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For parameter varying systems with the bounded parameter variations, the parameter variation upper bound is included in stability conditions and control design procedure.
The bounded parameter variation rate is assumed.
Finally, a constantly bounded parameter model is established, which can be used for robust control.
A factorial design search for similar loosely bounded parameter spaces is proposed.
To cater for possible implementation errors, the estimator gain is allowed to have certain bounded parameter variations.
Based on this result, a robust filter design to deal with convex bounded parameter uncertainty is considered.
Similar(35)
From a theoretical point of view, robust positive invariance theory is presented in order to perform the analysis of the effects that a bounded parameter-varying additive disturbance has on a linear parameter-varying controller used to ensure stability of a model predictive control strategy.
The Takagi and Sugeno fuzzy model is employed to represent such nonlinear nonhomogeneous Markov jump system with norm-bounded parameter uncertainties.
This research note extends existing methods for Bounded-parameter Markov Decision Processes (BMDPs) to solve the reachability problem.
In this paper, we introduce the notion of a bounded-parameter Markov decision process (BMDP) as a generalization of the familiar exact MDP.
Bounded-parameter MDPs can be used to represent variation or uncertainty concerning the parameters of sequential decision problems in cases where no prior probabilities on the parameter values are available.
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