Active Magnetic Bearings (AMB) are a relatively recent innovation in bearing technology. Unlike conventional bearings, which rely on mechanical forces originating from fluid films or physical contact to support bearing loads, AMB systems utilize magnetic fields to levitate and support a shaft in an air-gap within the bearing stator. This design has many benefits over conventional bearings. The potential capabilities that AMB systems offer are allowing this new technology to be considered for use in state-of-the-art applications. For example, AMB systems are being considered for use in jet engines, submarine propulsion systems, energy storage flywheels, hybrid electric vehicles and a multitude of high performance space applications. Many of the benefits that AMB systems have over conventional bearings makes them ideal for use in these types of vehicular applications. However, these applications present a greater challenge to the AMB system designer because the AMB-rotor system may be subjected to external vibrations originating from the vehicle's motion and operation. Therefore these AMB systems must be designed to handle the aggregate vibration of both the internal rotor dynamic vibrations and the external vibrations that these applications will produce. This paper will focus on the effects of direct base excitation to an AMB/rotor system because base excitation is highly possible to occur in vehicular applications. This type of excitation has been known to de-stabilize AMB/rotor systems therefore this aspect of AMB system operation needs to be examined. The goal of this research was to design, build and test a test rig that has the ability to excite an AMB system with large amplitude base excitation. Results obtained from this test rig will be compared to predictions obtained from linear models commonly used for AMB analysis and determine the limits of these models. / Master of Science

Magnetic bearings have been researched by the National Aeronautics and Space Administration (NASA) for a very long time to be used in wide applications. This research was to assemble and test an axial thrust electromagnetic bearing, which can handle 1000 lb-f of axial thrust load, when rotating at high speed, in a high temperature environment of 1000 0F. This high temperature magnetic bearing system would be used in high performance, high speed and high temperature applications like space vehicles, jet engines and deep sea equipment. An experimental procedure was developed to measure actual load capacity of the designed bearing in the test rig. All the results obtained from the experiment were compiled and analyzed to determine the relation between bearing force, applied current and temperature. The thesis incorporates the assembly, testing of the electromagnetic bearing at various speeds and temperatures and compare predicted to measured force vs. speed, current, gap and temperature. The results showed that the high temperature thrust magnetic bearing is capable of handling 1000 lb-f at 10000F and 5500 rpm.

One of the main challenges in order to make electric cars competitive with gas-powered cars is in the improvement of the electric power system. Although many of the energy sources currently used in electric vehicles have sufficientlyhigh specific energy, their applicability is limited due to low specific power. It would therefore be advantageous to create a driveline with the main energy storage separated from a smaller energy buffer, designed to have high power capabilities and to withstand frequent and deep discharge cycles. It has been found that rotating kinetic energy storage in flywheels is very well suited for this type of application. A composite shell, comprising an inner part made of glassfiber and an outer part made of carbonfiber, was analyzed analytically and numerically, designed, and constructed. The shell was fitted onto a metallic rotor using shrinkfitting. The cost of the shell, and the complexity of assembly, was reduced by winding the glass- and carbonfiber consecutively on a mandrel, and curing the complete assembly simultaneously. Thereby, the shell obtained an internal segmentation, without the need for fitting several concentric parts onto each other. The radial stress inside the composite shell was kept compressive thanks to a novel approach of using the permanent magnets of the integrated electric machine to provide radial mechanical load during rotation. Two thrust bearing units (one upper and one lower) comprising one segmented unit with the permanent magnets in a cylindrical Halbach configuration and one non-segmented unit in a up/down configuration were optimized, constructed and tested. Each thrust bearing unit generated 1040 N of repelling force, and a positive axial stiffness of 169 N/mm at the nominal airgap of 5 mm.  Two radial active magnetic bearings (one upper and one lower) were optimized, constructed and tested. By parameterizing the shape of the actuators, a numerical optimization of force over resistive loss from the bias currentcould be performed. The optimized shape of the electromagnets was produced by watercutting sheets of laminated steel. A maximum current stiffness of120 N/A at a bias current of 1.5 A was achieved.

Historical attempts to measure forces in magnetic bearings have been unsuccessful as a result of relatively high uncertainties. Recent advances in the strain-gauge technology have provided a new method for measuring magnetic bearing forces. Fiber optic strain gauges are roughly 100 times more sensitive than conventional strain gauges and are not affected by electro-magnetic interference. At the Texas A&M Turbomachinery Laboratory, installing the fiber-optic strain gauges in magnetic bearings has produced force measurements with low uncertainties. Dynamic flexibility transfer functions exhibiting noticeable gyroscopic coupling have been identified and compared with results of a finite element model. The comparison has verified the effectiveness of using magnetic bearings as calibrated exciters in rotordynamic testing. Many applications including opportunities for testing unexplained rotordynamic phenomena are now feasible.

Historical attempts to measure forces in magnetic bearings have been unsuccessful as a result of relatively high uncertainties. Recent advances in the strain-gauge technology have provided a new method for measuring magnetic bearing forces. Fiber optic strain gauges are roughly 100 times more sensitive than conventional strain gauges and are not affected by electro-magnetic interference. At the Texas A&M Turbomachinery Laboratory, installing the fiber-optic strain gauges in magnetic bearings has produced force measurements with low uncertainties. Dynamic flexibility transfer functions exhibiting noticeable gyroscopic coupling have been identified and compared with results of a finite element model. The comparison has verified the effectiveness of using magnetic bearings as calibrated exciters in rotordynamic testing. Many applications including opportunities for testing unexplained rotordynamic phenomena are now feasible.

