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This paper extends earlier work on nonlinear predictive control based on a representation of the nonlinear plant as quasi-LPV model. Since the scheduling parameters depend on state variables and inputs, they can be predicted. An efficient predictive scheme with guaranteed stability is proposed that involves solving a sequence of SOCP problems at each sampling period. Compared with previously reported...
Novel sufficient conditions for well-posedness and stability of spatially interconnected systems with finite extent are proposed. Existing conditions for space-invariant interconnected systems do in general not guarantee these properties for finite-extent systems. Rather than using a model based on the spatial shift operator, here the system is represented as a network of (not necessarily identical)...
A common challenge associated with designing a Linear Parameter-Varying (LPV) controller for a nonlinear plant is identification of a plant model in state-space form with static parameter dependency. Till date, the two most frequently used methods to solve this problem are special canonical forms of Input-Output (IO) and subspace (SS) identification. This paper compares both identification methods...
A method to reduce the dynamic order of linear parameter-varying (LPV) systems in grid representation is developed in this paper. It approximates balancing and truncation by an oblique projection onto a dominant subspace. The approach is novel in its use of a parameter-varying kernel to define the direction of this projection. Parameter-varying state transformations in general lead to parameter rate...
Stability and ℒ2-performance of linear parameter-varying (LPV) systems in input-output (IO) form are considered. Based on our previous results, novel linear matrix inequality conditions are presented that allow to compute a stabilizing full-order LPV-IO controller which satisfies ℒ2-performance constraints by means of a convex program. The problem of dynamic parameter dependence that usually hinders...
A new nondynamic multirate output feedback approach to robust tracking and disturbance rejection is presented. Assuming that a linear model of the plant under nominal operating conditions and under failure conditions is known, convex programming can be employed to find a state feedback gain such that the closed loop system meets given specifications in all operating points. If the full state is not...
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