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Wyświetlanie 1-15 z 33
Tytuł:
Efficient MPC algorithms with variable trajectories of parameters weighting predicted control errors
Autorzy:
Nebeluk, Robert
Marusak, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/230077.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
model predictive control
nonlinear systems
nonlinear models
nonlinear control
simulation
optimization
Opis:
Model predictive control (MPC) algorithms brought increase of the control system performance in many applications thanks to relatively easily solving issues that are hard to solve without these algorithms. The paper is focused on investigating how to further improve the control system performance using a trajectory of parameters weighting predicted control errors in the performance function of the optimization problem. Different shapes of trajectories are proposed and their influence on control systems is tested. Additionally, experiments checking the influence of disturbances and of modeling uncertainty on control system performance are conducted. The case studies were done in control systems of three control plants: a linear non-minimumphase plant, a nonlinear polymerization reactor and a nonlinear thin film evaporator. Three types of MPC algorithms were used during research: linear DMC, nonlinear DMC with successive linearization (NDMC–SL), nonlinear DMC with nonlinear prediction and linearization (NDMC–NPL). Results of conducted experiments are presented in greater detail for the control system of the polymerization reactor, whereas for the other two control systems only the most interesting results are presented, for the sake of brevity. The experiments in the control system of the linear plant were done as preliminary experiments with the modified optimization problem. In the case of control system of the thin film evaporator the researched mechanisms were used in the control system of a MIMO plant showing possibilities of improving the control system performance.
Źródło:
Archives of Control Sciences; 2020, 30, 2; 325-363
1230-2384
Pojawia się w:
Archives of Control Sciences
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:
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:
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:
Nieliniowe sterowanie predykcyjne ramion manipulatorów
Nonlinear Predictive Control of Manipulator Arms
Autorzy:
Tatjewski, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/27312429.pdf
Data publikacji:
2023
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
sterowanie manipulatorów
sterowanie nieliniowe
sterowanie predykcyjne
opóźnienie sterowania
szybkie próbkowanie
manipulator control
nonlinear control
model predictive control
control delay
fast sampling
Opis:
Przedmiotem artykułu są algorytmy sterowania predykcyjnego (typu MPC - Model Predictive Control) ramion manipulatorów sztywnych. Zastosowano MPC z modelem w przestrzeni stanów i wykorzystano najnowszą technikę tłumienia zakłóceń i błędów modelowania, pozwalającą uniknąć dynamicznego modelowania zakłóceń lub uciekania się do dodatkowych technik ich eliminowania, takich jak SMC. Rozważane są przede wszystkim najbardziej efektywne obliczeniowo algorytmy MPC-NPL (NPL - Nonlinear Prediction and Linearization), w dwóch wersjach: z optymalizacją QP (Quadratic Programming) z ograniczeniami i z jawną optymalizacją bez ograniczeń i spełnieniem ograniczeń nierównościowych a posteriori. Dla wszystkich rozważanych algorytmów przeprowadzono kompleksową analizę symulacyjną sterowania manipulatorem z napędem bezpośrednim, przy dwóch rodzajach zakłócenia: zewnętrznym i parametrycznym. Wyniki porównano z uzyskanymi dla znanego algorytmu CTC-PID (CTC - Computer Torque Control), uzyskując lepszą jakość regulacji algorytmami MPC. Zbadano wpływ długości okresu próbkowania i obliczeniowego opóźnienia sterowania na jakość regulacji, co jest istotne dla algorytmów z szybkim próbkowaniem opartych na modelach.
The subject of the article are predictive control algorithms (of MPC type - Model Predictive Control) for rigid manipulator arms. MPC with a state-space model and with the latest disturbance and modeling error suppression technique was applied, which avoids dynamic disturbance modeling or resorting to additional disturbance cancellation techniques, such as SMC. First of all, the most computationally efficient MPC-NPL (Nonlinear Prediction and Linearization) algorithms are considered, in two versions: the first with constrained QP (Quadratic Programming) optimization and the second with explicit (analytical) optimization without constraints and satisfying a posteriori inequality constraints. For all considered algorithms, a comprehensive simulation analysis was carried out for a direct drive manipulator, with two kinds of disturbances: external and parametric. The obtained results were compared with those for the well-known CTC-PID algorithm (CTC - Computer Torque Control), showing better control quality with MPC algorithms. In addition, the influence of the length of the sampling period and of the computational delay on control quality was investigated, which is important for model-based algorithms with fast sampling.
