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Then, the BRG analysis is used to quantify the potential for adverse interactions between a given set of controllers or subsystems.
The optimal active detector for a given set of controllers is intractable and therefore, the rolling horizon technique will be used to reduce computational costs.
First, it is verified whether for a given set of controllers, a switching policy satisfying a given set of constraints on the transitions among controllers exists.
As general solution of the problem is extremely difficult, a special case of active detector design for a given set of controllers for jump Markov non-linear Gaussian models is considered.
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The switched control law chooses a state-feedback controller gain, which belongs to a given set of gains, that minimizes the time derivative of a quadratic Lyapunov function.
The synthesis problem consists of obtaining a controller that ensures stability and meets a given set of performance specifications, in spite of the disturbance and model uncertainties.
The controller's trade-oHs are analysed using the obtained Pareto-optimal solutions (corresponding to a given set of target vectors).
Firstly, based on an algebraic state space representation of BCNs, two necessary and sufficient conditions are presented to check whether or not a given set is a robust control invariant set under a given state feedback controller.
EMPeror includes a rich set of controllers to modify features as a function of the metadata.
In this case it gives a set of uncertainty-dependent controllers and only a partial subset of the state feedback controllers is uncertainty-independent.
Given a set of design objectives, a suitable controller can be designed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com