Ograniczanie wyników
Czasopisma help
Autorzy help
Lata help
Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 201

Liczba wyników na stronie
first rewind previous Strona / 11 next fast forward last
Wyniki wyszukiwania
Wyszukiwano:
w słowach kluczowych:  adaptive control
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 11 next fast forward last
EN
This paper presents a concept of architecture and ontology layouts for the development of multiagent model-based predictive control systems. The presented architecture provides guidelines to simplify the development of agent-based systems and improve their maintainability. The proposed multiagent system (MAS) layout is split into multiple subsystems that include agents dedicated to performing assigned tasks. MAS implementation was prepared which can use provided algorithms and actuators and can react to changes in its environment to reach the best available control quality. An example of MAS based on the proposed architecture is shown in the application of dissolved oxygen (DO) concentration control in a laboratory-activated sludge setup with a biological reactor. For that application, MAS incorporates agent-based controllers from the boundary-based predictive controllers (BBPC) family. Presented experiments prove the flexibility, resilience, and online reconfiguration ability of the proposed multiagent system.
PL
W pracy przedstawiono problem syntezy prawa sterowania modułu wspomagania nawigacji semiautonomicznego wózka inwalidzkiego w dynamicznym środowisku, w obecności pieszych. Osoba poruszająca się na wózku inwalidzkim może spotkać się ze zjawiskiem empatii ze strony osób, z którymi wchodzi w interakcje. W pracy pokazano wykorzystanie tego zjawiska do adaptacji stylu automatycznego sterowania ruchem wózka. Działanie proponowanego podejścia zweryfikowano za pomocą symulacji.
EN
The paper presents the problem of designing a navigation strategy for a semiautonomous wheelchair cruise control system, intended to help driving the wheelchair in populated, dynamical environments. The method discussed in this paper utilizes long-term, model-based environmental prediction for planning the motion of the wheelchair. Resulting navigation strategy is both human aware and acceptable for the person driving the vehicle. The adaptation mechanism was implemented and verified using simulation.
PL
W publikacji przedstawiona została modyfikacja klasycznego regulatora stanu, która zakłada wprowadzenie radialnej sieci neuronowej (Radial Basis Function Neural Network). Celem jest wygenerowanie sygnału, który zostanie wprowadzony do wektora zmiennych stanu sprzężeń zwrotnych. Obiektem regulacji jest napęd elektryczny z połączeniem sprężystym. W artykule uwzględniono opis teoretyczny proponowanego rozwiązania, a także zaprezentowano wyniki badań symulacyjnych struktury sterowania. Badania przeprowadzone dla rzeczywistego układu napędowego stanowią dodatkową weryfikację analizowanego regulatora stanu.
EN
In this paper, a state feedback controller enhanced by a Radial Basis Function Neural Network is presented. The main goal of the network is calculation of a virtual signal used in state vector and applied as feedback. The plant considered in the article is an electrical drive with a flexible joint. The mathematical description of the proposed control scheme and the numerical tests can be found in the manuscript. Experimental analysis is performed as an additional verification of the proposed state controller.
EN
In this paper, we will develop an adaptive control algorithm applied to the wind energy conversion system (WECS) based on a double-fed induction machine (DFIM) driven by a turbine with variable blade pitch, and controlled through the rotor variables by two bidirectional converters. The main function of these converters in the considered system is the connection of the wind generator to the power grid in two different ways: one on the grid side converter which will allow continuous bus control and improve the power factor on the grid side; the other, on the converter on the rotor side, which will allow the control and optimization of the energy flow generated by the stator during the periods of operation of this system. In the first part we presented the individual modeling of the wind turbine chain, then we presented and developed the controls necessary to control the active and reactive powers produced by this system in order to ensure optimum performance and production quality.
PL
W niniejszym artykule opracujemy algorytm sterowania adaptacyjnego zastosowany w systemie konwersji energii wiatru (SKEW) oparty na dwustronnie zasilanej maszynie indukcyjnej (DZMI) napędzanej turbiną o zmiennym skoku łopatek i sterowanej poprzez zmienne wirnika dwoma dwukierunkowymi konwertery. Główną funkcją tych przekształtników w rozpatrywanym systemie jest podłączenie generatora wiatrowego do sieci elektroenergetycznej na dwa różne sposoby: jeden po stronie przekształtnika sieciowego, który umożliwi ciągłą kontrolę magistrali i poprawi współczynnik mocy po stronie sieci; drugi, na przekształtniku po stronie wirnika, co pozwoli na sterowanie i optymalizację przepływu energii generowanej przez stojan w okresach pracy tego układu. W pierwszej części przedstawiliśmy indywidualne modelowanie łańcucha turbiny wiatrowej, następnie przedstawiliśmy i opracowaliśmy sterowanie niezbędne do sterowania mocą czynną i bierną wytwarzaną przez ten system w celu zapewnienia optymalnej wydajności i jakości produkcji.
