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Solving the nonlinear dynamic control problems by GA with structurizing the search space

机译:通过结构化搜索空间用遗传算法解决非线性动态控制问题

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摘要

We propose a new search method of genetic algorithm (GA), which reduces the difficulties of the design of the fitness function. In the method, the control objective is divided into some intermediate control objectives according to the control strategy. The search process progresses with the fitness function corresponding to the intermediate control objective, and the process is controlled by switching the fitness function based on the average fitness value of the current candidate solutions so that the optimum solution with desired quality may be found. Thus, the search space is structured repeatedly during the search process by switching the fitness function based on the quality of the current candidate solutions. In order to confirm the availability of the proposed method, the swing-up control of the cart-pendulum system is used as an example, and some simulation results are given.
机译:我们提出了一种新的遗传算法搜索方法,减少了适应度函数设计的难度。该方法根据控制策略将控制目标分为一些中间控制目标。搜索过程以与中间控制目标相对应的适应度函数进行,并且通过基于当前候选解的平均适应度值切换适应度函数来控制该过程,从而可以找到具有期望质量的最优解。因此,通过基于当前候选解的质量切换适应度函数,在搜索过程中重复构造搜索空间。为了确认所提方法的有效性,以小车摆系统的上摆控制为例,给出了一些仿真结果。

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