This paper reviews what the first Author and his Group have been investigating for the past decade in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSI...
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The paper presents the requirements of measurement system for electric arc furnace parameters measurement and for working characteristic calculating. On this basis measurement signals were specified and measurement al...
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The paper presents the requirements of measurement system for electric arc furnace parameters measurement and for working characteristic calculating. On this basis measurement signals were specified and measurement algorithms were developed. For data acquisition a special system was constructed. The system consists of portable computer with acquisition card and conditioning system with differential amplifiers, antialiasing filters and sample and hold circuits. The system is connected with interface build-up permanent in arc furnace. The system software makes possible on-line observation of measured signals values and save data to hard disk. Further calculations may be performed off-line using special developed algorithms. For system software development the open source Python language and GCC compiler for Windows were used.
In the procedure of the steady-state hierarchical optimization for a large-scale industrial process,it is necessary to feed the real information to the coordinator in the supreme layer so as to improve the model-based...
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In the procedure of the steady-state hierarchical optimization for a large-scale industrial process,it is necessary to feed the real information to the coordinator in the supreme layer so as to improve the model-based *** this case,a sequence of control decisions, namely,the step set-point changes,with distinct magnitudes are carried *** the purpose of refining the dynamic performance of the transient response driven by the set-point changes,an optimal iterative learning control scheme is proposed in this *** the technique,an appropriate transition is moderately *** means of the functional derivation,an optimal solution with regard to each set-point change is deduced and its numerical form is explicitly *** result illustrates that both the optimal iterative learning control rule and the conventional scheme can remarkably improve the dynamic performance.
In this paper, a new hybrid impulsive and switching control strategy for chaos synchronization is developed. Using switched Lyapunov functions, several new criteria for exponential stability and asymptotical stability...
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In this paper, a new hybrid impulsive and switching control strategy for chaos synchronization is developed. Using switched Lyapunov functions, several new criteria for exponential stability and asymptotical stability of hybrid impulsive and switching nonlinear systems are established and, particularly, some simple sufficient conditions for driving the synchronization error to zero are proposed. A typical example, the Chua's chaotic circuit, is given for illustrating and visualizing the theoretical results.
This paper reviews what the first Author and his Group have been investigating for the past decade in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSI...
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This paper reviews what the first Author and his Group have been investigating for the past decade in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSIP), as well as large-scale systems (LSS). The techniques include the use of neural networks for identification and optimization, the use of expert systems to solve some kinds of hierarchical multi-objective optimization problems, the use of the fuzzy logic control and the use of the iterative learning control. In addition, several implementation examples and the product quality control for LSS are introduced. Finally the paper prospects the new stages of development.
The interaction balance method (IBM) with fuzzy constraints is proposed for large-scale industrial processes under hierarchical steady-state optimization with the consideration of the model-reality difference and the ...
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The interaction balance method (IBM) with fuzzy constraints is proposed for large-scale industrial processes under hierarchical steady-state optimization with the consideration of the model-reality difference and the constraints of subprocesses being flexible. In this approach, the models that are treated as equality constraints and the inequality constraints of the subprocesses are all fuzzified. Two cases of interaction balance method are studied: the open-loop IBM and the IBM with global feedback. Simulation results show that the solutions of the proposed method with global feedback are very close to the optimal solutions of the real process.
New developments in computer networks and communications provide new possibilities for control purposes. control systems for highly complex plants are themselves very complex and heterogeneous. A new software infrastr...
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Electroencephalograph (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communicatio...
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A nonlinear optimization-based identification procedure for fully parameterized multivariable state-space models is presented. The method can be used to identify linear time-invariant, linear parameter-varying, compos...
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This paper is concerned with an application study of model-based fault detection method to a ship propulsion system. When modeling the object system, Quasi-ARMAX model with multi-model form is used. In this model, the...
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