Carlos García‐Rodríguez

On the Control of the Permanent Magnet Synchronous Motor: An Active Disturbance Rejection Control Approach

This brief presents an active disturbance rejection control scheme for the angular velocity trajectory tracking task on a substantially perturbed, uncertain, and permanent magnet synchronous motor. The presence of unknown, time varying, and load-torque inputs, unknown system parameters, and the lack of knowledge of the initial shafts angular position, prompts a high-gain generalized proportional integral (GPI) observer-based active disturbance rejection (ADR) controller. This controller is synthesized on the basis of the differential flatness of the system and the direct measurability of the systems flat outputs, constituted by the motors angular displacement and the d-axis current. As a departure from many previous treatments, the d-q-axis currents model is here computed on the basis of the measured displacement and not on the basis of the unknown position. The proposed high-gain GPI observer-based ADR controller is justified in terms of a singular perturbation approach. The validity and robustness of the scheme are verified by means of realistic computer simulations, using the MATLAB/SIMULINK-PSIM package.

Robust Nonlinear Adaptive Control of a “Boost” Converter via Algebraic Parameter Identification

This paper presents the design of a robust nonlinear adaptive controller for trajectory tracking maneuvers of the nonminimum phase output voltage on a dc-to-dc “boost” power converter with uncertain time-varying parameters. The unknown parameter variations concern both the resistive load and the input voltage supply value. A generalized proportional-integral (GPI) indirect control, exploiting the flatness property of the system, performs fast adaptations on the feedback controller and on the desired output reference trajectory owing to a fast online algebraic parameter identification procedure. The required updating of the algebraic parameter identification process is periodically triggered to cope with the time variations of the unknown plant parameters. The proposed control scheme is shown to be quite effective for handling the significant plant uncertainties when tested through experiments on a laboratory prototype. An adaptive linear quadratic regulator optimal control based on feedback linearization was designed in order to compare its performance against that of the proposed GPI adaptive scheme. An integral square error index was used for the evaluation.

Algebraic Identification and Estimation Methods in Feedback Control Systems: Sira-Ramírez/Algebraic Identification and Estimation Methods in Feedback Control Systems

Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology.Key features:Presents a radically new approach to online parameter and state estimation.Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.Includes examples in a variety of physical applications with experimental results.Covers the latest developments and applications.Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.

Robust Backstepping Tracking Controller for Low-Speed PMSM Positioning System: Design, Analysis, and Implementation

This article is concerned with the design and implementation of a robust position trajectory tracking controller for a permanent magnet synchronous motor (PMSM). The information on the angular position, provided by a classical resolver, is here complemented with an observer based phase lock loop (PLL) circuit which accurately renders the position and the angular velocity of the rotor. A Backstepping control law is designed from the input-output linearization of the PMSM model, written in d-q coordinates. This controller is adapted through a load torque and friction reduced order observer to ensure high closed loop performance of the motor. An input-state stability analysis of the entire system is also provided. Co-simulation via the MATLAB/Simulink-PSIM package, including realistic measurement disturbances, are used to investigate the stability and accuracy of the proposed control algorithm. The simulation results are examined and confirmed through laboratory experiments.

Algebraic Identification and Discontinuous Control for Trajectory Tracking in a Perturbed 1-DOF Suspension System

This paper deals with the output feedback control and simultaneous online algebraic identification of an unknown perturbed 1-DOF suspension system. An algebraic identifier, which is known to be of unstable nature, is provided with an automatic disconnection strategy. The automatic disconnection is achieved by assessing an extra auxiliary parameter, called the ldquosentinelrdquo parameter that monitors the convergence of the rest of the estimated system parameters. The estimated values of mass, stiffness, and damping are realized via an algebraic estimator, with great rapidity and robustness to noise process signals present in the input and output signals. A generalized proportional integral controller was designed for a trajectory tracking task and the rejection of a constant disturbance input. The switched implementation of the average input in the form of a bounded discontinuous control signal is based on the use of a Sigma- Delta modulator. In an average sense, this modulation allows us to preserve the desirable features of the dynamic output feedback controller and to be close to a real implementation. The efficiency of the complete procedure is demonstrated via digital computer simulations.

Algebraic parameter identification for induction motors

In this article, we propose a fast, on-line, algebraic identification scheme for the determination of some relevant induction motor parameters. The estimated values, given by the algebraic identification methodology, are here tested in a self-tuning output feedback control, subject to constant perturbation load torques while solving a reference trajectory tracking task. An output feedback controller of the classical, Field Oriented, Proportional Integral (PI) type, is proposed for the perturbed output trajectory tracking problem. Experimental results validate the effectiveness of the proposed approach.

An algebraic denoising scheme

In this paper, the noise filtering problem (¿de-noising¿ problem) is approached via a suitable modification of the traditional Luenberger observer approach, also known as the ¿high gain observer¿ approach (HGO). The HGO observer is, fundamentally, a Luenberger observer with large stable eigenvalues of the output estimation error dynamics. HGO and some of its modifications have been particularly useful in the linear based control of perturbed linear and nonlinear systems. HGO are, however, inappropriate to deal with noisy injection signals and noisy plants. To overcome this fact, the structure of the Luenberger state estimator reconstructing the time derivatives of the given signal is enhanced against the effects of noise by means of an algebraic filtering scheme. The algebraic filtering consists in a suitable modification of the introduced algebraic parameter identification methodology. The proposed approach is capable of attenuating the noise effects significantly. The proposed strategy is illustrated via numerical simulations.

Robust backstepping tracking controller for low speed PMSM positioning system: Design, analysis, and implementation

This article is concerned with the design and implementation of a robust position trajectory tracking controller for a permanent magnet synchronous motor (PMSM). The information on the angular position, provided by a classical resolver, is here complemented with an observer based phase lock loop (PLL) circuit which accurately renders the position and the angular velocity of the rotor. A Backstepping control law is designed from the input-output linearization of the PMSM model, written in d-q coordinates. This controller is adapted through a load torque and friction reduced order observer to ensure high closed loop performance of the motor. An input-state stability analysis of the entire system is also provided. Co-simulation via the MATLAB/Simulink-PSIM package, including realistic measurement disturbances, are used to investigate the stability and accuracy of the proposed control algorithm. The simulation results are examined and confirmed through laboratory experiments.

Robust control of a rotational system via on-line inertia identification

The present work deals with the simultaneous control and identification of a rotational mechanical system constituted by a tandem connection of disks and rotational springs. We consider the rotational system to be controlled as constituted by the first disk alone. This is to be modeled by a simple second order controlled dynamics affected by unknown perturbations arising from the cascade attachment of similar disks and springs in an unknown quantity and of unknown inertia values. The only involved parameter in the robust perturbation rejection controller design is, then, the moment of inertia of the first disk, which is also assumed to be unknown. The on-line disk inertia identification process is carried out using the recently introduced algebraic identification technique. The online identification is achieved using exponential modulation functions, instead of the traditional convolutions with suitable powers of the time variable. The control law is a robust generalized proportional integral controller which regards the unknown part of the dynamics as a locally bounded, self updating, polynomial perturbation. The feasibility of this scheme is shown through numerical simulations as well as laboratory experimental results.

Design and construction of a passive mechanism for emulation of load forces in an electric power steering system

This article presents the design and construction of a mechanism for emulating load forces caused by the road conditions and friction over an electric power assisted steering (EPAS). This mechanism uses extension springs and a rack-and-pinion mechanism to emulate these load forces. The purpose of devising this mechanism is to build an EPAS system test bench, that allows observing and testing the operation steering system in load conditions.