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reciprocal variable feedback: induced sensing for nonlinear systems design and control

机译：倒数反馈：感应感应的非线性系统设计与控制

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摘要

System performance can be significantly improved when both the design of the plant and of the controller are considered concurrently. Control theory can be applied to a broad variety of systems, including those that are physical in nature and many that are not. Despite the generality of control theory, there are many situations in which opportunities are missed for using less conservative control laws and simpler overall implementations. This is due to the use of formulations that do not explicitly reveal the existence of intrinsic information pertaining to the particular domain of application. Such is the case with many physical systems. However, the various constraints associated with physical reality (in the form of principles, laws, etc.) openup several possibilities which can be exploited for system design and control. In this paper, we propose the Reciprocal Variable Feedback principle as a means for facilitating the control of plants with complicated nonlinear dynamics in the presence ofparameter and/or structural uncertainty. The RVF principle exploits the effort-flow relationships associated with power interactions in order to assist in the design and control of physical processes. This is accomplished by using appropriate sensorsinstead of computation based on models (e.g., feedback linearization) and can be implemented within many physical domains. A motion control example is used to provide insight into the nature of the principle. It is expected that in the future, additionalprinciples will be identified and introduced for integrating design with the control of dynamical systems.
机译：当同时考虑工厂和控制器的设计时，可以显着提高系统性能。控制理论可以应用于各种各样的系统，包括那些物理上的系统和许多非物理上的系统。尽管控制理论很普遍，但在许多情况下，由于使用较不保守的控制律和更简单的整体实现而错过了机会。这是由于使用了未明确揭示与特定应用领域有关的内在信息的配方。许多物理系统就是这种情况。但是，与物理现实相关的各种约束（以原理，定律等形式）为系统设计和控制提供了多种可能性。在本文中，我们提出了倒数可变反馈原理，作为在存在参数和/或结构不确定性的情况下，对具有复杂非线性动力学的设备进行控制的一种便利方法。 RVF原理利用了与电源交互相关的工作流关系，以协助物理过程的设计和控制。这是通过使用适当的传感器而不是基于模型的计算（例如，反馈线性化）来实现的，并且可以在许多物理域内实现。运动控制示例用于深入了解原理的本质。可以预期，将来会发现并引入其他原理，以将设计与动态系统的控制集成在一起。

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