Abstract
SummaryThis article presents a computationally efficient way of synthesizing linear parameter‐varying (LPV) controllers. It reviews the possibility of a separate observer and state feedback synthesis with guaranteed performance and shows that a standard mixed sensitivity problem can be solved in this way. The resultant output feedback controller consists of an LPV observer, augmented with dynamic filters to incorporate integral control and roll‐off properties, and an LPV state feedback gain. It is thus highly structured, which is beneficial for implementation. Moreover, it does not depend on scheduling parameter rates regardless of whether parameter‐dependent Lyapunov matrices are used during synthesis. A representative control design for active flutter suppression on an aeroelastic unmanned aircraft demonstrates the benefits of the proposed method in comparison with state‐of‐the‐art LPV output feedback synthesis.
Highlights
Linear parameter-varying (LPV) control is a powerful tool for designing self-scheduled control systems
Summary This article presents a computationally efficient way of synthesizing linear parameter-varying (LPV) controllers. It reviews the possibility of a separate observer and state feedback synthesis with guaranteed performance and shows that a standard mixed sensitivity problem can be solved in this way
The proposed two-step observer-based synthesis leads to an output feedback controller with guaranteed closed-loop performance as specified by a weighted mixed sensitivity problem
Summary
Linear parameter-varying (LPV) control is a powerful tool for designing self-scheduled control systems. These parameter variation rates are often difficult to measure, and the rate dependence of the controller is omitted in many application examples in the literature This issue of “practical implementability” has been addressed through specific synthesis formulations. A standard mixed sensitivity problem is formulated, but the controller is obtained through an observer synthesis step and a subsequent state feedback synthesis step Parameter-dependent Lyapunov matrices can be used for synthesis without leading to dependence on the derivative of the scheduling parameters This is an immediate consequence of the observer-based structure. While the restriction to an observer-based structure is a source of conservatism, it is shown in the application example in Section 4 that the benefit of using parameter-dependent Lyapunov matrices can outweigh this conservatism
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