919 resultados para Active linear feedback control
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This work presents a strategy to control nonlinear responses of aeroelastic systems with control surface freeplay. The proposed methodology is developed for the three degrees of freedom typical section airfoil considering aerodynamic forces from Theodorsen's theory. The mathematical model is written in the state space representation using rational function approximation to write the aerodynamic forces in time domain. The control system is designed using the fuzzy Takagi-Sugeno modeling to compute a feedback control gain. It useds Lyapunov's stability function and linear matrix inequalities (LMIs) to solve a convex optimization problem. Time simulations with different initial conditions are performed using a modified Runge-Kutta algorithm to compare the system with and without control forces. It is shown that this approach can compute linear control gain able to stabilize aeroelastic systems with discontinuous nonlinearities.
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The design and implementation of a new control scheme for reactive power compensation, voltage regulation and transient stability enhancement for wind turbines equipped with fixed-speed induction generators (IGs) in large interconnected power systems is presented in this study. The low-voltage-ride-through (LVRT) capability is provided by extending the range of the operation of the controlled system to include typical post-fault conditions. A systematic procedure is proposed to design decentralised multi-variable controllers for large interconnected power systems using the linear quadratic (LQ) output-feedback control design method and the controller design procedure is formulated as an optimisation problem involving rank-constrained linear matrix inequality (LMI). In this study, it is shown that a static synchronous compensator (STATCOM) with energy storage system (ESS), controlled via robust control technique, is an effective device for improving the LVRT capability of fixed-speed wind turbines.
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Semi-active damping devices have been shown to be effective in mitigating unwanted vibrations in civil structures. These devices impart force indirectly through real-time alterations to structural properties. Simulating the complex behavior of these devices for laboratory-scale experiments is a major challenge. Commercial devices for seismic applications typically operate in the 2-10 kN range; this force is too high for small-scale testing applications where requirements typically range from 0-10 N. Several challenges must be overcome to produce damping forces at this level. In this study, a small-scale magneto-rheological (MR) damper utilizing a fluid absorbent metal foam matrix is developed and tested to accomplish this goal. This matrix allows magneto-rheological (MR) fluid to be extracted upon magnetic excitation in order to produce MR-fluid shear stresses and viscosity effects between an electromagnetic piston, the foam, and the damper housing. Dampers for uniaxial seismic excitation are traditionally positioned in the horizontal orientation allowing MR-fluid to gather in the lower part of the damper housing when partially filled. Thus, the absorbent matrix is placed in the bottom of the housing relieving the need to fill the entire device with MR-fluid, a practice that requires seals that add significant unwanted friction to the desired low-force device. The damper, once constructed, can be used in feedback control applications to reduce seismic vibrations and to test structural control algorithms and wireless command devices. To validate this device, a parametric study was performed utilizing force and acceleration measurements to characterize damper performance and controllability for this actuator. A discussion of the results is presented to demonstrate the attainment of the damper design objectives.
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This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.
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El principal objetivo de la tesis es estudiar el acoplamiento entre los subsistemas de control de actitud y de control térmico de un pequeño satélite, con el fin de buscar la solución a los problemas relacionados con la determinación de los parámetros de diseño. Se considera la evolución de la actitud y de las temperaturas del satélite bajo la influencia de dos estrategias de orientación diferentes: 1) estabilización magnética pasiva de la orientación (PMAS, passive magnetic attitude stabilization), y 2) control de actitud magnético activo (AMAC, active magnetic attitude control). En primer lugar se presenta el modelo matemático del problema, que incluye la dinámica rotacional y el modelo térmico. En el problema térmico se considera un satélite cúbico modelizado por medio de siete nodos (seis externos y uno interno) aplicando la ecuación del balance térmico. Una vez establecido el modelo matemático del problema, se estudia la evolución que corresponde a las dos estrategias mencionadas. La estrategia PMAS se ha seleccionado por su simplicidad, fiabilidad, bajo coste, ahorrando consumo de potencia, masa coste y complejidad, comparado con otras estrategias. Se ha considerado otra estrategia de control que consigue que el satélite gire a una velocidad requerida alrededor de un eje deseado de giro, pudiendo controlar su dirección en un sistema inercial de referencia, ya que frecuentemente el subsistema térmico establece requisitos de giro alrededor de un eje del satélite orientado en una dirección perpendicular a la radiación solar