Adaptive complementary sliding-mode control for thrust active magnetic bearing system

An adaptive complementary sliding-mode control (ACSMC) system with a multi-input-multi-output (MIMO) recurrent Hermite neural network (RHNN) estimator is proposed to control the position of the rotor in the axial direction of a thrust active magnetic bearing (TAMB) system for the tracking of various reference trajectories in this study. First, the operating principles and dynamic model of the TAMB system using a linearized electromagnetic force model is derived. Then, a conventional sliding-mode control (SMC) system is designed for the tracking of various reference trajectories. Moreover, a complementary sliding-mode control (CSMC) system is adopted to reduce the guaranteed ultimate bound of the tracking error by half while using the saturation function as compared with the SMC. Furthermore, since the system parameters and the external disturbance are highly nonlinear and time-varying, the ACSMC is proposed to further improve the control performance and increase the robustness of the TAMB system. In the ACSMC, the MIMO RHNN estimator with estimation laws is proposed to estimate two complicated dynamic functions of the system on-line. In addition, a robust compensator is proposed to confront the minimum approximated errors and achieve the robustness. Finally, some experimental results for the tracking of various reference trajectories show that the control performance of the ACSMC is significantly improved comparing with the SMC and CSMC.     

Active magnetic bearings for machining applications

High-speed machining offers substantial economic benefits due to increased metal cutting productivity. Critical to realizing this technology's promise are the intertwined challenges of spindle dynamic stiffness and cutting process stability. Active magnetic bearings enable greater spindle dynamic stiffness through higher attainable bearing surface speeds, and also provide a means for enhancing cutting process stability. Herein, experimental results from two test rigs are presented illustrating the potential of magnetic bearings for the active suppression of machining chatter. Application challenges and controller design issues are examined in detail.     

Stability analysis of hybrid magnetic bearings

A mathematical model of noncontact bearings consisting of high-coercivity permanent magnets and electromagnetic control system is presented. The model is used to prove the stability of the rotor installed on such bearings by the Lyapunov method.     

基于BP的PID算法在磁轴承控制系统中研究

磁悬浮轴承数学模型复杂，常规PID很难达到预期控制效果。本文综合常规PID及BP网络的优点，设计出一种基于BP网络的PID自调整算法控制器。仿真结果表明：使用该算法的PID控制器，可在线获得最优的比例、积分及微分参数值，使整个系统得到最优化配置。     

A fault-tolerant multiprocess controller for magnetic bearings

A fault-tolerant microprocessor system designed to provide digital control for an active magnetic bearing is described. This particular control problem demands significant processing power, is easily divided into relatively independent parallel tasks, and cannot tolerate controller failures. The overall system requirements and architecture are described, as is the design of the digital control module and the analog I/O board. The fault tolerance of the system is evaluated. Extensive computer simulations of system reliability models verified that the design satisfies all of the reliability requirements. Although the system was designed for a specific problem, much effort was expended to make it general enough for applications to a wide range of real-time applications     

推靠式旋转导向系统推力变化平缓的控制方法

随着石油天然气开采难度越来越大,水平井、大位移井等高难度井越来越多,对旋转导向系统的需求也不断增加。目前国内推靠式旋转导向系统的控制方法比较复杂,且推力变化不平缓。针对上述情况,通过研究矢量分解以及高次谐波的作用,提出了一种简单且推力变化平缓的控制方法。该方法软件实现简单,而且由于推力变化平缓而降低了控制系统执行机构的设计难度,具有很好的工程应用价值。     

An algorithm for controlling hybrid magnetic bearings using the magnetic field pattern

A novel algorithm and a way of controlling the rotor position in hybrid magnetic bearings based on the pattern of the external magnetic field is presented. A mathematical apparatus for the practical implementation of the proposed control method and algorithm is developed, and computer simulation using Ansys and Maxwell is carried out. Results of experimental verification of theoretical conclusions are presented.     

磁轴承系统中差动变压器式位移传感器的研究

设计了用于磁悬浮轴承系统中的差动变压器式位移传感器。从基本原理出发,结合磁轴承特点,提出了改进的传感器结构方案。利用线性差动变压器的专用芯片AD598作为传感器的测量电路。实验结果表明:所设计的传感器具有较好的性能:在-0.35~0.35mm测量范围内,线性度为±1.25%,灵敏度可高达23.77mV/μm,完全适用于磁悬浮轴承系统中。     

Experimental comparison of nonlinear tracking controllers for active magnetic bearings

This paper presents an experimental comparison of position tracking controllers for an active magnetic bearing system. Two nonlinear designs are presented, each based on a different actuating constraint. The first design uses the constant current sum (CCS) biasing condition, and the second uses the current almost complementary (CAC) switching condition. While both designs achieve accurate tracking for a non-rotating shaft, a comparison of unbalance responses shows that the CCS-based design is more robust to disturbances for a given voltage saturation level. The nonlinear designs are compared to an industry standard decentralized PID controller. Experimental results are obtained using a commercially available five degree-of-freedom test stand.     

