C. Ham

A Highly Efficient 200 000 RPM Permanent Magnet Motor System

This paper presents the development of an ultra-high-speed permanent magnet synchronous motor (PMSM) that produces output shaft power of 2000 W at 200 000 rpm with around 90% efficiency. Due to the guaranteed open-loop stability over the full operating speed range, the developed motor system is compact and low cost since it can avoid the design complexity of a closed-loop controller. This paper introduces the collaborative design approach of the motor system in order to ensure both performance requirements and stability over the full operating speed range. The actual implementation of the motor system is then discussed. Finally, computer simulation and experimental results are provided to validate the proposed design and its effectiveness

Brief Nonlinear learning control for a class of nonlinear systems

Based on the Lyapunovs direct method, a new learning control design is proposed. The proposed technique can be applied in two ways: it is either the standard backward recursive design or its extension. In the first case, the design yields a class of learning control with a difference learning law, under which the class of nonlinear systems is guaranteed to be asymptotically stable with respect to the number of trials in performing repeated tasks. However, implementation of the difference learning control requires derivative measurement of the state for guaranteed stability and performance, as required by most of the existing linear learning control laws. To overcome this difficulty, the proposed design extends the recursive design by employing a new state transformation and a new Lyapunov function, and it yields a class of learning control with a difference-differential learning law. Compared with the existing design methods most of which are based on linear analysis and design, the extension not only guarantees global stability and good performance but also removes such limitations as derivative measurement, Lipschitz condition, and resetting of initial conditions. In addition, the proposed design does not rely on the property of a system under consideration such as the input-output passivity.

Design of a superhigh-speed cryogenic permanent magnet synchronous motor

This paper presents the design and simulation of a superhigh-speed permanent magnet synchronous motor (PMSM) that operates in the cryogenic temperature of 77 K. The designed PMSM is used to drive a two-stage cryocooler for zero boil-off and long duration storage of liquid hydrogen systems. The paper addresses electromagnetic and thermal finite-element analysis, selection of materials for cryogenic applications, stress analysis, rotor dynamic analysis, and some tradeoffs used in the design. A prototype PMSM was built to verify the design methodology.

Design of a super-high speed permanent magnet synchronous motor for cryogenic applications

This paper gives the design and simulation of a permanent magnet synchronous motor (PMSM) for a super-high speed centrifugal compressor drive application. The PMSM has an output power of 2000 W at 200,000 rpm with 28 V dc power supply. It is designed for operation at a cryogenic temperature of 77 K. The designed PMSM is a 2-pole, 3-phase slotless structure. The permanent magnet is centrally located inside the hollow shaft. Multi-strand twisted Litz-wire is used to reduce eddy current loss in the winding. The criteria of selecting materials for the super-high speed and cryogenic application are presented. Possible structures of the rotor and stator are considered and simulated using finite element method (FEM). Mechanical stress simulation and rotor dynamic issues are also considered. The connections of low pass filters to reduce switching harmonics of pulse-width modulation (PWM) and to reduce circulating current are also discussed. The first prototype has been fabricated and tested at room temperature. Projected total efficiency of the motor is over 90%

Analysis and Test of a High-Speed Axial Flux Permanent Magnet Synchronous Motor

This paper gives the analysis and test of a surface mounted axial flux permanent magnet synchronous motor (PMSM) for a high-speed centrifugal compressor drive. Both analytical analysis and 3-D electromagnetic finite element method (FEM) are used to calculate flux density in the airgap, rotor back iron, and stator iron. 3-D FEM is used to simulate the electromotive force (back EMF) and torque. The motor has been tested up to 87,000 rpm using an open-loop controller. The advantages and disadvantages of this kind of structure are analyzed, and some improvements of this design are also considered and partially verified by experiments

Design of an optimal V/f control for a super high speed permanent magnet synchronous motor

In this paper, a new design approach of an optimal V/f control for a super high speed permanent magnet synchronous motor (PMSM) is presented. The stator resistance of PMSM is generally neglected in design of a V/f control and compensated only by a boost voltage. However, due to the extra small size requirement of the proposed super high speed PMSM, stator resistance cannot be neglected any more. In this paper, the optimal design of a V/f control curve with consideration of the stator resistance is provided. The effect of the stator resistor to the V/f control curve is analyzed, it enables utilization of a simple and easy V/f control curve for an open-loop control of the super high speed PMSM. Simulation results are illustrated to show the effectiveness of the proposed design technique.

A new framework of learning control for a class of nonlinear systems

This paper illustrates a new nonlinear learning control design based on Lyapunovs direct method. The design is applicable to the class of nonlinear systems consisting of finite cascaded subsystems in performing repeated tasks. A class of difference or difference-differential learning laws is proposed. It is shown that, under a difference learning control, the class of nonlinear systems is guaranteed to be asymptotically stable with respect to the number of trials. For better rejection of measurement noise, the difference-differential learning law can be applied to yield arbitrarily good accuracy. The proposed approach provides closed-form expressions of learning controls, and it gives the designer much flexibility in choosing various combinations of feedforward and learning control parts.

A DSP-based super high-speed PMSM controller development and optimization

The paper presents the design and implementation of a DSP-based controller for super high-speed (up to 200,000 rpm) permanent magnet synchronous motor (PMSM). Constant V/f control and space vector pulse width modulation (SVPWM) are realized by DSP software. The open-loop control scheme is employed because of its simplicity and advantage to high speed. When we design the V/f control for the super high-speed motor, due to the extra small size requirement of the proposed super high speed PMSM, stator resistance cannot be neglected anymore. An optimal design approach to the V/f control curve with consideration of the stator resistance is developed. Experimental results are presented and validate the effectiveness of the DSP-based controller at super high-speed.

Analysis and optimization of a Maglev system based on the Halbach magnet arrays

A systematic analysis and an optimization are presented for an electrodynamic suspension Maglev system based on the Halbach magnet arrays that promises to develop a feasible Maglev system. The magnetic field was modeled using scalar potential and Fourier series methods and then confirmed with the corresponding finite element method (FEM) result. The optimization of the array was derived based on the performance index defined as the ratio of the square of flux to the magnet weight of a unit volume. The study results were applied to the Maglev system at the University of Central Florida for measuring the current capability and optimizing the performance while gaining some insight into the system stability.

A new nonlinear learning control for robot manipulators

A new iterative learning control scheme is applied to the trajectory tracking of robot manipulators. The proposed learning control is based on a hybrid, continuous and discrete, Lyapunov argument so that global asymptotic stability can be achieved with respect to the number of trials. This scheme also provides the designer flexibility to design and to implement a learning control for robotic systems by choosing various combinations of robust and learning control parts. The proposed control does not require acceleration measurement, resetting of initial tracking errors and Lipschitz condition. It is also robust in the sense that the exact knowledge of either the nonlinear dynamics or uncertainties of the system is not required except for bounding functions on the magnitude.