Speed-Sensorless Vector Control of a Bearingless Induction Motor With Artificial Neural Network Inverse Speed Observer
TL;DR: In this article, a speed observation scheme using artificial neural network (ANN) inverse method was proposed to effectively reject the influence of speed detection on system stability and precision for a bearingless induction motor.
Abstract: To effectively reject the influence of speed detection on system stability and precision for a bearingless induction motor, this paper proposes a novel speed observation scheme using artificial neural network (ANN) inverse method. The inherent subsystem consisting of speed and torque winding currents is modeled, and then its inversion is implemented by the ANN. The speed is successfully observed via cascading the original subsystem with its inversion. The observed speed is fed back in the speed control loop, and thus, the speed-sensorless vector drive is realized. The effectiveness of this proposed strategy has been demonstrated by experimental results.
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TL;DR: A novel decoupling scheme for a bearingless permanent-magnet synchronous motor (BPMSM) to achieve fast-response and high precision performances and to guarantee the system robustness to the external disturbance and parameter uncertainty is proposed.
Abstract: This paper proposes a novel decoupling scheme for a bearingless permanent-magnet synchronous motor (BPMSM) to achieve fast-response and high precision performances and to guarantee the system robustness to the external disturbance and parameter uncertainty. The proposed control scheme incorporates the neural network inverse (NNI) method and 2-degree-of-freedom (DOF) internal model controllers. By introducing the NNI systems into the original BPMSM system, a decoupled pseudo-linear system can be constituted. Additionally, based on the characteristics of the pseudo-linear system, the 2-DOF internal model control theory is utilized to design extra controllers to improve the robustness of the whole system. Consequently, the proposed control scheme can effectively improve the static and dynamic performances of the BPMSM system, as well as adjust the tracking and disturbance rejection performances independently. The effectiveness of the proposed scheme has been verified by both simulation and experimental results.
192 citations
Cites background from "Speed-Sensorless Vector Control of ..."
...One of the solutions to overcome the shortcoming of magnetic bearings can be bearingless motors [11]....
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TL;DR: Experimental results show that the proposed model can significantly improve the calculation accuracy of core losses of the SSRM, and the accuracy is better than the conventional Epstein frame method.
Abstract: In this paper, a new nonlinear lumped parameter equivalent circuit model is proposed to calculate the core losses of a novel 16/10 segmented rotor switched reluctance motor (SSRM) for belt-driven starter generators. The model investigates the hysteresis, eddy current and anomalous losses by using the method of energy conservation. Four parameters are introduced in the proposed model to consider the effects of saturation and leakage flux in SSRM. They are the incremental leakage inductance, the incremental equivalent winding resistance, the incremental magnetizing inductance, and the incremental equivalent core-loss resistance. This model can overcome the hysteresis effects of winding resistance and leakage inductance on the current, and improve the accuracy of the parameters. To illustrate the advantages of the proposed model, an experiment platform is developed. Experimental results show that the proposed model can significantly improve the calculation accuracy of core losses of the SSRM. The accuracy is better than the conventional Epstein frame method. The proposed core-loss model and analysis method can be applied to other kinds of switched reluctance motors.
132 citations
TL;DR: In this article, a decoupling control scheme for a 4-DOF PMBAMB in a direct-driven spindle system based on the neural network inverse (NNI) and 2-degree-of-freedom (DOF) internal model control method was proposed.
112 citations
TL;DR: A new computing paradigm is presented for evaluation of dynamics of nonlinear prey–predator mathematical model by exploiting the strengths of integrated intelligent mechanism through artificial neural networks, genetic algorithms and interior-point algorithm.
111 citations
TL;DR: The model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives to improve the performance of motor controllers and Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response.
Abstract: This paper presents a compound propulsion system with a high-speed permanent-magnet synchronous motor (PMSM) and two in-wheel motors for electric vehicles (EVs). In this paper, the longitudinal dynamic model of EVs is first presented. Then traction distribution ratio $\alpha $ is introduced to express the traction distribution between the front and the rear axles. Moreover, the function of power consumption concerned with the traction distribution ratio $\alpha $ is established. Therefore, the $\alpha $ that minimizes the power consumption function is selected as the optimal traction distribution ratio. To improve the performance of motor controllers, the model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives. Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response. Finally, experimental comparisons and hardware-in-loop (HiL) tests are presented to verify the MPTC method and the proposed energy allocation method, respectively.
100 citations
Cites background from "Speed-Sensorless Vector Control of ..."
...cascade control loops with several proportional-integral (PI), controllers for speed, position, and torque control [12], [13]....
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References
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01 Jan 1964
TL;DR: The real and complex number system as discussed by the authors is a real number system where the real number is defined by a real function and the complex number is represented by a complex field of functions.