PL
W pracy przedstawiono algorytm adaptacyjnego sterowania położeniem ramienia w układzie napędowym z nieliniowym połączeniem sprężystym. Do zaprojektowania algorytmu sterowania użyto metody „całkowania wstecz”. Zaproponowane w algorytmie prawa adaptacji realizują funkcję samostrojenia układu regulacji pozwalając projektantowi na nieznajomość parametrów układu napędowego. Działanie algorytmu zostało sprawdzone symulacyjnie oraz w układzie rzeczywistym.
EN
The paper presents an algorithm of adaptive control of the arm position in the drive with a non-linear elastic joint. The backstepping method was used to design the control algorithm. The laws of adaptation proposed in the algorithm implement the self-tuning function of the control system, and allow to avoid a process of identification parameters of the drive system. The operation of the algorithm has been verified in a simulation and in a real system.
PL
Praca przedstawia zagadnienie dotyczące pomiaru i analizy zużycia energii w trakcie cyklu wiercenia termicznego. Przedstawiono oparte na tokarce CNC stanowisko badawcze, którego elementem wyposażenia był eksperymentalny układ poboru energii oparty o licznik energii elektrycznej oraz siłomierz. Zastosowane urządzenia pomiarowe pozwalały na rejestrację obciążenia sieci energetycznej, obciążenia napędów obrabiarki, siłę osiową, moment hamujący wiertło, aktualne obroty wrzeciona obrabiarki, pozycję wiertła względem obrabianego materiału i wartości rejestrów parametrów pomocniczych w strategii adaptacyjnego sterowania posuwem. Rozważano dwa przypadki cyklu wiercenia: wykonanie pojedynczego otworu oraz wykonanie szeregu otworów w jednym cyklu. Testowano pięć strategii sterowania posuwem w trakcie cyklu wiercenia, w tym adaptacyjne sterowanie posuwem i rekurencyjną metodę optymalizacji posuwu. Dla porównania wykonano także otwory tradycyjnymi wiertłami krętymi HSS. Na podstawie uzyskanych rezultatów badań można stwierdzić, że metoda wiercenia ciernego może być zaliczona do energooszczędnych metod wykonywania otworów w elementach cienkościennych.
EN
The work presents the issue of measuring and analyzing energy consumption during a thermal drilling cycle. A research stand based on a CNC lathe was presented, the equipment of which was an experimental energy consumption system based on an electricity meter and a force gauge. The measuring devices used allowed for recording the load on the power grid, the load on the machine tool drives, the axial force, the drill braking torque, the current rotation of the machine tool spindle, the position of the drill in relation to the workpiece and the values of auxiliary parameter registers in the strategy of adaptive feed control. Two cases of a drilling cycle were considered: making a single hole and making a series of holes in one cycle. Five feed control strategies were tested during the drilling cycle, including adaptive feed control and a recursive feed optimization method. For comparison, holes were also made with traditional HSS twist drills. Based on the obtained test results, it can be concluded that the friction drilling method can be included in the energy-saving methods of making holes in thin-walled elements.
EN
The paper introduces Extended Identification-Based Predictive Control (EIPC), which is a novel control method developed for the problem of adaptive impact mitigation. The model-based approach utilizing the paradigm of Model Predictive Control is combined with sequential identification of selected system parameters and process disturbances. The elaborated method is implemented in the shock-absorber control system and tested under impact loading conditions. The presented numerical study proves the successful and efficient adaptation of the absorber to unknown excitation conditions as well as to unknown force and leakage disturbances appearing during the process. The EIPC is used for both semi-active and active control of the impact mitigation process, which are compared in detail. In addition, the influence of selected control parameters and disturbance identification on the efficiency of the impact absorption process is assessed. As a result, it can be concluded that an efficient and robust control method was developed and successfully applied to the problem of adaptive impact mitigation.