Źródło:
Pomiary Automatyka Robotyka; 2023, 27, 2; 47--58
1427-9126
Pojawia się w:
Pomiary Automatyka Robotyka
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:
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:
Neural Network-Based Narx Models in Non-Linear Adaptive Control
Autorzy:
Dzieliński, A.
Powiązania:
https://bibliotekanauki.pl/articles/907986.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
automatyka
neural networks
adaptive control
nonlinear systems
Opis:
The applicability of approximate NARX models of non-linear dynamic systems is discussed. The models are obtained by a new version of Fourier analysis-based neural network also described in the paper. This constitutes a reformulation of a known method in a recursive manner, i.e. adapted to account for incoming data on-line. The method allows us to obtain an approximate model of the non-linear system. The estimation of the influence of the modelling error on the discrepancy between the model and real system outputs is given. Possible applications of this approach to the design of BIBO stable closed-loop control are proposed.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 2; 235-240
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Control of Fractional-Order Nonlinear Systems: A Review
Autorzy:
Petráš, I.
Bednárová, D.
Powiązania:
https://bibliotekanauki.pl/articles/386576.pdf
Data publikacji:
2011
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
sterowanie
systemy nielioniowe
przegląd
control
nonlinear systems
review
Opis:
This paper deals with the control of the fractional-order nonlinear systems. A list of the control strategies as well as synchronization of the chaotic systems is presented. An illustrative example of sliding mode control (SMC) of the fractional-order (commensurate and incommensurate) financial system is described and commented together with the simulation results.
Źródło:
Acta Mechanica et Automatica; 2011, 5, 2; 96-100
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Finite horizon nonlinear predictive control by the Taylor approximation: Application to robot tracking trajectory
Autorzy:
Hedjar, R.
Toumi, R.
Boucher, P.
Dumur, D.
Powiązania:
https://bibliotekanauki.pl/articles/908454.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
układ nieliniowy
układ ciągły
sterowanie predykcyjne
aproksymacja Taylora
śledzenie trajektorii
nonlinear continuous time predictive control
Taylor approximation
tracking trajectory and robot
Opis:
In industrial control systems, practical interest is driven by the fact that today’s processes need to be operated under tighter performance specifications. Often these demands can only be met when process nonlinearities are explicitly considered in the controller. Nonlinear predictive control, the extension of well-established linear predictive control to nonlinear systems, appears to be a well-suited approach for this kind of problems. In this paper, an optimal nonlinear predictive control structure, which provides asymptotic tracking of smooth reference trajectories, is presented. The controller is based on a finite–horizon continuous time minimization of nonlinear predicted tracking errors. A key feature of the control law is that its implementation does not need to perform on-line optimization, and asymptotic tracking of smooth reference signal is guaranteed. An integral action is used to increase the robustness of the closed-loop system with respect to uncertainties and parameters variations. The proposed control scheme is first applied to planning motions problem of a mobile robot and, afterwards, to the trajectory tracking problem of a rigid link manipulator. Simulation results are performed to validate the tracking performance of the proposed controller.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 527-540
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptacyjny regulator LQR w układzie sterowania kątem kursowym i prędkością statku opisanego nieliniowym modelem dynamicznym MIMO
Adaptative LQR course-keeping controller for the nonlinear MIMO model of a container vessel
Autorzy:
Brasel, M.
Powiązania:
https://bibliotekanauki.pl/articles/408076.pdf
Data publikacji:
2014
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
sterowanie optymalne
sterowanie adaptacyjne
obiekty nieliniowe
nieliniowy model statku
optimal control
adaptive control
nonlinear systems
nonlinear model of a ship
Opis:
W artykule zaprezentowano adaptacyjny układ sterowania kątem kursowym i prędkością statku opisanego nieliniowym modelem dynamicznym MIMO (ang. Multi-input, Multi-Output) o czterech stopniach swobody ruchu (ang. Four-Degrees-of-Freedom, 4-DoF). Przedstawiony model statku jest silnie nieliniowy i uwzględnia nie tylko ograniczenia saturacyjne sygnałów sterujących ale także dynamikę maszyny sterowej i napędu głównego. Głównym zadaniem zaprojektowanego adaptacyjnego regulatora LQR jest sterowanie kątem kursowym statku i jego prędkością względem wody. Poszczególne zestawy parametrów regulatora użyte w procesie adaptacji zostały wyznaczone na podstawie linearyzacji modelu statku w wybranych nominalnych punktach pracy. W końcowej części artykułu przedstawiono wyniki badań symulacyjnych zaprojektowanego regulatora w układzie z pełnym nieliniowym modelem statku.
