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Wyświetlanie 1-15 z 48
Tytuł:
Tracking Control Algorithms for a Laboratory Aerodynamical System
Autorzy:
Gorczyca, P.
Hajduk, K.
Powiązania:
https://bibliotekanauki.pl/articles/907962.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
sterowanie w czasie rzeczywistym
sterowanie nadążne
kontroler suboptymalny
nonlinear systems
real-time control
tracking control
suboptimal controller
Opis:
The tracking control problem of a strongly nonlinear MIMO system is presented. The system shares some features with a helicopter, such as important interactions between the vertical and horizontal motions. The dedicated I/O board allows for control, measurements and communication with a PC. The RTWT toolbox in the MATLAB environment is used to perform real-time experiments. The control task is to track a predefined reference trajectory. A mathematical model of the system, containing experimental characteristics, is used to design the controllers: a multidimensional PD, a suboptimal controller in the sense of a quadratic performance index and a variable gain controller.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 4; 469-475
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Supervisory predictive control and on-line set-point optimization
Autorzy:
Tatjewski, P.
Powiązania:
https://bibliotekanauki.pl/articles/929583.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie predykcyjne
sterowanie nieliniowe
linearyzacja
model niepewności
sterowność wymuszona
optymalizacja
predictive control
nonlinear control
linearisation
model uncertainty
constrained control
set-point optimization
Opis:
The subject of this paper is to discuss selected effective known and novel structures for advanced process control and optimization. The role and techniques of model-based predictive control (MPC) in a supervisory (advanced) control layer are first shortly discussed. The emphasis is put on algorithm efficiency for nonlinear processes and on treating uncertainty in process models, with two solutions presented: the structure of nonlinear prediction and successive linearizations for nonlinear control, and a novel algorithm based on fast model selection to cope with process uncertainty. Issues of cooperation between MPC algorithms and on-line steady-state set-point optimization are next discussed, including integrated approaches. Finally, a recently developed two-purpose supervisory predictive set-point optimizer is discussed, designed to perform simultaneously two goals: economic optimization and constraints handling for the underlying unconstrained direct controllers.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 3; 483-495
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Suboptimal Nonlinear Predictive Controllers
Autorzy:
Declercq, F.
De Keyser, R.
Powiązania:
https://bibliotekanauki.pl/articles/908312.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie predykcyjne
sterowanie nieliniowe
programowanie sekwencyjne
równanie diofantyczne
predictive control
nonlinear control
sequential quadratic programming
diophantine equations
Opis:
Predictive control based on linear models has become a mature technology in the last decade. Many successful real-time applications can be found in almost every sector of industry. Nonlinear predictive control can further increase the performance of this easy-to-understand control strategy. One of the main problems of implementing nonlinear predictive control is the computational aspect, which is of most importance in real-life applications. In this paper, suboptimal nonlinear predictive control strategies are proposed and compared. The nonlinear predictors are built based on neural identification methods or by white modelling. The use of diophantine equations, which is a common technique to calculate the optimal contribution of the noise model, is avoided by using a more natural method. The comparison between the control algorithms is made based on a simulated discrete multivariable nonlinear system and a continuous stirred tank reactor.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 1; 129-148
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Suboptimal fault tolerant control design with the use of discrete optimization
Autorzy:
Kowalczuk, Z.
Oliński, K. E.
Powiązania:
https://bibliotekanauki.pl/articles/929873.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie optymalne
system odporny na uszkodzenia
model nieliniowy
badania operacyjne
optymalizacja dyskretna
optimal control
fault tolerant systems
nonlinear model
operations research
discrete optimization
Opis:
This paper presents a concept of designing fault tolerant control systems with the use of suboptimal methods. We assume that a given (nonlinear) dynamical process is described in a state space. The method consists in searching (at the off-line stage) for a trajectory of operational points of the system state space. The sought trajectory can be constrained by certain conditions, which can express faults or failures already detected. Within this approach, we are able to use the autonomous dynamics of the process in order to minimize a control cost index (a sub-optimality property). The search itself is based on finding a cheapest path in a graph structure, which represents the system’s dynamics described in the state space. Such a cheapest path (if it exists) represents the sought trajectory. Another (on-line) design stage consists in tracking this trajectory by an executive controller.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 561-568
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sub-Optimal Nonlinear Predictive and Adaptive Control Based on the Parametric Volterra Model
Autorzy:
Haber, R.
Bars, R.
Lengyel, O.
