The control of dynamical systems with inherent non-linear characteristics has motivated research in non-linear control theory. Two main approaches to dealing with uncertainties in control systems design are adaptive a...
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The control of dynamical systems with inherent non-linear characteristics has motivated research in non-linear control theory. Two main approaches to dealing with uncertainties in control systems design are adaptive and robust control. In this paper, discrete direct adaptive control of unknown non-linear SISO systems is considered. The controller is implemented using a fuzzy neural network. The control concept is tested on a laboratory pilot plant and compared to a standard discrete PID Takahashi controller
The paper examines the conditions for isolating the unknown input detection from the effects of the measurements noise in the important family of positional control problems. The study is motivated by the need of impr...
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This work is devoted to computation of large n-D polynomial determinants with a special structure. Applications involve n-D systems theory (e.g. coprimeness test for two n-D polynomials or the theory of algebraic equa...
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A detailed DSPN (Deterministic and Stochastic Petri Net) model and performance analysis of FF MAC sub-layer is constructed in this paper. Firstly, the centralized medium access protocol of FF MAC mechanism is introduc...
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A detailed DSPN (Deterministic and Stochastic Petri Net) model and performance analysis of FF MAC sub-layer is constructed in this paper. Firstly, the centralized medium access protocol of FF MAC mechanism is introduced. Secondly, the accurate DSPN models of FF MAC based on the same size periodic window and the different size periodic window are constructed according to the characteristic of periodic window in each microcycle respectively. Thirdly, performance analysis is presented in following performance aspects: the maximum throughout and the maximum network utilization. Finally, the simulation research based on the DSPN model is developed, which shows the relation throughout, mean aperiodic message delay and utilization with traffic load of aperiodic messages.
The new reconfigurable manufacturing paradigm requires development of systematic methods, and software tools, for the rapid design and builds up of production systems that change the capacity and functionality in resp...
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The new reconfigurable manufacturing paradigm requires development of systematic methods, and software tools, for the rapid design and builds up of production systems that change the capacity and functionality in response to the market demand. The effectiveness of reconfiguration depends upon the development of such tools. In this work, the new concept consisting of ontology knowledge based systems in connection with software agents are applied for the solution of the reconfiguration problem. Reconfigurability is achieved by the employment of the most modern technologies such as ontology driven solution
Computer algebra software tools in general, and the MATHEMATICA system in particular, are increasingly employed during the controls and systems graduate and undergraduate courses at FEE CTU in Prague. MATHEMATICA bene...
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In this paper, fuzzy supervisory PI controllers are developed and implemented on a pilot plant binary distillation column. Fuzzy c-means clustering technique is used in selecting membership functions and fuzzy rules a...
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In this paper, fuzzy supervisory PI controllers are developed and implemented on a pilot plant binary distillation column. Fuzzy c-means clustering technique is used in selecting membership functions and fuzzy rules are determined using fuzzy gain scheduling technique. Thus, the need of heuristic method for designing fuzzy membership functions and rules from expert knowledge is omitted. Then, the fuzzy supervisors adapt the parameters of the PI controllers on line. The task of the controllers is to perform dual composition control of the top and bottom products when the disturbances enter the column in the form of changes in feed flow rate. The results show that the fuzzy supervisory PI controllers achieve much better performance than the fixed PI controllers.
A new identification method for a linear discrete-time closed-loop system is proposed based on an output over-sampling scheme. When the system outputs are over-sampled the new output sequences would contain more infor...
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A new identification method for a linear discrete-time closed-loop system is proposed based on an output over-sampling scheme. When the system outputs are over-sampled the new output sequences would contain more information about the plant structure. Using general least squares method (GLS) the plant over-sampled model should be recognized. Then the original plant model should be obtained by its relationship with the over-sampled model. Compared with conventional approaches the advantage of the new method is that even if the ordinary identifiability conditions are not satisfied, a close-loop system can be identified by using the oversampled output without utilizing any external test signal. Accuracy analysis shows the relationship between the estimation error and the over-sampling rate. Numerical simulation illnstrates its effectiveness.
In this paper, an optimum fuzzy supervisory PI controller using hierarchical genetic algorithms is developed and implemented for controlling the top and bottom product quality of a nonlinear, multi-input multi-output ...
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In this paper, an optimum fuzzy supervisory PI controller using hierarchical genetic algorithms is developed and implemented for controlling the top and bottom product quality of a nonlinear, multi-input multi-output binary distillation column when the disturbance enters the column in the form of the changes in feed flow rate. Two conventional PI controllers, one for the bottom product composition and another for the top product composition, are used together in the control scheme. Hierarchical genetic algorithms are used to derive the optimal number and shape of membership functions and fuzzy rules of a fuzzy supervisory system that adapts the parameters of the PI controllers. The real-time implementation results show the effectiveness of the proposed method.
This work is devoted to computation of large n-D polynomial determinants with a special structure. Applications involve n-D systems theory (e.g. coprimeness test for two n-D polynomials or the theory of algebraic equa...
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This work is devoted to computation of large n-D polynomial determinants with a special structure. Applications involve n-D systems theory (e.g. coprimeness test for two n-D polynomials or the theory of algebraic equations. More specifically, these determinants were exploited in (Chiasson et al. , 2003 b ; Chiasson et al. , 2003 a ) to solve the practical problem of multilevel converter by a special computational procedure. To tackle the concerned problem it is essential to solve a system of polynomial equations with many unknowns. An algorithm was chosen based on elimination theory using resultants leading to the fundamental problem of computing determinants of large Sylvester type matrices with n-D polynomial entries. The aim of this work is to propose and test new numerical algorithms that would make it possible to solve the concerned problems more effectively.
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