Full form dynamic linearization controller based data-driven model free adaptive control algorithm has been studied in control *** method merely requires the I/O data of the plant to design the controller and is easy ...
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ISBN:
(纸本)9781467397155
Full form dynamic linearization controller based data-driven model free adaptive control algorithm has been studied in control *** method merely requires the I/O data of the plant to design the controller and is easy for ***,there still lacks necessary research on the conditions which can guarantee the stability of the closed loop *** paper presents a stability analysis result for a class of nonlinear *** some mild assumptions,the convergence of the output regulating error was derived by rigorous mathematical method,which guarantees the correctness of the proposed method in theory.
The Group Search Optimizer(GSO) is a novel optimization algorithm, which is inspired by searching behavior of animals. In this paper, we proposed an improved GSO algorithm named Fast Global Group Search Optimizer(FGGS...
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The Group Search Optimizer(GSO) is a novel optimization algorithm, which is inspired by searching behavior of animals. In this paper, we proposed an improved GSO algorithm named Fast Global Group Search Optimizer(FGGSO) to increase searching speed and balance the exploitation and exploration of the algorithm, which is based on our previous works. At first time, considering the complexity and time-consuming design of the producer's angle searching strategy, a novel local search mechanism, named campaign strategy, is developed, which is inspired by competition and cooperation between candidates in an electoral process. After that, a reconstruction operation is applied in searching process to guarantee the avoidance of the local minimum. The algorithm is evaluated on a set of 11 numerical optimization problems and compared favorably with other version of GSOs. Experimental results indicate the remarkable improvement on the performance of these problems.
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of th...
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of the process that can be accurately described by simple equations as, for example, mass balances. This work analyses the use of different types of ‘black-box’ and hybrid models to outline the dynamics of a batch beer production. The hybrid models, combine mechanistic equations with ‘black-box’ techniques (reserved only for the unclear parts of the system), in order to achieve an efficient use of the available information. The hybrid models can also be called ‘grey-box’ approaches. To generate the hybrid models, different level of information is introduced into the ‘black-box’ models, allowing for an interesting model performance comparison in the end. Results demonstrate that the ‘black-box’ models present a good performance in the range of process conditions used to develop them. However, the inclusion of mechanistic knowledge into the hybrid models increase the model extrapolative capability. In this work, artificial neural networks (ANN) are used as the main technique for both the ‘black-box’ models and the ‘black-box’ parts in the hybrid models.
Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data contain...
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Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data containing nine channels of EEG data and one of electrooculagram (EOG) data. Secondly, each 20s independent component (IC) was partitioned into ten 2 s epochs. And five features of each epoch were calculated, which are wavelet entropy, power in the band between 0 and 5 Hz, kurtosis, mutual information and correlation. Thirdly, the epochs were classified as either EEG or ocular artifact based on the result of FCM clustering. And then components which were recognized as ocular artifact were rejected. Clean EEG was obtained. The result shows that the method based on ICA and FCM can be applied to online automatic ocular artifact suppression from EEG.
This paper studies semi-global containment control problem for a multi-agent system. Each follower agent in the system is described by a general linear system in the presence of both actuator position and rate saturat...
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This paper studies semi-global containment control problem for a multi-agent system. Each follower agent in the system is described by a general linear system in the presence of both actuator position and rate saturation. A linear state feedback containment control law is constructed for each follower agent by using low gain approach such that the states of all follower agents will converge to the convex hull formed by the leader agents asymptotically when the communication topology among follower agents is a connected undirect graph and each leader agent is a neighbor of at least one follower agent. Simulation results illustrate the theoretical results.
The traditional robust adaptive control broadens the application of the routine adaptive control because of considering the uncertainty of the practice plant. However, traditional robust adaptive control solves the pr...
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control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control sy...
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This paper investigates the problem of stabilizing predictive control for constrained systems with quantization and communication delays. Based on the quantization matrix, the input-saturated control systems with loga...
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Dynamic model is the basis of dynamic optimization in chemicalprocess. In this paper a dynamic model for esterification section of poly(ethylene-terephthalate) (PET) was developed using segment method. Different from...
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This paper investigates the problem of sliding mode control for a class of stochastic Markovian jumping systems with partially known transition rate.A key feature in this work is to relax the requirement that all the ...
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ISBN:
(纸本)9781479900305
This paper investigates the problem of sliding mode control for a class of stochastic Markovian jumping systems with partially known transition rate.A key feature in this work is to relax the requirement that all the elements in transition rate matrix are known,which is usually encountered in some existing *** is shown that the reachability of the specified sliding surface can be ensured by the designed sliding mode ***,the suffcient conditions for the stability of the sliding motion on the sliding surface are also derived.
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