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Design of robust optimal regulator considering state and control nonlinearities

机译:考虑状态和控制非线性的鲁棒最优调节器设计

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Most real systems can be considered as a nonlinear and parameters of the systems may have uncertainties and external disturbances. Hence, in this paper, using the power series algorithm (PSA) based on State Dependent Riccati Equations (SDRE) and considering the proposed conditions that guarantee the asymptotic stability, the optimal regulator problem for a particular class of nonlinear systems is solved. Also, according to the specified pattern in the modified PSA (MPSA) method, weighting matrices are used as a function of state variables to achieve the better regulatory responses. Simulations are carried out on the Lorenz's chaotic system with uncertainties and external disturbances. The efficiency of optimal regulators the PSA and the MPSA methods in eliminating the external disturbances and being robust to uncertainties are compared together. The results show that the values of the performance index and the control cost in the MPSA method are smaller than the PSA method. Then the regulatory response in the MPSA method is more efficient.
机译:可以将大多数实际系统视为非线性系统,并且系统参数可能具有不确定性和外部干扰。因此,在本文中,使用基于状态相关Riccati方程(SDRE)的幂级数算法(PSA),并考虑了提出的保证渐近稳定性的条件,从而解决了特定类别非线性系统的最优调节器问题。同样,根据修改后的PSA(MPSA)方法中的指定模式,将加权矩阵用作状态变量的函数,以实现更好的调节响应。在具有不确定性和外部干扰的洛伦兹混沌系统上进行了仿真。将最佳调节器PSA和MPSA方法在消除外部干扰和对不确定性具有鲁棒性方面的效率进行了比较。结果表明,MPSA方法的性能指标和控制成本值小于PSA方法。这样,MPSA方法中的监管响应就会更加有效。

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