Temat: Model predictive control

Skocz do pozycji: 1.

Tytuł:: Sterowanie predykcyjne reaktorem egzotermicznym z wykorzystaniem linearyzacji
Constrained predictive control of continuous stirred exothermical reactor using linearization
Autorzy:: Ziętek, Beata
Ziętkiewicz, Joanna
Wydawca:: Wydawnictwo Poznańskiego Towarzystwa Przyjaciół Nauk
Cytata wydawnicza:: B. Ziętek, J. Ziętkiewicz: Constrained predictive control of continuous stirred exothermical reactor using linearization. Studia z Automatyki i Informatyki, Vol. 41, 2016, pp. 55-65.
Opis:: W artykule podejmowany jest problem sterowania predykcyjnego z modelem otrzymanym w procesie linearyzacji w punkcie. Obiektem regulacji jest reaktor chemiczny z wieloma punktami równowagi. Analiza algorytmu pokazuje jak punkt równowagi użyty do linearyzacji oraz wartości sygnału zadanego, zmienianego skokowo, wpływają na jakość algorytmu sterowania.
This paper considers constrained predictive control with linearized model. The object of control is a chemical reactor with many equilibrium points. The analysis show how the linearization steady-state point and the values in reference signal influence the performance of control algorithm.
Piotr Kozierski
Dostawca treści:: Repozytorium Centrum Otwartej Nauki

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Skocz do pozycji: 2.

