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The linear matrix inequality (LMI) based output memory-less controller design approach is presented in the paper. The design conditions are expressed in terms of LMIs with the matrix rank constraints implying from Lyapunov equation, which correspond to the feasible solution. Obtained formulation is the convex LMI problem for the output static controller design. The proposed method is demonstrated...
An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefore, instead of the offline backpropagation-through-time (BPTT) algorithm, a standard online (real-time) backpropagation (BP) algorithm, usually called Elman BP (EBP), can be applied for EN training for discrete-time sequence predictions...
The paper addresses the problem of output feedback stable model predictive control design with guaranteed cost. The proposed design method pursues the idea of sequential design for N prediction horizon using one-step ahead model predictive control design approach. Numerical examples are given to illustrate the effectiveness of the proposed method.
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