In the paper an adaptive control system for the nonlinear 4-DoF model of a container vessel is presented. The considered model of the ship includes input signals saturations and dynamics of actuators. Main goal of the presented control system is control of the course angle and speed of the ship relative to water. The system synthesis is carried out by means of LQ-optimal control method. Sets of controller parameters are designed using linearization of the considered model in the nominal steady-state operating points of the ship. The final part of the paper includes simulation results of control system operation with full nonlinear MIMO model of the container vessel.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2014, 2; 49-52
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Output tracking control of an aircraft subject to additive state dependent disturbance: an optimal control approach
Autorzy:
Tanyer, Ilker
Tatlicioglu, Enver
Zergeroglu, Erkan
Powiązania:
https://bibliotekanauki.pl/articles/1409414.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
optimal control
aerospace applications
nonlinear systems
mechanical applications
mechatronics applications
robust control
Opis:
In this paper, model reference output feedback tracking control of an aircraft subject to additive, uncertain, nonlinear disturbances is considered. In order to present the design steps in a clear fashion: first, the aircraft dynamics is temporarily assumed as known with all the states of the system available. Then a feedback linearizing controller minimizing a performance index while only requiring the output measurements of the system is proposed. As the aircraft dynamics is uncertain and only the output is available, the proposed controller makes use of a novel uncertainty estimator. The stability of the closed loop system and global asymptotic tracking of the proposed method are ensured via Lyapunov based arguments, asymptotic convergence of the controller to an optimal controller is also established. Numerical simulations are presented in order to demonstrate the feasibility and performance of the proposed control strategy.
Źródło:
Archives of Control Sciences; 2021, 31, 2; 267-286
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Friction compensation in nonlinear dynamical systems using fault-tolerant control methods
Autorzy:
Bonfè, M.
Castaldi, P.
Preda, N.
Simani, S.
Powiązania:
https://bibliotekanauki.pl/articles/327170.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
fault-tolerant control
friction compensation
nonlinear systems
differential geometry
Opis:
This paper describes the application of differential geometry and nonlinear systems analysis to the estimation of friction effects in a class of mechanical systems. The proposed methodology relies on adaptive filters, designed with a nonlinear geometric approach to obtain the disturbance de-coupling property, for the estimation of the friction force. Thanks to accurate estimation, friction effects are compensated by injecting the on-line estimate of friction force to the control action calculated by a standard linear state feedback. The inverted pendulum on a cart is considered as an application example and the proposed approach is compared with a commonly used friction compensation strategy, based on an explicit model of the friction force.
Źródło:
Diagnostyka; 2013, 14, 4; 13-19
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamic Contraction Method approach to digital longitudinal aircraft flight controller design
Autorzy:
Czyba, Roman
Stajer, Lukasz
Powiązania:
https://bibliotekanauki.pl/articles/229293.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
nonlinear systems
MIMO systems
aircraft control
digital controller
singular perturbation
Opis:
This paper presents the design of digital controller for longitudinal aircraft model basedon the Dynamic Contraction Method. The control task is formulated as a tracking problem of velocity and flight path angle, where decoupled output transients are accomplished in spite of incomplete information about varying parameters of the system and external disturbances. The design of digital controller based on the pseudo-continuous approach is presented, where the digital controller is the result of continuous-time controller discretization. A resulting output feedback controller has a simple form of a combination of low-order linear dynamical systems and a matrix whose entries depend nonlinearly on certain known process variables. Simulation results for an aircraft model confirm theoretical expectations.
Źródło:
Archives of Control Sciences; 2019, 29, 1; 97-109
1230-2384
Pojawia się w:
Archives of Control Sciences
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
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