Electrohydraulic thrust vector control of twin rocket engines with position feedback via angular transducers

The thrust vector control (TVC) of rocket engines is used when the aerodynamic surfaces are inadequate to control vehicles or when a greater agility may be required of a missile. Traditionally, in all spacecraft to date actuators used to gimbal the engine have been hydraulic. The subject of this paper is the TVC with gimballed nozzle assembly controlled by an electrohydraulic servosystem, where two linear hydraulic servoactuators gimbal the engine. Each servoactuator is controlled by an electrohydraulic servovalve. The thrust vector direction is a result of the motion of both servoactuators. In this paper the TVC system is treated as a robotic system that allows developing the procedure of solving an inverse kinematics problem as well as the control of the robotic system in the output space instead of in the space of internal dynamics. The position feedback is provided by measuring the direction of the thrust vector, instead of measuring the displacements of the servoactuators. A linear model of the servosystem has been developed and simulated. The proposed control concept has experimentally been validated in the TVC test bench.     

Positioning control of an underwater robot with tilting thrusters via decomposition of thrust vector

Positioning control of an underwater robot is a challenging problem due to the high disturbances of ocean flow. To overcome the high disturbance, a new underwater robot with tilting thrusters was proposed previously, which can compensate for disturbance by focusing the thrusting force in the direction of the disturbance. However, the tilting motion of the thrusters makes the system nonlinear, and the limited tilting speed sometimes makes the robot unstable. Therefore, an optimized controller is necessary. A new positioning controller is proposed for this robot using a vector decomposition method. Based on the dynamic model, the nonlinear force input term of the tilting thrusters is decomposed in the horizontal and vertical directions. Based on the decomposition, the solution is determined by a pseudo-inverse and null-space solution. Using the characteristics of the decomposed input matrix, the final solution can be found by solving a simple second-order algebraic equation to overcome the limitations of the tilting speed. The positioning was simulated to validate the proposed controller by comparing the results with a switching-based controller. Tracking results are also presented. In future work, a high-level control strategy will be developed to take advantage of the tilting thrusters by focusing the forcing direction toward the disturbance with a limited stability margin.

     

Position regulator for spindle of milling machine by embedded magnetic bearings

The goal of this work is to concurrently counter-balance the dynamic cutting force and regulate the spindle position deviation by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm and an adaptive self-tuning feedback loop. The mathematic model for cutting dynamics is constructed by experiments so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm. Once the cutting force can be real-time estimated, the corresponding compensation force can be exerted by the equipped AMB to counter-balance the cutting force (i.e., via inner-loop), in addition to the spindle position regulation by the feedback of spindle position (i.e., via outer-loop). At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.     

Sensor runout compensation in active magnetic bearings via an integral adaptive observer

Sensor runout is one of the main sources of harmonic disturbances in active magnetic bearing systems. This type of the disturbance not only causes harmonic vibrations in the system but also changes the steady-state position of the axis of rotation from the geometric center of the AMB. In this paper, an integral adaptive observer is proposed to identify the dc and harmonic content of the sensor runout and to estimate the states of the system at the same time. The Lyapunov method is used to prove asymptotic stability of the proposed observer. Unlike the proportional observer which amplifies the measurement error, the sensor runout can be completely compensated when the states of the integral adaptive observer are used for feedback stabilization. It is shown that the proposed technique can also attenuate rotor displacements, when both sensor runout and mass unbalance disturbances are applied to the system. Simulation results have been presented for both cases to demonstrate the performance of the integral adaptive observer. Experimental results are also obtained by an AMB test rig, which confirm the effectiveness of the proposed method.     

Complete determination of the dynamic coefficients of coupled journal and thrust bearings considering five degrees of freedom for a general rotor-bearing system

A complete method is presented for calculating the stiffness and damping coefficients of coupled journal and thrust bearings of a general rotor-bearing system considering five degrees of freedom. The Reynolds equations and their perturbation equations were derived by linearization of the bearing reaction with respect to the general five degrees of freedom, i.e., the tilting displacements and angular velocities as well as the translational displacements and velocities. The Reynolds equations and their perturbation equations were transformed into finite element equations by considering the continuity of pressure and flow at the interface between the journal and the thrust bearings. The Reynolds boundary condition was included in the numerical analysis so as to simulate the phenomenon of cavitation. The stiffness and damping coefficients of the proposed method were compared with those found from a numerical differentiation of the loads with respect to the finite displacements and velocities of the bearing center. It was shown that the proposed method may be used to calculate the dynamic coefficients of coupled journal and thrust bearings more accurately and efficiently than the differentiation method. The tilting motion was also been found to play an important role in the determination of force and moment coefficients.     

