This study is concerned with the robust H∞ control for a class of uncertain discrete Networked control Systems (NCSs). The NCSs with bounded network-induced delay and data packet dropout are modeled as closed-loop sy...
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Traditional frequency-tracking technique of ultrasonic power often adopts analog phase-locked loop circuit. But it has some defects, such as the narrow locked-inrange and the tendency to lose phase-locked with a sudde...
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A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. Th...
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A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas *** reaction stage. Part of the water produced in thepyrolysis and combust!on stag.e is assumed to be involved inthe second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.
This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinea...
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This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinear industrial process, the multiple-model LPV model in which the global model is constructed by smoothly weighted combination of multiple local models is considered here. The problem of missing output variables data is commonly encountered in practice. In order to handle the multiple-model identification problems of LPV systems with incomplete data, the local model is taken to have a finite impulse response (FIR) model structure and the generalized expectation-maximization (EM) algorithm is adopted to estimate the unknown parameters of the global LPV model. To avoid the problems of ill-conditioned matrices and high sensitivity of parameters to noise, the prior information on the coefficients of each local FIR model is employed to construct the prior probability of unknown parameters. Then the maximum a posteriori (MAP) estimates of the global model parameters are derived via the generalized EM algorithm. The numerical example is presented to demonstrate the effectiveness of the proposed method.
Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been w...
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Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.
For constrained piecewise linear （PWL） systems, the possible existing model uncertainty will bring the difficulties to the design approaches of model predictive control （MPC） based on mixed integer programming （...
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For constrained piecewise linear （PWL） systems, the possible existing model uncertainty will bring the difficulties to the design approaches of model predictive control （MPC） based on mixed integer programming （MIP）. This paper combines the robust method and hybrid method to design the MPC for PWL systems with structured uncertainty. For the proposed approach, as the system model is known at current time, a free control move is optimized to be the current control input. Meanwhile, the MPC controller uses a sequence of feedback control laws as the future control actions, where each feedback control law in the sequence corresponds to each partitions and the arbitrary switching technique is adopted to tackle all the possible switching. Furthermore, to reduce the online computational burden of MPC, the segmented design procedure is suggested by utilizing the characteristics of the proposed approach. Then, an offline design algorithm is proposed, and the reserved degree of freedom can be online used to optimize the control input with lower computational burden.
In this study, automatic method of sleep stage classification for daytime nap is investigated. The ultimate objective is to identify the changing of sleep level during one's nap. The sleep data is recorded accordi...
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ISBN:
(纸本)9781467355339
In this study, automatic method of sleep stage classification for daytime nap is investigated. The ultimate objective is to identify the changing of sleep level during one's nap. The sleep data is recorded according to the polysomnographic (PSG) measurement. The Electroencephalograph (EEG) is analyzed for sleep stage classification. Totally, 4 parameters are selected and calculated for each 20-second segment of EEG data. The main method is based on Hopfield Neural Network (HNN). The neural network is trained by using standard mode. The sleep stages are classified based on HNN for each consecutive segment. The obtained result showed about 80.6% consistence comparing with the visual inspection. The automatic classification results indicated the changing of sleep level during nap, which can be useful for daytime nap sleep evaluation.
This paper proposes a new incremental learning method based on weighted constraints support vector regression, called ***,a modified nearest neighbor clustering method is used to partition the whole input space into s...
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ISBN:
(纸本)9781479900305
This paper proposes a new incremental learning method based on weighted constraints support vector regression, called ***,a modified nearest neighbor clustering method is used to partition the whole input space into several ***,according to the distance distinguish condition,all the samples in sub-cluster are identified to form the candidate support vector *** each new sample added,it was clustered to an individual candidate support vector subset where the cluster center is the closest to the new ***,in the WCSVR learning process,the object function is modified by introducing a weight for each new sample and the corresponding regularization *** experiment shows prominence of our proposed incremental method in comparison with the standard SVR.
The model of NCS (Networked control Systems) with reduced dimension observer is presented when the network-induced random time-varying delays are bounded and the upper bound of which is longer than one sampling period...
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