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Fuzzy Optimal Control Approach in Low-Thrust Orbit Transfer Problem

机译:低推力轨道转移问题的模糊最优控制方法

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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.
机译:本文利用模糊最优控制算法解决了最佳低推力平面轨道传递问题。首先,动态方程以离散形式呈现,然后所有的设计变量和约束都被转换为模糊空间,同时最小化性能指数并满足横向性条件。根据专家体验应用隶属函数函数的概念,通过特定的成员函数转换与操作约束相关的设计成本函数。应用Bellman-Zadeh方法,可以将最佳控制问题转换为参数优化。将性能指数和问题的约束结合在标量函数中,以非线性代数方程的形式实现了必要的最优条件。最后,为了解决这组方程,使用基于梯度的方法。与问题的确切形式相比,所提出的算法的效率在时间和准确性方面突出显示。在模糊最优控制中,控制设计器可以利用确定成本函数的允许限制。该算法可以成功扩展到固定状态或固定控制问题,该问题在经典最优控制范围内耗时。

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