Abstract
Abstract In this paper, novel synthesis conditions for state-feedback Linear Parameter Varying (LPV) controller with Input Covariance Constraints (ICC) are developed. The synthesis conditions achieve the following design requirements 1) some constraints need to be satisfied on the control energy and 2) optimizing the performance outputs for the entire parameter space of the LPV system. These conditions are formulated as convex optimization problem with Parameterized Linear Matrix Inequalities (PLMIs) constraints. The effectiveness of the proposed approach is illustrated through numerical examples.
Highlights
Linear Parameter Varying (LPV) control techniques witnessed great interest in the past three decades [1, 2]
The synthesis conditions achieve the following design requirements 1) some constraints need to be satis ed on the control energy and 2) optimizing the performance outputs for the entire parameter space of the LPV system. These conditions are formulated as convex optimization problem with Parameterized Linear Matrix Inequalities (PLMIs) constraints
LPV systems can be divided into two main categories, gridding and polytopic LPV models [3]
Summary
Linear Parameter Varying (LPV) control techniques witnessed great interest in the past three decades [1, 2]. The ICC control problem is a problem that optimize output performance such that constraints on the control input are satis ed In other words, it guarantees the actuators work within their linear range of operation. The external disturbance inputs are assumed to belong to a bounded energy L set By de ning these inputs this way, the ICC control problem is the problem of minimizing the weighted sum of worst-case peak values on the performance outputs subject to the constraints on the worst-case peak values of the control input. The objective of this paper is to extend the ICC control problem presented in [12] for Linear Time-Invariant (LTI) to handle LPV systems.
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