In this paper, a neural network learning adaptive robust controller (NNLARC) is synthesized for an industrial linear motor stage to achieve good tracking performance and excellent disturbance rejection ability. The NNLARC scheme contains parametric adaption part, robust feedback part, and radial basis function (RBF) neural network (NN) part in a parallel structure. The adaptive part and the robust part are designed based on the system dynamics to meet the challenge of parametric variations and uncertain random disturbances. It must be noted that in actual industrial machining situations, precision motion equipment is always disturbed by unknown factors, which usually cannot be described by mathematical models but affect the tracking accuracy significantly. Therefore, the RBF NN part is employed to further approximate and compensate the complicated disturbances with high reconstructing accuracy and fast training rate. The stability of the proposed NNLARC strategy is analyzed and proved through the Lyapunov theorem. Comparative experiments under various external disturbances such as completely unknown disturbance added by polyfoam are conducted on an industrial linear motor stage. The experimental results consistently validate that the proposed NNLARC control strategy can excellently meet the challenge of complicated disturbance in practical applications. The proposed scheme also provides a guidance for control strategy synthesis with both good tracking performance and disturbance rejection.

Neural Network Learning Adaptive Robust Control of an Industrial Linear Motor-Driven Stage With Disturbance Rejection Ability

https://engagedscholarship.csuohio.edu/cgi/viewcontent.cgi?article=1044&context=enme_facpub

Detecting cracked rotors using auxiliary harmonic excitation

Two-stage oil-free centrifugal air compressors can bring significant advantages and open new market opportunities for compressor manufacturers. One of the core technologies behind this compressor type is the high-speed electrical machine supported by active magnetic bearings. In this paper, the requirements set by the compressor on the electrical machine design are presented. The design solutions aimed to satisfy these requirements are discussed. Two case studies illustrate possible design approaches for the target application with examples of a 120-kW, 60 000-r/min induction machine with a solid rotor and a 225-kW, 50 000-r/min permanent-magnet synchronous machine (PMSM) with a full cylindrical magnet. The system design and simulation results are confirmed by measurements of a PMSM prototype.

Design Aspects of High-Speed Electrical Machines With Active Magnetic Bearings for Compressor Applications

Most industrial active magnetic bearings (AMBs) are controlled by proportional–integral–derivative (PID) controllers. Usually, a time-consuming iterative manual tuning procedure is required to design these PID controllers. In this contribution, we introduce the strategy, algorithms, and results from an AMB controller design, including optimization using a multiobjective genetic algorithm. We focus on the combination of frequency- and time-domain-based optimization, a strategy for the evaluation of fitness functions for complex PID-controller design, and a sensitivity-based parameter reduction for optimization. Two AMB system controller designs are considered and satisfactory results are obtained using the suggested optimization strategy. For validation purposes, the optimized controller design is experimentally implemented for the first AMB system, which contains a flexible test rotor supported by two AMBs. The maximal rotational speed of 15 000 r/min is achieved for the test rotor. A comparison between simulated and experimental results is presented.

Optimization Strategy for PID-Controller Design of AMB Rotor Systems

With the development of the magnetic bearing (MB) and its application in industry, the demands of high-speed MB are developing, which bring up new problems and requirement for the design. The motor with a high-speed rigid rotor requires that the axial length of MB is minimized to increase the critical speed, and the diameter of thrust disk is minimized to reduce the air friction loss. Also because of the high speed, the eddy currents induced in the iron cores have a significant influence on the dynamic characteristics of the MB. To design a high-performance MB for a high-speed motor, first an MB structure that has the feature of short axial length and small thrust disk is recommended for the high-speed motor. Next, the dynamic model, which takes into consideration eddy current effects, and leakage effects is developed. Then, an optimal design method with multiobjective of minimum length and air friction loss is presented. Design constraints are imposed, which includes the simultaneous consideration of material properties, load capacity, and power amplifier. Finally, a design example is given and a prototype is manufactured. The experimental results demonstrate that the proposed MB structure and the optimization method are feasible and valid in the application of a high-speed motor.

Design and Optimization Method of Magnetic Bearing for High-Speed Motor Considering Eddy Current Effects

A method is presented for tooltip tracking in active magnetic bearing (AMB) spindle applications. The proposed tool tracking approach uses control of the AMB air gap to achieve the desired tool position. A μ-synthesis-based controller is designed for the AMBs with the goal of robustly minimizing the difference between the tool reference and estimated tool position. In such a way, the model-based control approach concurrently addresses the tracking problem and the inability to directly measure real-time tool position in the presence of machining disturbances. To ensure the tractability of the control problem, a model of the desired tracking dynamics is included in the plant. The method is demonstrated on a high-speed AMB boring spindle. To confirm the tool tracking capability, characteristic part geometries are traced including stepped, tapered, and convex profiles. Tool tracking is demonstrated for the rotating AMB spindle in the range of 90 μm. Also, static and dynamic external loading is applied to the spindle tool location to confirm the disturbance rejection ability of the closed-loop system.