Powiązania:
https://bibliotekanauki.pl/articles/908307.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie predykcyjne
sterowanie nieliniowe
sterowanie optymalne
układ nieliniowy
adaptacyjny układ sterowania
predictive control
nonlinear control
optimal control
nonlinear systems
adaptive control
Opis:
Predictive control algorithms have been worked out mainly to control linear plants. There is a great demand to apply different control ideas to nonlinear systems. Using predictive control algorithms for nonlinear systems is a promising technique. Extended horizon one-step-ahead and long-range optimal predictive control algorithms are given here for the parametric Volterra model (which includes also the generalized Hammerstein model). A quadratic cost function is minimized which considers the quadratic deviations of the reference signal and the output signal at a future point (or points) beyond the dead time and also penalizes large control signal increments. For prediction of the output signal, a predictive model is applied which uses information about the input and output signals up to the current time. A predictive transformation of the nonlinear dynamic model is given. The incremental model is advantageous since the cost function contains the control increment and not the control signal itself. An incremental transformation of the predictive forms is also described. Sub-optimal solutions to the optimal control algorithms are discussed with different assumptions for the control signal during the control horizon. The effect of the different strategies and the effect of the tuning parameters is investigated through simulation examples.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 1; 161-173
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stabilising solutions to a class of nonlinear optimal state tracking problems using radial basis function networks
Autorzy:
Ahmida, Z.
Charef, A.
Becerra, V. M.
Powiązania:
https://bibliotekanauki.pl/articles/908523.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
sterowanie optymalne
radialna funkcja bazowa
sieć neuronowa
regulacja predykcyjna
sterowanie wyprzedzające
nonlinear systems
optimal control
radial basis functions
neural networks
predictive control
feedforward control
Opis:
A controller architecture for nonlinear systems described by Gaussian RBF neural networks is proposed. The controller is a stabilising solution to a class of nonlinear optimal state tracking problems and consists of a combination of a state feedback stabilising regulator and a feedforward neuro-controller. The state feedback stabilising regulator is computed online by transforming the tracking problem into a more manageable regulation one, which is solved within the framework of a nonlinear predictive control strategy with guaranteed stability. The feedforward neuro-controller has been designed using the concept of inverse mapping. The proposed control scheme is demonstrated on a simulated single-link robotic manipulator.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 3; 369-381
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:
Robust flat filtering control of a two degrees of freedom helicopter subject to tail rotor disturbances
Autorzy:
Sánchez-Meza, Victor-Gabriel
Lozano-Hernández, Yair
Gutiérrez-Frías, Octavio
Lozada-Castillo, Norma
Luviano-Juárez, Alberto
Powiązania:
https://bibliotekanauki.pl/articles/24200696.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
flat filtering control
generalized proportional integral control
nonlinear system
tail rotor disturbance
two degrees of freedom helicopter
sterowanie całkujące
układ nieliniowy
zakłócenia wirnika
Opis:
This article deals with modelling and a flatness-based robust trajectory tracking scheme for a two degrees of freedom helicopter, which is subject to four types of tail rotor disturbances to validate the control scheme robustness. A mathematical model of the system, its differential flatness and a differential parametrization are obtained. The flat filtering control is designed for the system control with a partially known model, assuming the non-modelled dynamics and the external disturbances (specially the tail rotor ones) to be rejected by means of an extended state model (ultra-local model). Numerical and experimental assessments are carried out on a characterized prototype whose yaw angle (ψ), given by the z axis, is in free form, while the pitch angle (θ), which results from rotation about the y axis, is mechanically restricted. The proposed controller performance is tested through a set of experiments in trajectory tracking tasks with different disturbances in the tail rotor, showing robust behaviour for the different disturbances. Besides, a comparison study against a widely used controller of LQR type is carried out, in which the proposed controller achieves better results, as illustrated by a performance index.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 4; 521--535
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust Control of Nonlinear Time-Delay Systems
Autorzy:
Antoniades, C.
Christofides, P. D.
Powiązania:
https://bibliotekanauki.pl/articles/908267.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
model niepewności
sterowanie solidne nieliniowe
opóźnienie czasowe
model uncertainty
time delays
nonlinear robust control
fluidized catalytic cracker
Opis:
This paper focuses on single-input single-output nonlinear differential difference equation (DDE) systems with uncertain variables. For such systems, a general methodology is developed for the synthesis of robust nonlinear state feedback controllers that guarantee boundedness of the states and ensure that the ultimate discrepancy between the output and the external reference input in the closed-loop system can be made arbitrarily small by an appropriate choice of controller parameters. The controllers are synthesized by using a novel combination of geometric and Lyapunov-based techniques and enforce the above properties in the closed-loop system independently of the size of the state delay. The proposed control method is successfully applied to a fluidized catalytic cracking unit with a time-varying uncertain variable and is shown to outperform a proportional integral (PI) controller, a nonlinear controller that does not account for the uncertainty, and anonlinear controller that does not account for the state delays.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 4; 811-837
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems
Autorzy:
Tong, S.
Liu, C.
Li, Y.
Powiązania:
https://bibliotekanauki.pl/articles/908148.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
sterowanie rozmyte
sprzężenie zwrotne
nonlinear system
adaptive fuzzy control
backstepping
small-gain approach
K-filters
Opis:
In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 4; 637-653
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Protector control: Extension to a class of nonlinear distributed systems
Autorzy:
Qaraai, Y.