incidente. En relación con el problema térmico, para estudiar la influencia de la velocidad de giro en la evolución de las temperaturas en diversos puntos del satélite, se ha empleado un modelo térmico linealizado, obtenido a partir de la formulación no lineal aplicando un método de perturbaciones. El resultado del estudio muestra que el tiempo de estabilización de la temperatura y la influencia de las cargas periódicas externas disminuye cuando aumenta la velocidad de giro. Los cambios de temperatura se reducen hasta ser muy pequeños para velocidades de rotación altas. En relación con la estrategia PMAC se ha observado que a pesar de su uso extendido entre los micro y nano satélites todavía presenta problemas que resolver. Estos problemas están relacionados con el dimensionamiento de los parámetros del sistema y la predicción del funcionamiento en órbita. Los problemas aparecen debido a la dificultad en la determinación de las características magnéticas de los cuerpos ferromagnéticos (varillas de histéresis) que se utilizan como amortiguadores de oscilaciones en los satélites. Para estudiar este problema se presenta un modelo analítico que permite estimar la eficiencia del amortiguamiento, y que se ha aplicado al estudio del comportamiento en vuelo de varios satélites, y que se ha empleado para comparar los resultados del modelo con los obtenidos en vuelo, observándose que el modelo permite explicar satisfactoriamente el comportamiento registrado. ABSTRACT The main objective of this thesis is to study the coupling between the attitude control and thermal control subsystems of a small satellite, and address the solution to some existing issues concerning the determination of their parameters. Through the thesis the attitude and temperature evolution of the satellite is studied under the influence of two independent attitude stabilization and control strategies: (1) passive magnetic attitude stabilization (PMAS), and (2) active magnetic attitude control (AMAC). In this regard the mathematical model of the problem is explained and presented. The mathematical model includes both the rotational dynamics and the thermal model. The thermal model is derived for a cubic satellite by solving the heat balance equation for 6 external and 1 internal nodes. Once established the mathematical model of the problem, the above mentioned attitude strategies were applied to the system and the temperature evolution of the 7 nodes of the satellite was studied. The PMAS technique has been selected to be studied due to its prevalent use, simplicity, reliability, and cost, as this strategy significantly saves the overall power, weight, cost, and reduces the complexity of the system compared to other attitude control strategies. In addition to that, another control law that provides the satellite with a desired spin rate along a desired axis of the satellite, whose direction can be controlled with respect to the inertial reference frame is considered, as the thermal subsystem of a satellite usually demands a spin requirement around an axis of the satellite which is positioned perpendicular to the direction of the coming solar radiation. Concerning the thermal problem, to study the influence of spin rate on temperature evolution of the satellite a linear approach of the thermal model is used, which is based on perturbation theory applied to the nonlinear differential equations of the thermal model of a spacecraft moving in a closed orbit. The results of this study showed that the temperature stabilization time and the periodic influence of the external thermal loads decreases by increasing the spin rate. However, the changes become insignificant for higher values of spin rate. Concerning the PMAS strategy, it was observed that in spite of its extended application to micro and nano satellites, still there are some issues to be solved regarding this strategy. These issues are related to the sizing of its system parameters and predicting the in-orbit performance. The problems were found to be rooted in the difficulties that exist in determining the magnetic characteristics of the ferromagnetic bodies (hysteresis rods) that are applied as damping devices on-board satellites. To address these issues an analytic model for estimating their damping efficiency is proposed and applied to several existing satellites in order to compare the results with their respective in-flight data. This model can explain the behavior showed by these satellites.
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National Highway Traffic Safety Administration, Washington, D.C.
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Photon counting induces an effective non-linear optical phase shift in certain states derived by linear optics from single photons. Although this non-linearity is non-deterministic, it is sufficient in principle to allow scalable linear optics quantum computation (LOQC). The most obvious way to encode a qubit optically is as a superposition of the vacuum and a single photon in one mode-so-called 'single-rail' logic. Until now this approach was thought to be prohibitively expensive (in resources) compared to 'dual-rail' logic where a qubit is stored by a photon across two modes. Here we attack this problem with real-time feedback control, which can realize a quantum-limited phase measurement on a single mode, as has been recently demonstrated experimentally. We show that with this added measurement resource, the resource requirements for single-rail LOQC are not substantially different from those of dual-rail LOQC. In particular, with adaptive phase measurements an arbitrary qubit state a alpha/0 > + beta/1 > can be prepared deterministically.