Magnetic Bearing Spindle Tool Tracking Through ${\mu}$ -Synthesis Robust Control

It has been widely recognized that the changes in the dynamic response of a rotor could be utilized for general fault detection and monitoring. Current methods rely on the monitoring of synchronous response of the machine during its transient or normal operation. Very little progress has been made in developing robust techniques to detect subtle changes in machine condition caused by rotor cracks. It has been demonstrated that the crack-induced changes in the rotor dynamic behavior produce unique vibration signatures. When the harmonic excitation force is applied to the cracked rotor system, nonlinear resonances occur due to the nonlinear parametric excitation characteristics of the crack. These resonances are the result of the coexistence of a parametric excitation term and different frequencies present in the system, namely critical speed, the synchronous frequency, and excitation frequency from the externally applied perturbation signals. This paper presents the application of this approach on an experimental test rig. The simulation and experimental study for the given rig configuration, along with the application of active magnetic bearings as a force actuator, are presented.

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Condition Monitoring of Rotor Using Active Magnetic Actuator

This paper presents an experimentally-driven model updating approach to address the dynamic inaccuracy of the nominal finite element (FE) rotor model of a machining spindle supported on active magnetic bearings. Modeling error is minimized through the application of a numerical optimization algorithm to adjust appropriately selected FE model parameters. Minimizing the error of both resonance and antiresonance frequencies simultaneously accounts for rotor natural frequencies as well as for their mode shapes. Antiresonance frequencies, which are shown to heavily influence the model’s dynamic properties, are commonly disregarded in structural modeling. Evaluation of the updated rotor model is performed through comparison of transfer functions measured at the cutting tool plane, which are independent of the experimental transfer function data used in model updating procedures. Final model validation is carried out with successful implementation of robust controller, which substantiates the effectiveness of the model updating methodology for model correction.Copyright © 2012 by ASME

/pdf/rotor-model-updating-and-validation-for-an-active-magnetic-g28441otxw.pdf

Rotor Model Updating and Validation for an Active Magnetic Bearing Based High-Speed Machining Spindle

A rotor supported on active magnetic bearings (AMBs) is levitated inside an air gap by electromagnets controlled in feedback. In the event of momentary loss of levitation due to an acute exogenous disturbance or external fault, reestablishing levitation may be prevented by unbalanced forces, contact forces, and the rotor’s dynamics. A novel robust control strategy is proposed for ensuring levitation recovery. The proposed strategy utilizes model-based μ-synthesis to find the requisite AMB control law with unique provisions to account for the contact forces and to prevent control effort saturation at the large deflections that occur during levitation failure. The proposed strategy is demonstrated experimentally with an AMB test rig. First, rotor drop tests are performed to tune a simple touchdown-bearing model. That model is then used to identify a performance weight, which bounds the contact forces during controller synthesis. Then, levitation recovery trials are conducted at 1000 and 2000 RPM, in which current to the AMB coils is momentarily stopped, representing an external fault. The motor is allowed to drive the rotor on the touchdown bearings until coil current is restored. For both cases, the proposed control strategy shows a marked improvement in relevitation transients.

Active Magnetic Bearing Online Levitation Recovery through μ-Synthesis Robust Control

The purpose of this paper is to present a method for development of the optimal speed-dependent control matrix for a rotor supported on active magnetic bearings (AMBs) with the provision of minimum control power consumption over the operating speed range. The speed dependency of the optimal control matrix is the result of the dynamics of rotating machines. Most of published works on optimal control use a stationary optimal control matrix derived for the non-rotating system and thus neglecting the effect of gyroscopic phenomena. This paper employs the minimum energy consumption condition to derive the speed varying optimal control for rotating AMB rotor system. In the presented approach the control matrix is characterized by a second order polynomial matrix with the angular speed as a variable. This leads to a more compact and lower computational burden for controller implementation. Calculations are performed for a 4-axis AMB rotor test rig. Testing with rotor speed ramps is performed and experimental values for power consumption are presented. These results are compared to results with speed invariant optimal control and PID control.Copyright © 2010 by ASME

Alexander H. Pesch

Papers

Magnetic Bearing Spindle Tool Tracking Through ${\mu}$ -Synthesis Robust Control

Condition Monitoring of Rotor Using Active Magnetic Actuator

Rotor Model Updating and Validation for an Active Magnetic Bearing Based High-Speed Machining Spindle

Active Magnetic Bearing Online Levitation Recovery through μ-Synthesis Robust Control

Experimental Investigations of Minimum Power Consumption Optimal Control for Variable Speed AMB Rotor