Adaptive input-output linearizing control of induction motors
TL;DR: A nonlinear adaptive state feedback input-output linearizing control is designed for a fifth-order model of an induction motor which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits.
Abstract: A nonlinear adaptive state feedback input-output linearizing control is designed for a fifth-order model of an induction motor which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The control algorithm contains a nonlinear identification scheme which asymptotically tracks the true values of the load torque and rotor resistance which are assumed to be constant but unknown. Once those parameters are identified, the two control goals of regulating rotor speed and rotor flux amplitude are decoupled, so that power efficiency can be improved without affecting speed regulation. Full state measurements are required. >
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01 Nov 2000
TL;DR: A controller is proposed for the robust backstepping control of a class of general nonlinear systems using neural networks (NNs) and can guarantee the boundedness of tracking error and weight updates.
Abstract: A controller is proposed for the robust backstepping control of a class of general nonlinear systems using neural networks (NNs). A tuning scheme is proposed which can guarantee the boundedness of tracking error and weight updates. Compared with adaptive backstepping control schemes, we do not require the unknown parameters to be linear parametrizable. No regression matrices are needed, so no preliminary dynamical analysis is needed. One salient feature of our NN approach is that there is no need for the off-line learning phase. Three nonlinear systems, including a one-link robot, an induction motor, and a rigid-link flexible-joint robot, were used to demonstrate the effectiveness of the proposed scheme.
418 citations
TL;DR: A nonlinear model for magnetic levitation systems which is validated with experimental measurements and a real-time implementation of this model based on differential geometry is developed.
Abstract: In this paper, the authors propose a nonlinear model for magnetic levitation systems which is validated with experimental measurements. Using this model, a nonlinear control law based on differential geometry is firstly synthesized. Then, its real-time implementation is developed. In order to highlight the performance of the proposed control law, experimental results are given.
285 citations
Cites methods from "Adaptive input-output linearizing c..."
...This approach, which has been successfully applied to many nonlinear system controls [6]‐[8], [ 11 ], was first developed in the effort of designing an autopilot for helicopters [12] . It requires measurements of the state vector in order to transform the nonlinear system into a linear and controllable one by means of the nonlinear state feedback and the nonlinear state-space change of coordinates....
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08 Oct 2000
TL;DR: In this article, an adaptive backstepping technique for an interior permanent-magnet synchronous motor (IPMSM) drive based on newly developed adaptive back stepping technique is presented.
Abstract: This paper presents a novel speed control technique for an interior permanent-magnet synchronous motor (IPMSM) drive based on newly developed adaptive backstepping technique. The proposed stabilizing feedback law for the IPMSM drive is shown to be globally asymptotically stable in the context of Lyapunov theory. The adaptive backstepping technique takes system nonlinearities into account in the control system design stage. The detailed derivations of the control laws have been given for controller design. The complete IPMSM drive incorporating the proposed backstepping control technique has been successfully implemented in real-time using digital signal processor board DS1102 for a laboratory 1-hp motor. The performance of the proposed drive is investigated both in experiment and simulation at different operating conditions. It is found that the proposed control technique provides a good speed tracking performance for the IPMSM drive ensuring the global stability.
284 citations
TL;DR: The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive.
Abstract: This paper presents a new method of online estimation for the stator and rotor resistances of the induction motor for speed sensorless indirect vector controlled drives, using artificial neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The rotor speed is synthesized from the induction motor state equations. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations for variations in the stator and rotor resistances from their nominal values. Both resistances are estimated experimentally, using the proposed neural network in a vector controlled induction motor drive. Data on tracking performances of these estimators are presented. With this speed sensorless approach, the rotor resistance estimation was made insensitive to the stator resistance variations both in simulation and experiment. The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive
265 citations
Cites background from "Adaptive input-output linearizing c..."
...The second approach, developed in [9] and [10], was to compensate for rotor resistance variation by adaptive feedback linearization control with unknown rotor resistance....
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TL;DR: In this article, a current-command input-output linearization controller was proposed to achieve high performance motion control, that is, the precise tracking of a fast point-to-point position reference.