Abstract: Chapter 1: The Real and Complex Number Systems Introduction Ordered Sets Fields The Real Field The Extended Real Number System The Complex Field Euclidean Spaces Appendix Exercises Chapter 2: Basic Topology Finite, Countable, and Uncountable Sets Metric Spaces Compact Sets Perfect Sets Connected Sets Exercises Chapter 3: Numerical Sequences and Series Convergent Sequences Subsequences Cauchy Sequences Upper and Lower Limits Some Special Sequences Series Series of Nonnegative Terms The Number e The Root and Ratio Tests Power Series Summation by Parts Absolute Convergence Addition and Multiplication of Series Rearrangements Exercises Chapter 4: Continuity Limits of Functions Continuous Functions Continuity and Compactness Continuity and Connectedness Discontinuities Monotonic Functions Infinite Limits and Limits at Infinity Exercises Chapter 5: Differentiation The Derivative of a Real Function Mean Value Theorems The Continuity of Derivatives L'Hospital's Rule Derivatives of Higher-Order Taylor's Theorem Differentiation of Vector-valued Functions Exercises Chapter 6: The Riemann-Stieltjes Integral Definition and Existence of the Integral Properties of the Integral Integration and Differentiation Integration of Vector-valued Functions Rectifiable Curves Exercises Chapter 7: Sequences and Series of Functions Discussion of Main Problem Uniform Convergence Uniform Convergence and Continuity Uniform Convergence and Integration Uniform Convergence and Differentiation Equicontinuous Families of Functions The Stone-Weierstrass Theorem Exercises Chapter 8: Some Special Functions Power Series The Exponential and Logarithmic Functions The Trigonometric Functions The Algebraic Completeness of the Complex Field Fourier Series The Gamma Function Exercises Chapter 9: Functions of Several Variables Linear Transformations Differentiation The Contraction Principle The Inverse Function Theorem The Implicit Function Theorem The Rank Theorem Determinants Derivatives of Higher Order Differentiation of Integrals Exercises Chapter 10: Integration of Differential Forms Integration Primitive Mappings Partitions of Unity Change of Variables Differential Forms Simplexes and Chains Stokes' Theorem Closed Forms and Exact Forms Vector Analysis Exercises Chapter 11: The Lebesgue Theory Set Functions Construction of the Lebesgue Measure Measure Spaces Measurable Functions Simple Functions Integration Comparison with the Riemann Integral Integration of Complex Functions Functions of Class L2 Exercises Bibliography List of Special Symbols Index
6,681 citations
Additional excerpts
...According to the inverse function theory [31], under the condition Det(A(x,u)) = 0, the system expressed in (7) is invertible, and based on implicit function theorem, its inversion can be expressed as...
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Book•
29 Dec 1995TL;DR: This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules, as well as methods for training them and their applications to practical problems.
Abstract: This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems. Features Extensive coverage of training methods for both feedforward networks (including multilayer and radial basis networks) and recurrent networks. In addition to conjugate gradient and Levenberg-Marquardt variations of the backpropagation algorithm, the text also covers Bayesian regularization and early stopping, which ensure the generalization ability of trained networks. Associative and competitive networks, including feature maps and learning vector quantization, are explained with simple building blocks. A chapter of practical training tips for function approximation, pattern recognition, clustering and prediction, along with five chapters presenting detailed real-world case studies. Detailed examples and numerous solved problems. Slides and comprehensive demonstration software can be downloaded from hagan.okstate.edu/nnd.html.
6,463 citations
"Speed-Sensorless Vector Control of ..." refers methods in this paper
...The Levenberg–Marquardt algorithm [33] is used in ANN training....
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Book•
01 Jan 1998
TL;DR: This paper presents a space-phasor model of A.C. machines based on artificial intelligence-based steady-state and transient analysis of electrical machines, estimators and investigates the role of magnetic saturation in the control of these machines.
Abstract: 1. Introduction 2. The space-phasor model of A.C. machines 3. Vector and direct torque control of synchronous machines 4. Vector and direct torque control of induction machines 5. Torque control of switched reluctance motors 6. Effects of magnetic saturation 7. Artificial intelligence-based steady-state and transient analysis of electrical machines, estimators 8. Self-commissioning Index
2,343 citations
"Speed-Sensorless Vector Control of ..." refers methods in this paper
...For the conventional induction motors, various techniques have been proposed to estimate speed for sensorless drives, such as the direct computing method [21], Luenberger observers...
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TL;DR: From a direct proof of the universal approximation capabilities of perceptron type networks with two hidden layers, estimates of numbers of hidden units are derived based on properties of the function being approximation and the accuracy of its approximation.
685 citations
"Speed-Sensorless Vector Control of ..." refers methods in this paper
...Taking the Kolmogorov theory [32] and the calculating ability...
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Book•
03 Jun 2005
TL;DR: The application of bearingless drives is emerging as an important technique in the areas of high-speed machinery and motion control, and a thorough grounding in the principles behind this cutting-edge technology is provided in this article.
Abstract: The application of bearingless drives is emerging as an important technique in the areas of high-speed machinery and motion-control, and this book aims to provide a thorough grounding in the principles behind this cutting-edge technology. Basic principles are described in detail with practical examples to aid understanding, and the different types of bearingless drives are introduced, along with coverage of test machines and applications.Aimed at practising electrical and mechanical engineers and advanced students, Magnetic Bearings and Bearingless Drives provides an essential guide to an area of engineering previously only fully covered by large numbers of academic papers. Key Features :
Unique and comprehensive coverage of a cutting-edge subject for electrical and mechanical engineers
A reference text and survey for designers, manufacturers and users of high-speed motors, generators and electrical drive systems
Examines the basic principles behind magnetic bearings, with key technologies and applications illustrated through examples and case studies
464 citations
"Speed-Sensorless Vector Control of ..." refers background in this paper
...ies, machine tool spindles, vacuum pumps, blood pumps, computer disk drives, energy storage flywheels, etc [9]–[11]....
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