Motion control for a vertical rigid rotor rotating in electromagnetic bearings

The problems of control of a motion of a rigid rotor in electromagnetic bearings are considered. The main ides of synthesis of the control laws is the approach based on feedback linearization of the original nonlinear mathematical model of the system. The method of Lyapunov functions and methods connected with solution of linear matrix inequalities are used in synthesis of control laws.     

Millimeter-scale actuator with fiber-optic roller bearings

A technique combining semiconductor processing and fiber-optic technology has been developed to micromachine a 1-cm² silicon die that rolls on two wheels above a flat substrate. Each wheel consists of a glass capillary surrounding a fixed solid glass fiber axle. A 100-silicon die is anisotropically etched to create two variable width v-grooves. Each v-groove has a wide center section and two narrow ends, which is schematically illustrated as -==-. The capillary is free to rotate about the axle in the wide v-groove section while the axle is anodically bonded into the narrow v-groove ends. The gap between the die and the substrate is determined by the narrow v-groove width, fiber diameter, and capillary wall thickness. Several rolling die have been fabricated with 210-120 μm gaps. The coefficient of static friction (μ_S) has been investigated on several substrates as a function of the load on the die. Values for μ_S are compared to an unetched die with a silicon nitride coating. With loads ranging from 0-10 grams, the wheels reduce μ_S by more than 50% on borosilicate glass     

Learning control using fuzzified self-organizing radial basisfunction network

This note describes an approach to integrating fuzzy reasoning systems with radial basis function (RBF) networks and shows how the integrated network can be employed as a multivariable self-organizing and self-learning fuzzy controller. In particular, by drawing some equivalence between a simplified fuzzy control algorithm (SFCA) and a RBF network, we conclude that the RBF network can be interpreted in the context of fuzzy systems and can be naturally fuzzified into a class of more general networks, referred to as FBFN, with a variety of basis functions (not necessarily globally radial) synthesized from each dimension by fuzzy logical operators. On the other hand, as a result of natural generalization from RBF to SFCA, we claim that the fuzzy system like RBF is capable of universal approximation. Next, the FBFN is used as a multivariable rule-based controller but with an assumption that no rule-base exists, leading to a challenging problem of how to construct such a rule-base directly from the control environment. We propose a simple and systematic approach to performing this task by using a fuzzified competitive self-organizing scheme and incorporating an iterative learning control algorithm into the system. We have applied the approach to a problem of multivariable blood pressure control with a FBFN-based controller having six inputs and two outputs, representing a complicated control structure     

Compactly supported radial basis functions for adaptive process control

An adaptive nonlinear control strategy based on networks of compactly supported radial basis functions is proposed. The local influence of the basis functions allows efficient on-line adaptation that is performed using a gradient law, and new basis functions are added to the network only when new regions in state space are encountered and the prediction error exceeds a pre-specified tolerance. The approximate model is used to construct an input-output linearizing control law. The adaptive control strategy is applied to a nonlinear chemical reactor model.     

Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles

An obstacle avoidance problem of rear-steered wheeled vehicles in consideration of the presence of uncertainties is addressed. Modelling errors and additional uncertainties are taken into consideration. Controller designs for driving and steering motors are designed. A proportional-derivative-type driving motor controller and a sliding-mode steering controller combined with radial basis function neural network (RBFNN) based estimators are proposed. The convergence properties of the RBFNN-based estimators are proven by the Stone–Weierstrass theorem. The stability of the proposed control law is proven using Lyapunov stability analysis. The obstacle avoidance strategy utilising the sliding surface adjustment to an existing navigation method is presented. It is concluded that the driving velocity and steering-angle performances of the proposed control system are satisfactory.     

Position error reduction in magnetic disk drives using a head gimbal assembly with radial head motion capability

Reducing the head positioning error is important to achieve higher track density in hard disk drives. In this paper, it is shown that the head off-track due to disk vibration can be reduced by using a head gimbal assembly capable of moving not only vertically to disk surface but also radially across the track. We find the optimal geometric relationship to minimize the head off-track due to disk vibration. The relationship is obtained based on precise mathematical modeling of head off-track mechanism due to disk vibration. Some examples of head gimbal assembly (HGA) with radial head motion capability, which satisfy such optimal relationship, are also proposed. It is experimentally found that the proposed optimal HGA can reduce non-repeatable run-out (NRRO) position error signal (PES) significantly. Since it reduces NRRO PES during servo track writing as well, the written-in portion of repeatable run-out PES can be also significantly reduced.