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Lyapunov Theory (lyapunov + theory)

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Engineering	100%

Selected Abstracts

A robust air-gap flux estimation for speed sensorless vector control of double-star induction machine

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2004
M.F. Mimouni
Abstract The paper presents a new direct field-oriented control (DFOC) for double-star induction machine (DSIM) drives using the stator currents. First, we propose a new algorithm to estimate air-gap flux for speed sensorless air-gap flux orientation control. Compared to the previous DFOC schemes the new one is independent from any motor parameter variation, specially on the stator resistance. Then, the DFOC is associated with a low pass filter (LPF) to solve the dc drift problems caused by the pure integration of air-gap flux. In the present paper, the rotor resistance is estimated by an algorithm using Lyapunov theory. Good results have been obtained in the benchmark simulations. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Modelling and simulation of a double-star induction machine vector control using copper-losses minimization and parameters estimation

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 9 2002
M.F. Mimouni
Abstract This paper shows that it is possible to extend the principle of field-oriented control (FOC) approach to a double-star induction motor (DSIM). In the first stage, a robust variable structure current controller based on space phasor voltages PWM scheme is established. In this current controller design, only the stator currents and rotor speed sensors are used. In the second stage, the FOC method developed for DSIM is motivated by the minimization of the copper losses. The developed approach uses a loss model controller (LMC) and an adaptive rotor flux observer to compute the adequate rotor flux value minimizing the copper losses. The control variables are the stator currents or the machine input power. Compared to the constant rotor flux approach, it is proved that higher performances are achieved. However, the sensitivity of the FOC to parameter error of the machine still remains a problem. To guarantee the performance of the vector control, the stator and rotor resistances are adapted on-line, based on the Lyapunov theory. An appropriate choice of the reference model allows building a Lyapunov function by means of which the updating law can be found. The simulation results show the satisfactory behaviour of the proposed identification algorithm. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Nonsingular path following control of a unicycle in the presence of parametric modelling uncertainties

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 10 2006
L. Lapierre
Abstract A new type of control law is derived to steer the dynamic model of a wheeled robot of unicycle type along a desired path. The methodology adopted for path following control deals explicitly with vehicle dynamics and plant parameter uncertainty. Furthermore, it overcomes stringent initial condition constraints that are present in a number of path following control strategies described in the literature. This is done by controlling explicitly the rate of progression of a ,virtual target' to be tracked along the path, thus bypassing the problems that arise when the position of the virtual target is simply defined by the projection of the actual vehicle on that path. In the paper, a nonlinear adaptive control law is derived that yields convergence of the (closed-loop system) path following error trajectories to zero. Controller design relies on Lyapunov theory and backstepping techniques. Simulation results illustrate the performance of the control system proposed. Copyright © 2006 John Wiley & Sons, Ltd. [source]

New IQC for quasi-concave nonlinearities

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 7 2001
Alexandre Megretski
Abstract A new set of integral quadratic constraints (IQC) is derived for a class of ,rate limiters', modelled as a series connections of saturation-like memoryless nonlinearities followed by integrators. The result, when used within the standard IQC framework (in particular, with finite gain/passivity-based argiments, Lyapunov theory, structured singular values, etc.), is expected to be widely useful in nonlinear system analysis. For example, it enables ,discrimination' between ,saturation-like' and ,deadzone-like' nonlinearities and can be used to prove stability of systems with saturation in cases when replacing the saturation block by another memoryless nonlinearity with equivalent slope restrictions makes the whole system unstable. In particular, it is shown that the L2 gain of a unity feedback system with a rate limiter in the forward loop cannot exceed \sqrt{2}. In addition, a new, more flexible version of the general IQC analysis framework is presented, which relaxes the homotopy and boundedness conditions, and is more aligned with the language of the emerging IQC software. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Neural network-based adaptive attitude tracking control for flexible spacecraft with unknown high-frequency gain

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2010
Qinglei Hu
Abstract Adaptive control design using neural networks (a) is investigated for attitude tracking and vibration stabilization of a flexible spacecraft, which is operated at highly nonlinear dynamic regimes. The spacecraft considered consists of a rigid body and two flexible appendages, and it is assumed that the system parameters are unknown and the truncated model of the spacecraft has finite but arbitrary dimension as well, for the purpose of design. Based on this nonlinear model, the derivation of an adaptive control law using neural networks (NNs) is treated, when the dynamics of unstructured and state-dependent nonlinear function are completely unknown. A radial basis function network that is used here for synthesizing the controller and adaptive mechanisms is derived for adjusting the parameters of the network and estimating the unknown parameters. In this derivation, the Nussbaum gain technique is also employed to relax the sign assumption for the high-frequency gain for the neural adaptive control. Moreover, systematic design procedure is developed for the synthesis of adaptive NN tracking control with L2 -gain performance. The resulting closed-loop system is proven to be globally stable by Lyapunov's theory and the effect of the external disturbances and elastic vibrations on the tracking error can be attenuated to the prescribed level by appropriately choosing the design parameters. Numerical simulations are performed to show that attitude tracking control and vibration suppression are accomplished in spite of the presence of disturbance torque/parameter uncertainty. Copyright © 2009 John Wiley & Sons, Ltd. [source]