Hossam A. Abdel Fattah

Adaptive Fuzzy Control of the Inverted Pendulum Problem

In this brief, we address adaptive fuzzy control of the inverted-pendulum on a cart problem as an underactuated mechanical system. Many of the schemes presented in the adaptive fuzzy control literature tackle the problem as a second-order system based on feedback linearization. Such schemes render unstable zero dynamics for the cart-pole systems which hinders experimental implementation. The paradigm presented is also based on a feedback linearizing (FBL) scheme, yet it ensures system stabilization. A damping term and an adaptive fuzzy control term are added to guarantee asymptotic stability and to account for disturbances. Experimental results illustrate the success of the proposed controller in stabilization and cart-position tracking of a reference trajectory

Non-linear adaptive sliding mode observer-controller scheme for induction motors

An adaptive non-linear observer-based controller is designed for a full model of an induction motor including both electrical and mechanical dynamics. The controller is designed primarily for speed control and is then modified to address position control. Without flux measurement, the controller has the ability to adapt to changes in rotor resistance and load parameters. Considering that the separation principle does not hold for general classes of non-linear systems, an adaptive observer is first developed to accommodate rotor resistance and load parameter variations. A non-linear feedback control law, that uses the state estimates from the adaptive observer to steer the estimated speed (position) and flux magnitude to the desired trajectories, is then designed. The basic idea is to use a singularly perturbed model to design a sliding mode observer. Estimated stator currents converge to their true values in the fast time scale and an adaptive flux observer on the sliding surface is developed using the equivalent switching vector. The adaptive scheme guarantees that both the estimated fluxes and the estimated rotor resistance converge to their true values. Because the observer design is independent of the control, closed-loop stability can be guaranteed. Moreover, because the adaptive observer system is typically a singularly perturbed system that can be decomposed into slow and fast dynamics, controllers are designed for both of these two subsystems. The fast dynamics are stabilized by a linear feedback law while an input–output decoupling and linearizing control scheme is designed for the slow dynamics, based on non-linear geometric control theory. Finally, simulation results confirm the theoretical results and exhibit good performance when applied to the benchmark problems suggested by Ortega et al. (Call for paper for special issue of International Journal of Adaptive Control and Signal Processing). Copyright

Input-output linearization of induction motors with magnetic saturation

The problem of controlling induction motors with magnetic saturation is addressed from an input-output feedback linearization perspective. The induction motor /spl pi/-model is considered. A input-output feedback linearizing controller is developed under the assumption of known motor parameters and measurable rotor flux. Simulation results are provided for illustration.

Brief Passivity-based torque and flux tracking for induction motors with magnetic saturation

An observer-based, globally asymptotically stable torque and rotor flux magnitude tracking controller for induction motors under magnetic saturation is proposed. The controller is synthesized using the passivity-based techniques. The paper considers a magnetically saturated @p-model of the motor without any simplifying assumptions. Motor fluxes are reconstructed by a closed-loop observer. Closed-loop stability of the overall scheme including the observer is demonstrated. Simulation results are given to illustrate the proposed scheme.

Particle Swarm Optimized Direct Torque Control of Induction Motors

The flux and torque hysteresis bands are the only adjustable parameters in direct torque control (DTC) of induction motors. Their selection greatly influences the inverter switching loss, motor harmonic loss and motor torque ripples, which are major performance criteria. In this paper, the effects of flux and torque hysteresis bands on these criteria are investigated and optimized via the minimization, by the particle swarms optimization (PSO) technique, of a suitably selected cost function. A DTC control strategy with variable hysteresis bands, which improves the drive performance compared to the classical DTC, is proposed. Online operating artificial neural networks (ANNs) use the offline optimum values obtained by PSO, to modify the hysteresis bands in order to improve the performance. The implementation of the proposed scheme is illustrated by simulation results

Passivity-based torque and flux tracking for induction motors with magnetic saturation

An observer-based, globally asymptotically stable torque and rotor flux magnitude tracking controller for induction motors under magnetic saturation is proposed. Simulation results are provided.

Variable structure flux linkage controller for torque ripple minimization in switched reluctance motors

A variable structure based flux linkage controller scheme, which takes into account the limitations imposed by the finite DC-link voltage and rotor speed when calculating the reference flux values, is proposed. Correct selection of the flux reference parameters nearly allows the achievement of constant torque operation over wide speed and torque ranges. In order to use the controller described a current gauge curve model is developed, based on an idea similar to the flux linkage gauge curve model of Stiebler and Ke-Liu (1999). Simulation results illustrate that the proposed approach provides lower torque ripples than other existing techniques.

Stochastic tracking controller for maximum power point tracking in wind energy conversion system

This paper discusses the rotor speed tracking loop configuration in maximum power point tracking (MPPT) in wind energy conversion system (WECS). A new loop configuration is proposed in which the aerodynamic torque is treated as an external disturbance. Internal model control and minimum variance control are used to achieve full disturbance rejection and exact reference tracking. Provided simulation results compare the performance of the proposed controller and the traditional (PI) controller with different wind profiles and reference speed trajectory patterns. A tradeoff between tracking performance and overall wind farm power quality is discussed and a solution is proposed.

Numerical optimization algorithm for Maximum Power Point Tracking in wind Energy Conversion System

This paper proposes a line search numerical algorithm for Maximum Power Point Tracking (MPPT) in Wind Energy Conversion Systems (WECS). The algorithm maximizes the captured power objective function constructed via a mechanical acceleration estimator with no wind speed measurement necessary. Simulation results are included with varying wind profile, speed and air density to compare the proposed algorithm with the common kω2 feedback controller.

Adaptive Output Feedback Voltage-Based Control of Magnetically-Saturated Induction Motors

The problem of controlling the induction motor -model with magnetic saturation is considered. An adaptive controller is developed under the assumption of measurable stator currents and speed only with unknown rotor resistance and load torque. All the unknown parameters are assumed constant or slowly varying and are estimated online by the controller. Simulation results are provided for illustration.