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This paper presents the decentralized fault-tolerant tracker based on the model predictive control (MPC) for a class of unknown interconnected large-scale sampled-data nonlinear systems. Due to the computational requirements of MPC and the system information is unknown, the observer/Kalman filter identification (OKID) method is utilized to determine decentralized appropriate (low-) order discrete-time...
The universal state-space adaptive observer-based fault diagnosis/estimator and the high-gain property tracker for sampled-data linear slowly time-varying system with unanticipated decay factors in actuators/system states are proposed in this paper. An improved Kalman filter-based adaptive observer is proposed in this paper to achieve better estimation-based performance recovery than the conventional...
The optimal hybrid tracking control problem for analog neutral systems with multiple discrete and distributed time delays is discussed in this paper. In order to obtain good tracking performance and improve the drawback of conventional optimal control in selecting the weighting matrices, the observer with evolutionary-programming (EP)-based alternative digital redesign control technique is presented...
Based on the modified state-space self-tuning control (STC), a novel low-order tuner via the modified observer/Kalman filter identification (OKID) is proposed for stochastic fractional-order chaotic systems. The OKID method is a time-domain technique that identifies a discrete input-output map by using known input-output sampled data in the general coordinate form, through an extension of the eigensystem...
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