EN
Reliability and safety of an electro-hydraulic position servo system (EHPSS) can be greatly reduced for potential sensor and actuator faults. This paper proposes a novel reconfiguration control (RC) scheme that combines multi-model and adaptive control to compensate for the adverse effects. Such a design includes several fixed models, one adaptive model, and one reinitialized adaptive model. Each of the models has its own independent controller that is based on a complete parametrization of the corresponding fault. A proper switching mechanism is set up to select the most appropriate controller to control the current plant. The system output can track the reference model asymptotically using the proposed method. Simulation results validate robustness and effectiveness of the proposed scheme. The main contribution is a reconfiguration control method that can handle component faults and maintain the acceptable performance of the EHPSS.
EN
In this article, an method is proposed combining optimal control for linear system and disturbances observer to control a 3 degree of freedom (3DoF) robot manipulator. By making the tracking error follow a given stable linear reference model through the observer, an optimal controller LQR will be designed to solve the optimization problem for the reference system, thereby leading to good control quality for the original system. The effectiveness of the method is shown through simulation results performed on Matlab/Simulink.
EN
The paper presents an adaptive control algorithm for an asymmetric quadcopter. For determining the control algorithm, the identification was made, and an identification algorithm is presented in the form of a recursive method. The control method is realized using inverse dynamics, full state feedback and finally adaptive control method. The algorithms for the off-line and on-line identification of quadcopter model parameters are also presented. The paper shows the effectiveness of the selected algorithm on the example of the movement along a given trajectory. Finally, recommendations of the application of these different methods are made.
PL
W pracy przedstawiono algorytm sterowania adaptacyjnego dla asymetrycznego quadrocoptera. W celu określenia sterowania zrealizowano identyfikację parametrów i przedstawiono algorytm identyfikacji w formie metody rekurencyjnej. Metoda sterowania realizowana jest z wykorzystaniem dynamiki odwrotnej, przesuwania biegunów oraz sterowania adaptacyjnego. Zaprezentowano algorytmy identyfikacji parametrów modelu quadrocoptera w trybie off-line i on-line. W artykule przedstawiono skuteczność wybranych algorytmów na przykładzie ruchu wzdłuż podanej trajektorii. Na zakończenie artykułu przedstawiono zalecenia dotyczące stosowania różnych metod sterowania.
EN
To solve the nonlinear control problems of the unknown time-varying environmental disturbances and parametric uncertainties for ship course-keeping control, this paper presents an adaptive self-regulation PID (APID) scheme which can ensure the boundedness of all signals in the ship course-keeping control system by using the Lyapunov direct method. Compared with the traditional PID control scheme, the APID control scheme not only is independent of the model parameters and the unknown input, but also can regulate the gain of PID adaptively and resist time-varying disturbances well. Simulation results illustrate the effectiveness and the robustness of the proposed control scheme.
12
EN
In this paper, the issue related to control of the plant with nonconstant parameters is addressed. In order to assure the unchanged response of the system, an adaptive state feedback speed controller for permanent magnet synchronous motor is proposed. The model-reference adaptive system is applied while the Widrow-Hoff rule is used as adjustment mechanism of controller’s coefficients. Necessary modifications related to construction of the cost function and formulas responsible for adjustment of state feedback speed controller’s coefficients are depicted. The impact of adaptation gain, which is the only parameter in proposed adjustment mechanism, on system behaviour is experimentally examined. The discussion about computational resources consumption of the proposed adaptation algorithm and implementation issues is included. The proposed approach is utilized in numerous experimental tests on modern SiC based drive with nonconstant moment of inertia. Comparison between adaptive and nonadaptive control schemes is also shown.
EN
The paper describes a nonlinear controller design technique applied to a servo drive in the presence of hard state constraints. The approach presented is based on nonlinear state-space transformation and adaptive backstepping. It allows us to impose hard constraints on the state variables directly and to achieve asymptotic tracking of any reference trajectory inside the constraints, despite unknown plant parameters. Two control schemes (with and without integral action) are derived, investigated and then compared. Several examples demonstrate the main features of the design procedure and prove that it may be applied in case of motion control problems in electric drive automation.
EN
The paper presents a method for designing a neural speed controller with use of Reinforcement Learning method. The controlled object is an electric drive with a synchronous motor with permanent magnets, having a complex mechanical structure and changeable parameters. Several research cases of the control system with a neural controller are presented, focusing on the change of object parameters. Also, the influence of the system critic behaviour is researched, where the critic is a function of control error and energy cost. It ensures long term performance stability without the need of switching off the adaptation algorithm. Numerous simulation tests were carried out and confirmed on a real stand.
