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By utilizing this set invariance condition, the design of a time-invariant state feedback law is formulated and solved as an optimization problem with LMI constraints.
The time-invariant state equation is used to design cold start feedforward and feedback controllers.
The time-invariant state space model is used to design cold start feedforward and feedback controllers.
Second, the concept of role state variables is proposed to transform the periodically time-varying state space model into a time-invariant state space model.
The stabilizability and optimality of the time-invariant state space model imply those of the periodically time-varying state space model.
Second, the concept of role state variables is proposed to transform the periodic state equation into a time-invariant state equation.
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The models or agents with the dynamics of linear continuous-time time-invariant state-space systems are considered.
The linearized model is described as a continuous, time-invariant state-space model where the state is formed by temperature and concentration profiles on the grid points.
In this paper, the equations of structural motion are expressed in time-invariant state-space equations by expressing the frequency dependent self-excited forces in terms of rational functions.
The algorithms were designed for linear time-invariant state-space signal models with white Gaussian noise.
In this paper, we investigate the effect of embedded unbiasedness (EU) on optimal finite impulse response (OFIR) filtering estimates of linear discrete time-invariant state-space models.
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