The problem of the static output feedback stabilization is the solvability of the two invert-coupled matrix inequalities. This is non-linear optimal problem and cannot be solved directly. In this paper, the relation o...
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The problem of the static output feedback stabilization is the solvability of the two invert-coupled matrix inequalities. This is non-linear optimal problem and cannot be solved directly. In this paper, the relation of the two coupled matrix inequalities is studied and a sufficient condition of the solvability for the stabilization problem is proposed on a structural Lyapunov matrix. The corresponding algorithm is presented, which is non-iterative and simply solved by linear matrix inequality (LMI) tools. Examples are given to show the simplicity and effectiveness of the proposed method.
In cutting tool temperature experiment, a large number of related data could be available. In order to define the relationship among the experiment data, the nonlinear regressive curve of cutting tool temperature must...
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In cutting tool temperature experiment, a large number of related data could be available. In order to define the relationship among the experiment data, the nonlinear regressive curve of cutting tool temperature must be constructed based on the data. This paper proposes the Particle Swarm Optimization (PSO) algorithm for estimating the parameters such a curve. The PSO algorithm is an evolutional method based on a very simple concept. Comparison of PSO results with those of GA and LS methods showed that the PSO algorithm is more effective for estimating the parameters of the above curve.
A first principles-based dynamic model for a continuous catalyst regeneration (CCR) platforming process, the UOP commercial naphtha catalytic reforming process, is developed in this paper. The lumping details of the n...
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A first principles-based dynamic model for a continuous catalyst regeneration (CCR) platforming process, the UOP commercial naphtha catalytic reforming process, is developed in this paper. The lumping details of the naphtha feed and reaction scheme of the reaction model are given. The process model is composed of the reforming reaction model with catalyst deactivation, the furnace model and the separator model, which is capable of capturing the major dynamics that occurs in this process system. Dynamic simulations are performed based on Gear numerical algorithm and method of lines (MOL), a numerical technique dealing with partial differential equations (PDEs). The results of simulation are also presented. Dynamic responses caused by disturbances in the process system can be correctly predicted through simulations.
Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. ...
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Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
The fuzzy neuron hybrid control method is proposed for mold level control of the continuous steel casting in this paper. The dynamic characteristics of the continuous steel casting process is described. To the plant w...
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The neuron control method based on RBF network and fuzzy scheme is proposed for a direct drive robot In this intelligent control system, the RBF network is used to update the weights of neuron controller on-line accor...
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A necessary and sufficient condition of the quadratic D-stability for a class of uncertain linear systems is presented in terms of linear matrix inequslity (LMI) technology. Finally, the validity and less conservatism...
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A necessary and sufficient condition of the quadratic D-stability for a class of uncertain linear systems is presented in terms of linear matrix inequslity (LMI) technology. Finally, the validity and less conservatism of the obtained results in this paper are illustrated by a benchmark example.
In this paper, a novel data mining method is introduced to solve the multi-objective optimization problems of process industry. A hyperrectangle association rule mining （HARM） algorithm based on support vector machi...
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In this paper, a novel data mining method is introduced to solve the multi-objective optimization problems of process industry. A hyperrectangle association rule mining （HARM） algorithm based on support vector machines （SVMs） is proposed. Hyperrectangles rules are constructed on the base of prototypes and support vectors （SVs） under some heuristic limitations. The proposed algorithm is applied to a simulated moving bed （SMB） paraxylene （PX） adsorption process. The relationships between the keyprocess variables and some objective variables such as purity, recovery rate of PX are obtained. Using existing domain knowledge about PX adsorption process, most of the obtained association rules can be explained.
A quite great progress of the supervisory control theory for discrete event systems (DES) has been made in the past nearly twenty years, and now, automata, formal language and Petri nets become the main research tools...
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A quite great progress of the supervisory control theory for discrete event systems (DES) has been made in the past nearly twenty years, and now, automata, formal language and Petri nets become the main research tools. This paper focus on the Petri nets based supervisory control theory of DES. Firstly, we review the research results in this field, and claim that there generally exists a problem in Petri nets based supervisory control theory of DES, that is, the deadlock caused by the controller introduced to enforce the given specification occurs in the closed-loop systems, especially the deadlock occurs in the closed-loop system in which the original plant is live. Finally, a possible research direction is presented for the solution of this problem.
An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction ste...
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An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.
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