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This paper presents results from the first use of neural networks for the real-time feedback control of high temperature plasmas in a Tokamak fusion experiment. The Tokamak is currently the principal experimental device for research into the magnetic confinement approach to controlled fusion. In the Tokamak, hydrogen plasmas, at temperatures of up to 100 Million K, are confined by strong magnetic fields. Accurate control of the position and shape of the plasma boundary requires real-time feedback control of the magnetic field structure on a time-scale of a few tens of microseconds. Software simulations have demonstrated that a neural network approach can give significantly better performance than the linear technique currently used on most Tokamak experiments. The practical application of the neural network approach requires high-speed hardware, for which a fully parallel implementation of the multi-layer perceptron, using a hybrid of digital and analogue technology, has been developed.
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Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via crank shaft However, to ensure efficient and reliable operation under all conditions, it is essential that the motor current of the linear compressor follows a sinusoidal command profile with a frequency which matches the system resonant frequency. This paper describes a hybrid current controller for the linear compressors. It comprises a conventional proportional-integral (PI) controller, and a B-spline neural network compensator which is trained on-line and in real-time in order to minimize the current tracking error under all conditions with uncertain disturbances. It has been shown that the hybrid current controller has a superior steady-state and transient performance over the conventional carrier based PI controller. The performance of the proposed hybrid controller has been demonstrated by extensive simulations and experiments. It has also been shown that the linear compressor operates stably under the current feedback control and the piston stroke can be adjusted by varying the amplitude of the current command. © 2007 IEEE.
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The aim of this paper is to provide an efficient control design technique for discrete-time positive periodic systems. In particular, stability, positivity and periodic invariance of such systems are studied. Moreover, the concept of periodic invariance with respect to a collection of boxes is introduced and investigated with connection to stability. It is shown how such concept can be used for deriving a stabilizing state-feedback control that maintains the positivity of the closed-loop system and respects states and control signals constraints. In addition, all the proposed results can be efficiently solved in terms of linear programming.
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This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs) taking values in a general Borel space and with compact action space depending on the state variable. The control variable acts on the jump rate and transition measure of the PDMP, and the running and boundary costs are assumed to be positive but not necessarily bounded. Our first main result is to obtain an optimality equation for the long run average cost in terms of a discrete-time optimality equation related to the embedded Markov chain given by the postjump location of the PDMP. Our second main result guarantees the existence of a feedback measurable selector for the discrete-time optimality equation by establishing a connection between this equation and an integro-differential equation. Our final main result is to obtain some sufficient conditions for the existence of a solution for a discrete-time optimality inequality and an ordinary optimal feedback control for the long run average cost using the so-called vanishing discount approach. Two examples are presented illustrating the possible applications of the results developed in the paper.
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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.
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We compare two different approaches to the control of the dynamics of a continuously monitored open quantum system. The first is Markovian feedback, as introduced in quantum optics by Wiseman and Milburn [Phys. Rev. Lett. 70, 548 (1993)]. The second is feedback based on an estimate of the system state, developed recently by Doherty and Jacobs [Phys. Rev. A 60, 2700 (1999)]. Here we choose to call it, for brevity, Bayesian feedback. For systems with nonlinear dynamics, we expect these two methods of feedback control to give markedly different results. The simplest possible nonlinear system is a driven and damped two-level atom, so we choose this as our model system. The monitoring is taken to be homodyne detection of the atomic fluorescence, and the control is by modulating the driving. The aim of the feedback in both cases is to stabilize the internal state of the atom as close as possible to an arbitrarily chosen pure state, in the presence of inefficient detection and other forms of decoherence. Our results (obtained without recourse to stochastic simulations) prove that Bayesian feedback is never inferior, and is usually superior, to Markovian feedback. However, it would be far more difficult to implement than Markovian feedback and it loses its superiority when obvious simplifying approximations are made. It is thus not clear which form of feedback would be better in the face of inevitable experimental imperfections.
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The integrated control of nitrate recirculation and external carbon addition in a predenitrification biological wastewater treatment system is studied. The proposed control structure consists of four feedback control loops, which manipulate the nitrate recirculation and the carbon dosage flows in a highly coordinated manner such that the consumption of external carbon is minimised while the nitrate discharge limits (based on both grab and composite samples) are met. The control system requires the measurement of the nitrate concentrations at the end of both the anoxic and the aerobic zones. Distinct from ordinary control systems, which typically minimise the variation in the controlled variables, the proposed control system essentially maximises the diurnal variation of the effluent nitrate concentration and through this maximises the use of influent COD for denitrification, thus minimising the requirement for external carbon source. Simulation studies using a commonly accepted simulation benchmark show that the controlled system consistently achieves the designated effluent quality with minimum costs.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica