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Then, the dissipative non-fragile state estimator is designed successfully via linear matrix inequality method.
A sufficient condition guaranteeing the existence of linear switching surface is given based on the linear matrix inequality method (LMIs).
By using linear matrix inequality method, the numerical solution of mixed H2/H∞ state-feedback controller can be efficiently solved.
The linear matrix inequality method is employed to obtain sufficient conditions for achieving fault tolerance and ensuring the prescribed H∞ performance index.
Using the linear matrix inequality method, sufficient conditions are derived to ensure the consensus for both the cases without and with communication delay in the multi-agent systems.
Attention is focused on the proportional plus derivative state feedback controller design based on the linear matrix inequality method, which guarantees the closed-loop system to be normal and quadratically stable with a prescribed upper bound of the cost function.
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Advances in Linear Matrix Inequality Methods in Control, Laurent El Ghaoui and Silviu-Iulian Niculescu, Editors.
Linear matrix inequality methods are applied to develop a solution which links control objective, performance, and communication limits.
In contrast with LMI or BMI approaches, these new methods avoid the use of Lyapunov variables, which gives them two major strategic advances over matrix inequality methods.
The one-step LMIs (Linear Matrix Inequalities) method is applied to design the controller gains and observer gains.
A linear matrix inequalities method has been developed to solve this problem.
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