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Wyszukujesz frazę "nonlinear system control" wg kryterium: Temat


Wyświetlanie 1-6 z 6
Tytuł:
A numerically efficient fuzzy MPC algorithm with fast generation of the control signal
Autorzy:
Marusak, Piotr M.
Powiązania:
https://bibliotekanauki.pl/articles/1838187.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
model predictive control
fuzzy system
fuzzy control
nonlinear control
sterowanie predykcyjne
system rozmyty
sterowanie rozmyte
sterowanie nieliniowe
Opis:
Model predictive control (MPC) algorithms are widely used in practical applications. They are usually formulated as optimization problems. If a model used for prediction is linear (or linearized on-line), then the optimization problem is a standard, i.e., quadratic, one. Otherwise, it is a nonlinear, in general, nonconvex optimization problem. In the latter case, numerical problems may occur during solving this problem, and the time needed to calculate control signals cannot be determined. Therefore, approaches based on linear or linearized models are preferred in practical applications. A novel, fuzzy, numerically efficient MPC algorithm is proposed in the paper. It can offer better performance than the algorithms based on linear models, and very close to that of the algorithms based on nonlinear optimization. Its main advantage is the short time needed to calculate the control value at each sampling instant compared with optimization-based numerical algorithms; it is a combination of analytical and numerical versions of MPC algorithms. The efficiency of the proposed approach is demonstrated using control systems of two nonlinear control plants: the first one is a chemical CSTR reactor with a van de Vusse reaction, and the second one is a pH reactor.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 1; 59-71
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effective dual-mode fuzzy DMC algorithms with on-line quadratic optimization and guaranteed stability
Autorzy:
Marusak, P. M.
Tatjewski, P.
Powiązania:
https://bibliotekanauki.pl/articles/907866.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
system rozmyty
sterowanie predykcyjne
stabilność
sterowność wymuszona
nonlinear system
fuzzy system
model predictive control
stability
constrained control
dual-mode control
Opis:
Dual-mode fuzzy dynamic matrix control (fuzzy DMC-FDMC) algorithms with guaranteed nominal stability for constrained nonlinear plants are presented. The algorithms join the advantages of fuzzy Takagi-Sugeno modeling and the predictive dual-mode approach in a computationally efficient version. Thus, they can bring an improvement in control quality compared with predictive controllers based on linear models and, at the same time, control performance similar to that obtained using more demanding algorithms with nonlinear optimization. Numerical effectiveness is obtained by using a successive linearization approach resulting in a quadratic programming problem solved on-line at each sampling instant. It is a computationally robust and fast optimization problem, which is important for on-line applications. Stability is achieved by appropriate introduction of dual-mode type stabilization mechanisms, which are simple and easy to implement. The effectiveness of the proposed approach is tested on a control system of a nonlinear plant-a distillation column with basic feedback controllers.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2009, 19, 1; 127-141
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Actuator fault tolerance in control systems with predictive constrained set-point optimizers
Autorzy:
Marusak, P. M.
Tatjewski, P.
Powiązania:
https://bibliotekanauki.pl/articles/929879.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie odporne na błędy
sterowanie predykcyjne
optymalizacja
system nieliniowy
fault tolerant control
model predictive control
set-point optimization
nonlinear system
Opis:
Mechanisms of fault tolerance to actuator faults in a control structure with a predictive constrained set-point optimizer are proposed. The structure considered consists of a basic feedback control layer and a local supervisory set-point optimizer which executes as frequently as the feedback controllers do with the aim to recalculate the set-points both for constraint feasibility and economic performance. The main goal of the presented reconfiguration mechanisms activated in response to an actuator blockade is to continue the operation of the control system with the fault, until it is fixed. This may be even long-term, if additional manipulated variables are available. The mechanisms are relatively simple and consist in the reconfiguration of the model structure and the introduction of appropriate constraints into the optimization problem of the optimizer, thus not affecting the numerical effectiveness. Simulation results of the presented control system for a multivariable plant are provided, illustrating the efficiency of the proposed approach.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 539-551
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Soft computing in model-based predictive control
Autorzy:
Tatjewski, P.
Ławryńczuk, M.
Powiązania:
https://bibliotekanauki.pl/articles/908473.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie procesami
sterowanie predykcyjne
system nieliniowy
system rozmyty
sieć neuronowa
process control
model predictive control
nonlinear systems
fuzzy systems
neural networks
Opis:
The application of fuzzy reasoning techniques and neural network structures to model-based predictive control (MPC) is studied. First, basic structures of MPC algorithms are reviewed. Then, applications of fuzzy systems of the Takagi-Sugeno type in explicit and numerical nonlinear MPC algorithms are presented. Next, many techniques using neural network modeling to improve structural or computational properties of MPC algorithms are presented and discussed, from a neural network model of a process in standard MPC structures to modeling parts or entire MPC controllers with neural networks. Finally, a simulation example and conclusions are given.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2006, 16, 1; 7-26
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Input constraints handling in an MPC/feedback linearization scheme
Autorzy:
Deng, J.
Becerra, V. M.
Stobart, R.
Powiązania:
https://bibliotekanauki.pl/articles/907653.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie predykcyjne
sterowanie odwrotne
sieć neuronowa
system nieliniowy
predictive control
feedback linearization
neural network
nonlinear system
constraints
Opis:
The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real timeMPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2009, 19, 2; 219-232
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optymalizujące sterowanie układem napędowym samochodu z silnikiem spalinowym
The optimized control of a propulsion system of an internal combustion engine car
Autorzy:
Strojny, R.
Piotrowski, R.
Powiązania:
https://bibliotekanauki.pl/articles/155219.pdf
Data publikacji:
2013
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
modelowanie matematyczne
systemy dynamiczne
systemy nieliniowe
sterowanie predykcyjne
układ napędowy samochodu
mathematical modeling
dynamic systems
nonlinear systems
predictive control
car propulsion system
Opis:
Sterowanie układami napędowymi nowoczesnych samochodów to prężnie rozwijająca się dziedzina inżynierii. Wzrost wymagań względem ekologii, ekonomii i bezpieczeństwa osób wymusza poszukiwanie nowych rozwiązań, zarówno technologicznych jak i związanych z automatyzacją procesów. W artykule przedstawiono dynamiczny model układu napędowego samochodu z silnikiem spalinowym o zapłonie iskrowym. Zbudowano układ regulacji prędkości obrotowej oparty na nieliniowym sterowaniu predykcyjnym. W badaniach symulacyjnych przedstawiono wyniki sterowania modelem pojazdu marki Golf III.
Control of propulsion systems of modern cars is a rapidly growing field of engineering. New policies in the terms of ecology, economy and safety of persons forced to search for new solutions, both technological and automation of processes. Both car companies and research centers around the world deal with the designing of appropriate models that can be used to simulate the behavior of vehicles. This paper presents a dynamic model of the propulsion system of a car with an internal combustion engine with spark ignition. It was built for a speed control system based on nonlinear predictive control. The controller is applied to the model of Golf III. The paper is divided into 5 sections. Section 1 contains a short introduction to the issues of this paper. The structure and synthesis of the dynamical nonlinear model of the propulsion system of a Golf III car are dealt with in Section 2. A nonlinear model predictive controller is derived in Section 3. Simulation tests and discussion of the results are presented in Section 4. Section 5 concludes the paper.
Źródło:
Pomiary Automatyka Kontrola; 2013, R. 59, nr 12, 12; 1289-1293
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-6 z 6

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