EN
This paper deals with two control algorithms which utilize learning of their models’ parameters. An adaptive and artificial neural network control techniques are described and compared. Both control algorithms are implemented in MATLAB and Simulink environment, and they are used in the simulation of a postion control of the LWR 4+ manipulator subjected to unknown disturbances. The results, showing the better performance of the artificial neural network controller, are shown. Advantages and disadvantages of both controllers are discussed. The usefulness of the learning algorithms for the control of LWR 4+ robots is discussed. Preliminary experiments dealing with dynamic properties of the two LWR 4+ robots are reported.
EN
Stabilization of the carbon monoxide (CO) in the waste gas is a common technical problem in many industrial plants. Stabilization can be performed continuously by regulating the fuel input or by regulating the exhaust gas draught. This paper proposes an adaptive control system for CO stabilization in waste gases based on a discrete controller. Heuristic adaptation of a discrete controller is based on continuous optimization of controller parameters. The advantage of this solution is that the control system does not need to perform the identification of the controlled system repeatedly. The parameters of the controller are dynamically optimized during the production process. By regulating the under-pressure, we change the amount of air supplied to the combustion chambers, which affects the combustion of gaseous fuel and also the concentration of CO in the waste flue gas. The control algorithm was verified for the combustion process in coke making. The proposed control achieved good stabilization quality when verified in simulation and also in an industry operation. The CO level at which the waste gas temperature was highest was selected as the setpoint. It was found that the stabilization of CO in waste gas to lower values is possible to achieve higher waste gas temperature and by that, higher temperatures in heating chambers.
EN
This paper analyses the management process of the vessel traffic control on one-way section on navigable canal with the adaptive time-sequential filter (traffic lights). One-way section on canal significantly decreases waterway capacity and requests special attention in control and regulation of the vessel traffic. The vessel traffic is a stochastic variable, and the vessel traffic control needs to be flexible and adaptive in order to achieve the required traffic flow with minimal delays. On the one-way section, two independent variable vessel flows from opposite directions are encountered, and fixed (predefined) signal plans lead to an increase in vessel delays. An appropriate solution is development of a Fuzzy Control System (FCS) for the vessel traffic control. A control algorithm is designed according to a set of linguistic rules that describes input parameters for the control strategy. The estimated and approximate input parameters are implemented in the algorithm as fuzzy sets. The final result of the developed algorithm is the traffic light scheme (duration of green light for certain direction). The presented control system can be used as an adaptive automatic control system for the vessel traffic control processes on navigable canals or on critical sections of other waterways.
EN
Today's highly automated manufacturing specifies the service time of a tool in a way that the tooling costs are balanced against the potential costs of a tool failure. However, the potential cost induced by a tool malfunctioning are rather high. Therefore, the current state-of-the art tackles this issue by replacing the tools prematurely at fixed intervals. To tap into the potential of under-utilized tool runtime this work purposes the use of sensory-tool holders and an interfering feedback loop to the machine tool control system. Besides its real-time closed loop control, to avoid tool failure, it also provides data in the context of (a) the work order, (b) the produced part, (c) the NC-block and command line, on (d) specific machines. Based on this data an ex-post analysis to optimize tool-life and productivity scenarios becomes possible, e.g. custom NC-programs for certain work-orders, configurations and machines. Furthermore, downstreamed work steps can be changed e.g. only to measure produced workpieces if abnormal vibrations are reported by in-process-monitoring.
EN
The issue addressed in the article concerns the current needs and possibilities of computer-aided design of adaptive control strategies in machining processes. A simulative method of selecting the adaptive feed control strategy while rough turning materials difficult to machine, effective and inexpensive in its implementation, based on controlling the load placed on the machine's drives, has been presented. The results of a number of virtual tests of the proposed feed control strategy have been included, while paying particular attention to the stability of the machining process during moments of sudden change in the machining allowance. The obtained results meet the accepted quality indicators of the control algorithm. At the same time, the experiences collected by the author while conducting the tests confirmed the complexity of the issue and the resulting necessity to implement a comprehensive simulation testing program.
EN
We introduce a control strategy to solve the regulation control problem, from the perspective of trajectory planning, for an uncertain 3D overhead crane. The proposed solution was developed based on an adaptive control approach that takes advantage of the passivity properties found in this kind of systems. We use a trajectory planning approach to preserve the accelerations and velocities inside of realistic ranges, to maintaining the payload movements as close as possible to the origin. To this end, we carefully chose a suitable S-curve based on the Bezier spline, which allows us to efficiently handle the load translation problem, considerably reducing the load oscillations. To perform the convergence analysis, we applied the traditional Lyapunov theory, together with Barbalat’s lemma. We assess the effectiveness of our control strategy with convincing numerical simulations.
first rewind previous Strona / 11 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.