Tytuł:: Robust model predictive control for autonomous Underwater Vehicle – Manipulator System with fuzzy compensator
Autorzy:: Esfahani, Hossein Nejatbakhsh
Tematy:: UVMS
model predictive control
fuzzy compensator; Pokaż więcej
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:: https://bibliotekanauki.pl/articles/260317.pdf Link otwiera się w nowym oknie
Opis:: This paper proposes an improved Model Predictive Control (MPC) approach including a fuzzy compensator in order to track desired trajectories of autonomous Underwater Vehicle Manipulator Systems (UVMS). The tracking performance can be affected by robot dynamical model uncertainties and applied external disturbances. Nevertheless, the MPC as a known proficient nonlinear control approach should be improved by the uncertainty estimator and disturbance compensator particularly in high nonlinear circumstances such as underwater environment in which operation of the UVMS is extremely impressed by added nonlinear terms to its model. In this research, a new methodology is proposed to promote robustness virtue of MPC that is done by designing a fuzzy compensator based on the uncertainty and disturbance estimation in order to reduce or even omit undesired effects of these perturbations. The proposed control design is compared with conventional MPC control approach to confirm the superiority of the proposed approach in terms of robustness against uncertainties, guaranteed stability and precision.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Effectiveness of Dynamic Matrix Control algorithm with Laguerre functions
Autorzy:: Tatjewski, Piotr
Tematy:: process control
model predictive control
DMC algorithm
Laguerre functions; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2083461.pdf Link otwiera się w nowym oknie
Opis:: The paper is concerned with the presentation and analysis of the Dynamic Matrix Control (DMC) model predictive control algorithm with the representation of the process input trajectories by parametrised sums of Laguerre functions. First the formulation of the DMCL (DMC with Laguerre functions) algorithm is presented. The algorithm differs from the standard DMC one in the formulation of the decision variables of the optimization problem - coefficients of approximations by the Laguerre functions instead of control input values are these variables. Then the DMCL algorithm is applied to two multivariable benchmark problems to investigate properties of the algorithm and to provide a concise comparison with the standard DMC one. The problems with difficult dynamics are selected, which usually leads to longer prediction and control horizons. Benefits from using Laguerre functions were shown, especially evident for smaller sampling intervals.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Long-horizon model predictive control of induction motor drive
Autorzy:: Wróbel, Karol Tomasz
Szabat, Krzysztof
Serkies, Piotr
Tematy:: model predictive control
long horizon
induction motor drive; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/140624.pdf Link otwiera się w nowym oknie
Opis:: This paper investigates the application of a novel Model Predictive Control struc- ture for the drive system with an induction motor. The proposed controller has a cascade-free structure that consists of a vector of electromagnetics (torque, flux) and mechanical (speed) states of the system. The long-horizon version of the MPC is investigated in the paper. In order to reduce the computational complexity of the algorithm, an explicit version is applied. The influence of different factors (length of the control and predictive horizon, values of weights) on the performance of the drive system is investigated. The effectiveness of the proposed approach is validated by some experimental tests.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Internet digital content pricing and subscribers control
Autorzy:: Mejjouali, Sobhi
Tadj, Lotfi
Tematy:: maximum principle
model predictive control
optimal control
web content pricing; Pokaż więcej
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:: https://bibliotekanauki.pl/articles/27315325.pdf Link otwiera się w nowym oknie
Opis:: We use optimal control theory to determine the optimal rate of change in the subscription fee and the optimal ratio of ad space to the total web page space for a web content provider. An optimal solution is obtained using the maximum principle approach and the model predictive control approach. Numerical experiments show that it is preferable to use the first approach when the planning horizon is short and the second approach when the planning horizon is long.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: A computationally efficient stable dual-mode type nonlinear predictive control algorithm
Autorzy:: Ławryńczuk, M.
Tadej, W.
Tematy:: linearyzacja
optymalizacja
stabilność
nonlinear model predictive control
dual-mode model predictive control
process control
linearisation
optimisation
quadratic programming
stability
constraints
terminal set; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:: https://bibliotekanauki.pl/articles/971003.pdf Link otwiera się w nowym oknie
Opis:: This paper describes a computationally efficient (sub-optimal) nonlinear predictive control algorithm. The algorithm uses a modified dual-mode approach which guarantees closed-loop stability. In order to reduce the computational burden, instead of online nonlinear optimisation used in the classical dual-mode control scheme, a nonlinear model of the plant is linearised on-line and a quadratic programming problem is solved. Calculation of the terminal set and implementation steps of the algorithm are detailed, especially for input-output models, which are widely used in practice.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Robust fuzzy model predictive control of an overhead crane
Autorzy:: Smoczek, J.
Szpytko, J.
Tematy:: overhead crane
model predictive control
linear parameter varying model
fuzzy interpolation; Pokaż więcej
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Powiązania:: https://bibliotekanauki.pl/articles/242944.pdf Link otwiera się w nowym oknie
Opis:: The method of controlling an overhead crane with respect to the variation of operating conditions and control constraints is developed using a model predictive control (MPC) and fuzzy interpolation applied in linear parameter varying (LPV) approach to crane dynamic modelling. The proposed control approach is based on the assumption that operating conditions vary within the known range of scheduling variables, and the parameters of a crane dynamic model can be interpolated by a quasi-linear fuzzy model designed through utilizing the P1-TS fuzzy theory. Hence, a crane dynamic is approximated through interpolation between a set of local linear models determined through identification experiments at the local operating points selected within the bounded intervals of scheduling variables. For the modelling assumptions, the control algorithm is developed based on a generalized predictive control (GPC) procedure taking into consideration the constraints on sway angle of a payload and control signal. Feasibility and applicability of the proposed control technique were confirmed during experiments carried out on a laboratory-scaled overhead crane. The results of experiments are presented and compared with performances of a fuzzy logic-based scheduling control scheme.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Evacuation by leader-follower model with bounded confidence and predictive mechanisms
Autorzy:: Almeida, Ricardo
Girejko, Ewa
Machado, Luis
Malinowska, Agnieszka B.
Martins, Natália
Tematy:: multi-agent systems
emergency
model predictive control
bounded confidence; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/1845516.pdf Link otwiera się w nowym oknie
Opis:: This paper studies an evacuation problem described by a leader-follower model with bounded confidence under predictive mechanisms. We design a control strategy in such a way that agents are guided by a leader, which follows the evacuation path. The proposed evacuation algorithm is based on Model Predictive Control (MPC) that uses the current and the past information of the system to predict future agents’ behaviors. It can be observed that, with MPC method, the leader-following consensus is obtained faster in comparison to the conventional optimal control technique. The effectiveness of the developed MPC evacuation algorithm with respect to different parameters and different time domains is illustrated by numerical examples.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Evacuation by leader-follower model with bounded confidence and predictive mechanisms
Autorzy:: Almeida, Ricardo
Girejko, Ewa
Machado, Luis
Malinowska, Agnieszka B.
Martins, Natália
Tematy:: multi-agent systems
emergency
model predictive control
bounded confidence; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/1845527.pdf Link otwiera się w nowym oknie
Opis:: This paper studies an evacuation problem described by a leader-follower model with bounded confidence under predictive mechanisms. We design a control strategy in such a way that agents are guided by a leader, which follows the evacuation path. The proposed evacuation algorithm is based on Model Predictive Control (MPC) that uses the current and the past information of the system to predict future agents’ behaviors. It can be observed that, with MPC method, the leader-following consensus is obtained faster in comparison to the conventional optimal control technique. The effectiveness of the developed MPC evacuation algorithm with respect to different parameters and different time domains is illustrated by numerical examples.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Supervisory optimal control using machine learning for building thermal comfort
Autorzy:: Abdufattokhov, Shokhjakhon
Mahamatov, Nurilla
Ibragimova, Kamila
Gulyamova, Dilfuza
Yuldashev, Dilyorjon
Tematy:: building thermal comfort
Gaussian processes
machine learning
model predictive control; Pokaż więcej
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:: https://bibliotekanauki.pl/articles/2204083.pdf Link otwiera się w nowym oknie
Opis:: For the past few decades, control and building engineering communities have been focusing on thermal comfort as a key factor in designing sustainable building evaluation methods and tools. However, estimating the indoor air temperature of buildings is a complicated task due to the nonlinear and complex building dynamics characterised by the time-varying environment with disturbances. The primary focus of this paper is designing a predictive and probabilistic room temperature model of buildings using Gaussian processes (GPs) and incorporating it into model predictive control (MPC) to minimise energy consumption and provide thermal comfort satisfaction. The full probabilistic capabilities of GPs are exploited from two perspectives: the mean prediction is used for the room temperature model, while the uncertainty is involved in the MPC objective not to lose the desired performance and design a robust controller. We illustrated the potential of the proposed method in a numerical example with simulation results.
Dostawca treści:: Biblioteka Nauki

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