Bernoussi, A. S.
Powiązania:
https://bibliotekanauki.pl/articles/907703.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
system rozproszony
zaburzenia
podatność na uszkodzenia
nonlinear distributed systems
disturbance
spreadability
vulnerability
remediability
protector control
Opis:
We present an extension of the protector control scheme introduced for the linear case in a previous work to a class of nonlinear systems. The systems considered are assumed to have a finite propagation velocity while the initial state is subject to a spreading disturbance. We characterize such a control first by using the remediability approach to the resulting nonlinear delay system, and then by coupling families of transformations and the delay approach. To illustrate this work, we provide a simulation example.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 3; 427-443
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Powerful nonlinear observer associated with field-oriented control of an induction motor
Autorzy:
Mansouri, A.
Chenafa, M.
Bouhenna, A.
Etien, E.
Powiązania:
https://bibliotekanauki.pl/articles/907397.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
silnik indukcyjny
obserwator nieliniowy
rezystancja wirnika
induction motor
field-oriented control
nonlinear observer
rotor resistance
Opis:
In this paper, we associate field-oriented control with a powerful nonlinear robust flux observer for an induction motor to show the improvement made by this observer compared with the open-loop and classical estimator used in this type of control. We implement this design strategy through an extension of a special class of nonlinear multivariable systems satisfying some regularity assumptions. We show by an extensive study that this observer is completely satisfactory at low and nominal speeds and it is not sensitive to disturbances and parametric errors. It is robust to changes in load torque, rotational speed and rotor resistance. The method achieves a good performance with only one easier gain tuning obtained from an algebraic Lyapunov equation. Finally, we present results and simulations with concluding remarks on the advantages and perspectives for the observer proposed with the field-oriented control.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 2; 209-220
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear state-space predictive control with on-line linearisation and state estimation
Autorzy:
Ławryńczuk, M.
Powiązania:
https://bibliotekanauki.pl/articles/330330.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
process control
model predictive control
nonlinear state space model
extended Kalman filter
online linearization
proces sterowania
model sterowania predykcyjnego
model przestrzeni stanów
rozszerzony filtr Kalmana
Opis:
This paper describes computationally efficient model predictive control (MPC) algorithms for nonlinear dynamic systems represented by discrete-time state-space models. Two approaches are detailed: in the first one the model is successively linearised on-line and used for prediction, while in the second one a linear approximation of the future process trajectory is directly found on-line. In both the cases, as a result of linearisation, the future control policy is calculated by means of quadratic optimisation. For state estimation, the extended Kalman filter is used. The discussed MPC algorithms, although disturbance state observers are not used, are able to compensate for deterministic constant-type external and internal disturbances. In order to illustrate implementation steps and compare the efficiency of the algorithms, a polymerisation reactor benchmark system is considered. In particular, the described MPC algorithms with on-line linearisation are compared with a truly nonlinear MPC approach with nonlinear optimisation repeated at each sampling instant.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 833-847
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear model predictive control for processes with complex dynamics: A parameterisation approach using Laguerre functions
Autorzy:
Ławryńczuk, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/329999.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
process control
nonlinear model predictive control
Laguerre functions
linearisation
sterowanie procesami
model nieliniowy
sterowanie predykcyjne
funkcje Laguerre’a
Opis:
Classical model predictive control (MPC) algorithms need very long horizons when the controlled process has complex dynamics. In particular, the control horizon, which determines the number of decision variables optimised on-line at each sampling instant, is crucial since it significantly affects computational complexity. This work discusses a nonlinear MPC algorithm with on-line trajectory linearisation, which makes it possible to formulate a quadratic optimisation problem, as well as parameterisation using Laguerre functions, which reduces the number of decision variables. Simulation results of classical (not parameterised) MPC algorithms and some strategies with parameterisation are thoroughly compared. It is shown that for a benchmark system the MPC algorithm with on-line linearisation and parameterisation gives very good quality of control, comparable with that possible in classical MPC with long horizons and nonlinear optimisation.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 1; 35-46
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear controller design of a ship autopilot
Autorzy:
Tomera, M.
Powiązania:
https://bibliotekanauki.pl/articles/907758.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sterowanie ślizgowe
sterowanie nieliniowe
eliminacja zakłóceń
sterowanie statkiem
sliding-mode control
nonlinear control
disturbance rejection
ship control
Opis:
The main goal here is to design a proper and efficient controller for a ship autopilot based on the sliding mode control method. A hydrodynamic numerical model of CyberShip II including wave effects is applied to simulate the ship autopilot system by using time domain analysis. To compare the results similar research was conducted with the PD controller, which was adapted to the autopilot system. The differences in simulation results between two controllers are analyzed by a cost function composed of a heading angle error and rudder deflection either in calm water or in waves. Simulation results show the effectiveness of the method in the presence of nonlinearities and disturbances, and high performance of the proposed controller.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 2; 271-280
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 48

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