Abstract: We have shown that a current-command input-output linearization controller can achieve high-performance motion control, that is, the precise tracking of a fast point-to-point position reference. Specifically, this controller was shown to provide the means of decoupling the speed and flux dynamics in an induction motor. This decoupling of speed and flux was exploited to simultaneously track the position/speed reference and an optimal flux reference. This flux reference was used to obtain the optimal (max/min) motor torque at any given speed without violating voltage and current limits. Experimental results were presented to demonstrate the effectiveness of this scheme. >
260 citations
References
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Book•
09 Mar 1990
TL;DR: In this paper, the authors describe the motion of a drive with Lumped Inertia and two Axes Drive in Polar Coordinates, and the integration of the simplified Equation of Motion.
Abstract: 1. Elementary Principles of Mechanics.- 1.1 Newtons Law.- 1.2 Moment of Inertia.- 1.3 Effect of Gearing.- 1.4 Power and Energy.- 1.5 Experimental Determination of Inertia.- 2. Dynamics of a Mechanical Drive.- 2.1 Equations Describing the Motion of a Drive with Lumped Inertia.- 2.2 Two Axes Drive in Polar Coordinates.- 2.3 Steady State Characteristics of Motors and Loads.- 2.4 Stable and Unstable Operating Points.- 3. Integration of the Simplified Equation of Motion.- 3.1 Solution of the Linearised Equation.- 3.1.1 Start of a Motor with Shunt-type Characteristic at No-load.- 3.1.2 Starting the Motor with a Load Torque Proportional to Speed.- 3.1.3 Loading Transient of the Motor Initially Running at No-load Speed.- 3.1.4 Starting of a DC Motor by Sequentially Short-circuiting Starting Resistors.- 3.2 Analytical Solution of Nonlinear Differential Equation.- 3.3 Numerical and Graphical Integration.- 4. Thermal Effects in Electrical Machines.- 4.1 Power Losses and Temperature Restrictions.- 4.2 Heating of a Homogeneous Body.- 4.3 Different Modes of Operation.- 4.3.1 Continuous Duty.- 4.3.2 Short Time Intermittent Duty.- 4.3.3 Periodic intermittent duty.- 5. Separately Excited DC Machine.- 5.1 Introduction.- 5.2 Mathematical Model of the DC Machine.- 5.3 Steady State Characteristics with Armature and Field Control.- 5.3.1 Armature Control.- 5.3.2 Field Control.- 5.3.3 Combined Armature and Field Control.- 5.4 Dynamic Behaviour of DC Motor with Constant Flux.- 6. DC Motor with Series Field Winding.- 6.1 Block Diagram of a Series-wound Motor.- 6.2 Steady State Characteristics.- 7. Control of a Separately Excited DC Machine.- 7.1 Introduction.- 7.2 Cascade Control of DC Motor in the Armature Control Region.- 7.3 Cascade Control of DC Motor in the Field-weakening Region.- 7.4 Supplying a DC Motor from a Rotating Generator.- 8. Static Converter as a Power Actuator for DC Drives.- 8.1 Electronic Switching Devices.- 8.2 Line-commutated Converter in Single-phase Bridge Connection.- 8.3 Line-commutated Converter in Three-phase Bridge Connection.- 8.4 Line-commutated Converters with Reduced Reactive Power.- 8.5 Control Loop Containing an Electronic Power Converter.- 9. Control of Converter-supplied DC Drives.- 9.1 DC Drive with Line-commutated Converter.- 9.2 DC Drives with Force-commutated Converters.- 10. Symmetrical Three-Phase AC Machines.- 10.1 Mathematical Model of a General AC Machine.- 10.2 Induction Motor with Sinusoidal Symmetrical Voltages in Steady State.- 10.2.1 Stator Current, Current Locus.- 10.2.2 Steady State Torque, Efficiency.- 10.2.3 Comparison with Practical Motor Designs.- 10.2.4 Starting of the Induction Motor.- 10.3 Induction Motor with Impressed Voltages of Arbitrary Wave- forms.- 10.4 Induction Motor with Unsymmetrical Line Voltages in Steady State.- 10.4.1 Symmetrical Components.- 10.4.2 Single-phase Induction Motor.- 10.4.3 Single-phase Electric Brake for AC Crane-Drives.- 10.4.4 Unsymmetrical Starting Circuit for Induction Motor.- 11. Power Supplies for Adjustable Speed AC Drives.- 11.1 Pulse width modulated (PWM) Voltage Source Transistor Converter (IGBT).- 11.2 Voltage Source PWM Thyristor Converter.- 11.3 Current Source Thyristor Converters.- 11.4 Converter Without DC Link (Cycloconverter).- 12. Control of Induction Motor Drives.- 12.1 Control of Induction Motor Based on Steady State Machine Model.- 12.2 Rotor Flux Orientated Control of Current-fed Induction Motor.- 12.2.1 Principle of Field Orientation.- 12.2.2 Acquisition of Flux Signals.