This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
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ISBN:
(纸本)9780955529337
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
In this paper, a mmlmum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for non...
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ISBN:
(纸本)9780955529337
In this paper, a mmlmum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for nonlinear NeSs via information theoretic learning approach based on stochastic gradient algorithm. A numerical example is given to illustrate the effectiveness of the proposed scheme.
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
In this paper, a minimum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for no...
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In this paper, a minimum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for nonlinear NCSs via information theoretic learning approach based on stochastic gradient algorithm. A numerical example is given to illustrate the effectiveness of the proposed scheme.
Aim at the hysteretic nonlinearity characteristic of the giant magnetostrictive actuator in control, an internal model control method based on support vector regression is presented in this paper. Its models are built...
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Aim at the hysteretic nonlinearity characteristic of the giant magnetostrictive actuator in control, an internal model control method based on support vector regression is presented in this paper. Its models are built by support vector regression using the input and output data of the actuator and the internal model control is achieved. The simulation results show the method in this paper has better control precision.
A sliding mode control scheme is presented in αβ frame for grid-side PWM rectifiers in wind power generation systems. The positive and negative sequence voltages are needed to design the controller, nevertheless, th...
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In this paper, a novel fault detection scheme is presented for networked controlsystems with random delays and noises. Since the random noises and delays existed in networked controlsystem are probably non- Gaussian...
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A sliding mode control scheme is presented in αβframe for grid-side PWM rectifiers in wind power generation systems. The positive and negative sequence voltages are needed to design the controller, nevertheless, the...
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ISBN:
(纸本)9781424427994
A sliding mode control scheme is presented in αβframe for grid-side PWM rectifiers in wind power generation systems. The positive and negative sequence voltages are needed to design the controller, nevertheless, the positive and negative sequence currents are not needed. This scheme is compared with the dual current control scheme in the rotating frame d-q. The simulation results show that sliding mode control scheme can realize unit power factor operation when the amplitude is unbalanced.
A novel control method is proposed for networked controlsystems with nonlinear process,probably non-Gaussian process noise and time *** performance index of closed loop controlsystem consists of entropy,mean value a...
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A novel control method is proposed for networked controlsystems with nonlinear process,probably non-Gaussian process noise and time *** performance index of closed loop controlsystem consists of entropy,mean value and control energy *** stochastic control methods for networked controlsystems are given under the same general *** method utilizes gradient optimal techniques to obtain an optimal control law,and the stability of closed loop systems is *** other method gives the optimal solution of control law *** implementation issues are *** sliding window techniques and non-parametric probability density function estimation techniques are employed to obtain the entropy of tracking error *** a result,the controller can be on-line ***,the methodology is illustrated by simulations.
In most batch processes, quality controlmeasurements cannot be completed before the next batch operation. Thus, the corrective step is often delayed by one batch or more. The uncertain duration of delay with stochast...
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ISBN:
(纸本)9781424454402
In most batch processes, quality controlmeasurements cannot be completed before the next batch operation. Thus, the corrective step is often delayed by one batch or more. The uncertain duration of delay with stochastic characteristics can be treated as a random variable of unknown distribution. Coupled with inaccurate process models, the delay may lead to significant process output variations even with EWMA controllers. This paper proposes a new method of handling the uncertain metrology delay and its ensuing complications. The run-to-run controller is designed based on minimization of error entropy, and the probability density function of the tracking error can be estimated by the historical operation data. The simulation example demonstrates the effectiveness of the proposed method.
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