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Fault tolerant control can accommodate the component faults in a control system such as sensors, actuators, plants, etc. This dissertation presents two fault tolerant control schemes to accommodate the failures of power amplifiers and sensors in a magnetic suspension system. The homopolar magnetic bearings are biased by permanent magnets to reduce the energy consumption. One control scheme is to adjust system parameters by swapping current distribution matrices for magnetic bearings and weighting gain matrices for sensor arrays, but maintain the MIMO-based control law invariant before and after the faults. Current distribution matrices are evaluated based on the set of poles (power amplifier plus coil) that have failed and the requirements for uncoupled force/voltage control, linearity, and specified force/voltage gains to be unaffected by the failure. Weighting gain matrices are evaluated based on the set of sensors that have failed and the requirements for uncoupling x1 and x2 sensing, runout reduction, and voltage/displacement gains to be unaffected by the failure. The other control scheme is to adjust the feedback gains on-line or off-line, but the current distribution matrices are invariant before and after the faults. Simulation results have demonstrated the fault tolerant operation by these two control schemes.

The harsh conditions of space, the stringent requirements for orbiting devices, and the increasing precision pointing requirements of many space applications demand an actuator that can provide necessary force while using less space and power than its predecessors. Ideally, this actuator would be able to isolate vibrations and never fail due to mechanical wear, while pointing with unprecedented accuracy. This actuator has many space applications from satellite optical communications and satellite appendage positioning to orbiting telescopes. This thesis presents the method of design of such an actuator a self-bearing motor. The actuator uses Lorentz forces to generate both torque and bearing forces. It has a slotless winding configuration with four sets of three-phase currents. A stand-alone software application, LFMD, was written to automatically optimize and configure such a motor according to a designers application requirements. The optimization is done on the bases of minimum powerloss, minimum motor outer diameter, minimum motor mass, and minimum length. Using that program, two sample space applications are analyzed and applicable motor configurations are presented.

The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is faced with many challenges because AMB systems are multivariable, nonlinear, dynamic and inherently unstable systems. It is no wonder that existing AMB models are poor approximations of reality. This modelling problem is avoided because the adaptive controller is based on an indirect adaptive control law. Online system identification is performed by a neural network to obtain a better model of the AMB flywheel system. More specifically, a nonlinear autoregressive with exogenous inputs (NARX) neural network is implemented as an online observer. Changes in the AMB flywheel system’s environment also add uncertainty to the control problem. The adaptive controller adjusts to these changes as opposed to a robust controller which operates despite the changes. Making use of reinforcement learning because no online training data can be obtained, an adaptive critic model is applied. The adaptive controller consists of three neural networks: a critic, an actor and an observer. It is called an observer-based adaptive critic neural controller (ACNC). Genetic algorithms are used as global optimization tools to obtain values for the parameters of the observer, critic and actor. These parameters include the number of neurons and the learning rate for each neural network. Since the observer uses a different error signal than the actor and critic, its parameters are optimized separately. When the actor and critic parameters are optimized by minimizing the tracking error, the observer parameters are kept constant. The chosen adaptive control design boasts analytical proofs of stability using Lyapunov stability analysis methods. These proofs clearly confirm that the design ensures stable simultaneous identification and tracking of the AMB flywheel system. Performance verification is achieved by step response, robustness and stability analysis. The final adaptive control system remains stable in the presence of severe cross-coupling effects whereas the original decentralized PD control system destabilizes. This study provides the justification for further research into adaptive control using artificial intelligence techniques as applied to the AMB flywheel system. / Thesis (M.Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2011.

The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is faced with many challenges because AMB systems are multivariable, nonlinear, dynamic and inherently unstable systems. It is no wonder that existing AMB models are poor approximations of reality. This modelling problem is avoided because the adaptive controller is based on an indirect adaptive control law. Online system identification is performed by a neural network to obtain a better model of the AMB flywheel system. More specifically, a nonlinear autoregressive with exogenous inputs (NARX) neural network is implemented as an online observer. Changes in the AMB flywheel system’s environment also add uncertainty to the control problem. The adaptive controller adjusts to these changes as opposed to a robust controller which operates despite the changes. Making use of reinforcement learning because no online training data can be obtained, an adaptive critic model is applied. The adaptive controller consists of three neural networks: a critic, an actor and an observer. It is called an observer-based adaptive critic neural controller (ACNC). Genetic algorithms are used as global optimization tools to obtain values for the parameters of the observer, critic and actor. These parameters include the number of neurons and the learning rate for each neural network. Since the observer uses a different error signal than the actor and critic, its parameters are optimized separately. When the actor and critic parameters are optimized by minimizing the tracking error, the observer parameters are kept constant. The chosen adaptive control design boasts analytical proofs of stability using Lyapunov stability analysis methods. These proofs clearly confirm that the design ensures stable simultaneous identification and tracking of the AMB flywheel system. Performance verification is achieved by step response, robustness and stability analysis. The final adaptive control system remains stable in the presence of severe cross-coupling effects whereas the original decentralized PD control system destabilizes. This study provides the justification for further research into adaptive control using artificial intelligence techniques as applied to the AMB flywheel system. / Thesis (M.Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2011.