Fuzzy Optimal Control Approach in Low-Thrust Orbit Transfer Problem

A. Razavi, A. Kosari
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引用次数: 1

Abstract

In this paper, the optimal low thrust planar orbit transfer problem is solved utilizing a fuzzy optimal control algorithm. Firstly, dynamic equations are presented in a discretized form, then all the design variables and constraints are transformed to fuzzy space, while minimizing the performance index and also satisfying transversallity conditions. Applying the concept of membership functions based on expert experience, the designed cost function associated with operational constraints are transformed to fuzzy relations through specific membership functions. Applying Bellman-Zadeh approach, the optimal control problem can be converted to a parameter optimization. Combining the performance index and problem’s constraints in a scalar function, necessary optimality conditions are achieved in a form of nonlinear algebraic equations. Finally, to solve this set of equations, the gradient-based method is used. In comparison with the exact form of the problem, the efficiency of the proposed algorithm is highlighted in terms of time and accuracy. In the fuzzy optimal control, a control designer could take advantage of determining the allowed limit for cost function. This algorithm could be successfully extended to fixed state or fixed control problems which is time-consuming in scope of the classical optimal control.
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低推力轨道转移问题的模糊最优控制方法
本文采用模糊最优控制算法求解低推力平面轨道最优转移问题。首先将动力学方程离散化,然后将所有设计变量和约束转化为模糊空间,同时使性能指标最小化并满足横向条件。应用基于专家经验的隶属度函数概念,通过特定的隶属度函数将与操作约束相关的设计成本函数转化为模糊关系。利用Bellman-Zadeh方法,将最优控制问题转化为参数优化问题。将性能指标与问题约束结合在标量函数中,以非线性代数方程的形式得到了必要的最优性条件。最后,采用基于梯度的方法求解该方程组。与问题的精确形式相比,该算法在时间和精度方面的效率得到了突出的体现。在模糊最优控制中,控制设计者可以利用确定代价函数的允许极限。该算法可以成功地推广到经典最优控制中耗时较长的固定状态或固定控制问题。
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