. The dynamic optimization problem presents singularity regions in the design space requiring the use of the proposed hybrid gradient-evolutionary optimization technique. The rationale behind the proposed hybrid algorithm lies in using a exploratory search mechanism for finding the initial guess to the fine search mechanism, which is used to search in a local region of a solution. We discuss both the results of the proposed optimization technique and the experimental results of the robot designed with the proposed approach. In addition, the result provided by the proposed synergetic design approach is compared with a sequential design approach, showing the advantages of the synergetic approach.
机译:本文提出了一种协同方法来设计带有控制系统的平面并联机器人。在此建议中,设计问题被描述为一个动态优化问题,在机器人参数和对机器人的控制输入上都具有动态和静态约束。通过PID控制器进行控制参数化可将动态优化问题改写为非线性规划问题,可通过使用混合梯度进化优化技术来解决。动态优化问题在设计空间中出现了奇异区域,需要使用所提出的混合梯度进化优化技术。提出的混合算法的基本原理是使用探索性搜索机制来查找对精细搜索机制的初始猜测,该搜索机制用于在解决方案的局部区域中进行搜索。我们讨论了所提出的优化技术的结果,以及使用所提出的方法设计的机器人的实验结果。此外,将所提出的协同设计方法提供的结果与顺序设计方法进行了比较,显示了协同方法的优点。

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