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首页> 外文期刊>Journal of Optimization Theory and Applications >New Risk-Averse Control Paradigm for Stochastic Two-Time-Scale Systems and Performance Robustness
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New Risk-Averse Control Paradigm for Stochastic Two-Time-Scale Systems and Performance Robustness

机译:随机两次尺度系统的新规避风险范式和性能鲁棒性

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摘要

This work is concerned with the optimal control of stochastic two-time-scale linear systems with performance measure in a finite-horizon integral-quadratic form. Nature, modeled by stationary Wiener processes whose mean and covariance statistics are known, malevolently affects the state dynamics and output observations of the control problem class. With particular focus on the system performance robustness, the use of higher-order statistics or cumulants associated with the performance measure of chi-squared random variable type makes it possible to restate the stochastic control problem as the solution of a deterministic one, which subsequently allows disregarding all sample-path realizations by Nature acting on the original problem. The distinguishing feature of the risk-averse control paradigm is that the performance index is multiobjective in nature, being composed of both risk-neutral integrals and risk-sensitive costs associated with the ubiquitous linear-quadratic-Gaussian (LQG) and rather recent risk-sensitive control problems. Another issue that makes this class of control particularly interesting is the fact that Nature has the ability to exercise all the higher-order characteristics of the uncertain chi-squared performance measure. The efficient controller, having access to Nature's apriori statistical knowledge and employing dynamic output feedback, seeks to minimize the performance uncertainty that Nature can do over the set of mixed random realizations. Furthermore, the results herein potentially generalize the existing results for the single-objective H_2, H_∞, and risk-sensitive control problems to a substantially larger class of systems, wherein Nature selects mixed sample-path realizations that need not be Gaussian. That is, the entire probability density function of Nature's choices is not necessarily known except for its first two statistics. Finally, the numerical simulations for a two-time-scale longitudinal dynamics of the F-8 jet aircraft demonstrate that the proposed control paradigm has competitive performance in the closed-loop system responses and offers multiple levels of robustness for the system performance.
机译:这项工作涉及具有有限水平积分-二次形式的性能度量的随机二阶线性系统的最优控制。自然,用已知的均值和协方差统计量不变的维纳过程建模,恶意影响状态动态和控制问题类别的输出观察结果。特别关注系统性能的鲁棒性,使用与卡方随机变量类型的性能度量相关的高阶统计量或累积量可以重述随机控制问题,作为确定性解决方案的解决方案,这随后允许忽略了自然界解决原始问题的所有样本路径实现。规避风险的范式的显着特征是,绩效指标本质上是多目标的,既包含风险中性积分,又包含与普遍存在的线性二次高斯(LQG)以及最近的风险相关的风险敏感成本。敏感的控制问题。使此类控制尤为有趣的另一个问题是,自然具有执行不确定的卡方性能度量的所有高阶特征的能力。高效的控制器可以访问Nature的先验统计知识并采用动态输出反馈,以最大程度地减少Nature在混合随机实现集上可以实现的性能不确定性。此外,本文的结果可能将单目标H_2,H_∞和风险敏感控制问题的现有结果推广到实质上更大的系统类别,其中Nature选择不需要高斯的混合样本路径实现。也就是说,除自然选择的前两个统计量外,不一定知道其全部概率密度函数。最后,对F-8喷气飞机的两倍比例纵向动力学的数值模拟表明,所提出的控制范式在闭环系统响应中具有竞争性能,并为系统性能提供了多个级别的鲁棒性。

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