- 12.2.3 Effects of Residual Lag of the Current Control Loops.- 12.2.4 Digital Signal Processing.- 12.2.5 Experimental Results.- 12.2.6 Effects of a Detuned Flux Model.- 12.3 Control of Voltage-fed Induction Motor.- 12.4 Field Orientated Control of Induction Motor with a Current Source Converter.- 12.5 Control of an Induction Motor Without a Mechanical Sensor.- 12.5.1 Machine Model in Stator Flux Coordinates.- 12.5.2 Example of an "Encoderless Control".- 12.5.3 Simulation and Experimental Results.- 12.6 Control of an Induction Motor Using a Combined Flux Model.- 13. Induction Motor Drive with Reduced Speed Range.- 13.1 Doubly-fed Induction Machine with Constant Stator Frequency and Field-orientated Rotor Current.- 13.2 Control of a Line-side Voltage Source Converter as a Reactive Power Compensator.- 13.3 Wound-Rotor Induction with Slip-Power Recovery.- 14. Variable Frequency Synchronous Motor Drives.- 14.1 Control of Synchronous Motors with PM Excitation.- 14.2 Synchronous Motor with Field- and Damper-Windings.- 14.3 Synchronous Motor with Load-commutated Inverter (LCI- Drive).- 15. Some Applications of Controlled Electrical Drives.- 15.1 Speed Controlled Drives.- 15.2 Lineax Position Control.- 15.3 Lineax Position Control with Moving Reference Point.- 15.4 Time-optimal Position Control with Fixed Reference Point.- 15.5 Time-optimal Position Control with Moving Reference Point.
2,882 citations
Book•
06 Apr 1990TL;DR: The controlled Invariant Submanifolds and Nonlinear Zero Dynamics and the Disturbance Decoupling problem are studied.
Abstract: Contents: Introduction.- Manifolds, Vectorfields, Lie Brackets, Distributions.- Controllability and Observability, Local Decompositions.- Input-Output Representations.- State Space Transformation and Feedback.- Feedback Linearization of Nonlinear Systems.- Controlled Invariant Distribution and the Disturbance Decoupling Problem.- The Input-Output Decoupling Problem: Geometric Considerations.- Local Stability and Stabilization of Nonlinear Systems.- Controlled Invariant Submanifolds and Nonlinear Zero Dynamics.- Mechanical Nonlinear Control Systems.- Controlled Invariance and Decoupling for General Nonlinear Systems.- Discrete-Time Nonlinear Control Systems.- Subject Index.
2,573 citations
TL;DR: A systematic procedure for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems is developed, which substantially enlarges the class of non linear systems with unknown parameters for which global stabilization can be achieved.
Abstract: A systematic procedure for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems is developed. The coordinate-free geometric conditions, which characterize this class of systems, do not constrain the growth of the nonlinearities. Instead, they require that the nonlinear system be transformable into the so-called parametric-pure feedback form. When this form is strict, the proposed scheme guarantees global regulation and tracking properties, and substantially enlarges the class of nonlinear systems with unknown parameters for which global stabilization can be achieved. The main results use simple analytical tools, familiar to most control engineers. >
1,722 citations
26 Jun 1991
TL;DR: In this paper, a systematic procedure is developed for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems, which are transformable into the so-called pure-feedback form.
Abstract: A systematic procedure is developed for the design of new adaptive regulation and trackdng schemes for a class of feedback linearizable nonlinear systems. The coordinate-free geometric conditions, which characterize this class of systems, neither restrict the location of the unknown parameters, nor constrain the growth of the nonlinearities. Instead, they require that the nonlinear system be transformable into the so-called pure-feedback form. When this form is "strict", the proposed scheme guarantees global regulation and tracking properties, and substantially enlarges the class of nonlinear systems with unknown parameters for which global stabilization can be achieved. The main results of this paper use simple analytical tools, familiar to most control engineers.
1,517 citations
TL;DR: In this paper, the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback is discussed. But the application of the adaptive technique to control of robot manipulators is discussed only in the continuous-time case.
Abstract: The authors give some initial results on the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious. >
1,182 citations