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Human-in-the-Loop Systems with Inner and Outer Feedback Control Loops: Adaptation, Stability Conditions, and Performance Constraints*

机译:具有内部和外部反馈控制回路的环内系统:适应性,稳定性条件和性能约束*

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In this paper, we focus on human-in-the-loop physical systems with inner and outer feedback control loops. Specifically, our problem formulation considers that inner loop control laws use a model reference adaptive control approach to suppress the effect of system uncertainties such that the overall physical system operates close to its ideal behavior as desired in the presence of adverse conditions due to failures and/or modeling inaccuracies. Moreover, we consider that the outer loop control laws exist owing to employing either sequential loop closure and/or high-level guidance methods. As it is true in practice, in addition, humans are considered to inject commands directly to the outer loop dynamics in response to the changes in the physical system, where the outer loop commands affect inner loop dynamics in response to the commands received from the humans as well as in response to the changes in the physical system. The presence of humans can result in system instability, even when the resulting physical system augmented with inner and outer feedback control loops yield to stable trajectories in the absence of humans. This paper addresses this problem by proving a sufficient stability condition for the overall physical system with human dynamics modeled as a linear time-invariant system with human reaction time-delay, where this condition does not depend on system uncertainties similar to our recent theoretical results. Furthermore, inner loop system errors during the transient phase of adaptively suppressing system uncertainties can severely affect the human-outer loop interactions. We also address this issue by utilizing a recently proposed set-theoretic model reference adaptive control approach at the inner loop for enforcing a user-defined performance constraint on the norm of the system error trajectories, where we show how the selection of this constraint affects the overall physical system. Finally, the efficacy of our results is demonstrated through an illustrative numerical example for an adaptive flight control application with a Neal-Smith pilot model.
机译:在本文中,我们将重点放在具有内部和外部反馈控制回路的人在环物理系统中。具体来说,我们的问题陈述认为内环控制定律使用模型参考自适应控制方法来抑制系统不确定性的影响,从而使整个物理系统在由于故障和/或不利条件而存在的不利条件下,按预期接近其理想行为或建模不正确。此外,我们认为,由于采用了顺序循环闭合和/或高级指导方法,因此存在外部循环控制法则。在实践中,确实如此,此外,人们还被认为是响应物理系统的变化而将命令直接注入到外部循环动力学中,其中,外部循环命令会响应于从人类接收到的命令而影响内部循环动力学。以及对物理系统变化的响应。人的存在会导致系统不稳定,即使在没有人的情况下,使用内部和外部反馈控制回路增强的最终物理系统产生稳定的轨迹时,也是如此。本文通过为人体动力学的整体物理系统提供足够的稳定性条件来解决此问题,人体动力学被建模为具有人类反应时间延迟的线性时不变系统,其中该条件不依赖于类似于我们最近的理论结果的系统不确定性。此外,在自适应抑制系统不确定性的过渡阶段,内环系统错误会严重影响人与外环的相互作用。我们还通过在内环处使用最近提出的集合理论模型参考自适应控制方法来解决此问题,该方法用于对系统错误轨迹的范数强制执行用户定义的性能约束,其中我们展示了该约束的选择如何影响系统性能。整体物理系统。最后,通过一个带有Neal-Smith飞行员模型的自适应飞行控制应用的说明性数值示例,证明了我们的研究结果的有效性。

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