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The traditional control has good performance in the control of linear systems while has poor performance in the control of nonlinear systems. The bearingless asynchronous motor is a multivariable nonlinear system with high coupling. In this paper, the method of adaptive inverse control is proposed for these reasons. Firstly, the mathematical model of the bearingless asynchronous motor is built, and the possibility of the existence of the bearingless asynchronous motor system inverse model is explored. Secondly, since the object to be controlled is highly nonlinear and has high variability. In this paper, adaptive inverse fuzzy decoupling control is used to make up the deficiency of traditional adaptive inverse control. Finally, the Matlab simulation model is established. The simulation results show that the control method has good dynamic and static performance.

A bearingless induction motor is a strong coupled complex system, the decoupling control of torque and radial suspension force is the premise of the stable operation of the bearingless induction motor. In this paper, the principle of bearingless induction motor is expounded. The magnetic mathematical models of bearingless induction motor are created. The rotor field oriented control strategy is designed. The control strategy is validated with Matlab/simulink. Real-time simulation model based on dSPACE is given and the platform based on dSPACE is constructed. The results show that this method has good decoupling control performance. The actual system development and experiment process confirms that the dSPACE real-time simulation platform can shorten the development time and facilitate the development process, and save costs during the design and test period.

According to the strong coupling between the electromagnetic torque and radial suspension force, and the difficulty of establishing a precise mathematical model of bearingless induction motor, least squares support vector machine is proposed in this paper. The inverse model approximated by the LS-SVM is connected with the original system, decoupling a complex nonlinear multivariable system into four relatively independent pseudo-linear sub-systems of single input and single output. At the same time, fuzzy PID control strategy is introduced to the pseudo linear system to ensure the robustness and anti-jamming ability of the control system. Then the performance is simulated with Matlab/ Simulink. The theory research and simulation experiment have validated that the decoupling control of inverse system based on least squares support vector machine method can be successfully realized, which between the electromagnetic torque and radial suspension force, and the good performance of dynamic and static state of system can be also obtained.

Compared with the complex structure and unsatisfactory performance of traditional flywheel drive system, the proposed strategy adopts bearingless brushless DC motor as the drive actuator of flywheel. The direct torque control which combines the space voltage vector pulse width modulation is presented to control the system. Moreover, a simulation system is built with Matlab/Simulink toolbox. From the simulation results, the proposed control strategy is verified and the rotor can be stably suspended by suspension force along the central axis.

This paper designs an intelligent fuzzy PID controller of electromagnetic bearing for axial artificial heart pump (AAHP) to achieve re-stable suspension and quick response performance. and Matlab/Simulink is employed to simulate floating process of the rotor and the process of response to displacement disturbance. The simulation results show that the floating overshoot can be inhibited effectively, with the fuzzy PID controller. Fuzzy PID controller can respond to sudden displacement disturbance quickly. Then analyze the simulation waveforms of Fuzzy PID controller and traditional PID controller, verify that the fuzzy PID controller can overcome the shortcomings of traditional PID controller, and increase the control precision of the system and the robustness of the system.

In this paper, a new type of maglev wind generator is proposed. The working principle, structure characteristics and the finite element analysis of the new maglev wind turbine are introduced. The generator consists of a 2 degrees of freedom (DOF) maglev generator and a 3 DOF hybrid magnetic bearing. An eight poles active magnetic bearing with external rotor is added into traditional direct-drive permanent magnet wind generator. The rotor ring is hollowed, which can leads to the self-decoupling for magnetic fields between power generation system and suspension system. Compared with the conventional maglev wind generator, the proposed generator not only shows the same advantages of traditional maglev wind turbines, but also improves the axial length utilization and decrease the cost of motor control.

As an important component of maglev wind generators, magnetic bearing should possess the merits of small volume, light weight, lower consumption and so on. A novel low-loss axial hybrid magnetic bearing (HMB) is proposed in this paper, its structure and operation principle are introduced, and the process of producing suspension force is elaborated. Based on equivalent magnetic circuit method, magnetic circuit models of PM and control coil are analyzed and established to deduce the quotation of axial levitation force. The accuracy and the reasonableness of proposed low-loss axial HMB are analyzed and validated by using finite element method (FEM), and the comparison between theoretical calculation and FEM is given, which indicates the proposed HMB exhibits good dynamic response and easy control.

In This paper, a direct torque control (DTC) method for bearingless permanent magnet synchronous motor (BPMSM) based on three-level neutral-point clamped (NPC) inverter is described. Through the analysis of virtual space vector modulation, an independent control strategy is adopted into the suspension winding control and a flux linkage error vector SVM-DTC method supplied by three-level NPC inverter is introduced into the torque windings control. By using the proposed control strategy, the neutral-point voltage variation can be greatly limited and the voltage shifting can be eliminated. The results of simulation verify the feasibility of the control algorithm, the dv/dt of output voltage and the torque ripple are restrained effectively, satisfactory robustness and the good performance of the radial levitation can be achieved in a wide speed range by using the proposed method.

In order to realize the solar photovoltaic (PV) system connecting with grid friendly, a PV system with voltage-controlled inverter based on virtual synchronous generator (SG) is presented. This kind of system has features of SG, which supply the virtual moment of inertia to grid. The mathematical model of PV and virtual SG is built, and the control strategy of the maximum power point tracking (MPPT) is also studied in the paper. Simulation model of the grid-connected PV power system is built on Matlab/Simulink. Finally, correctness and feasibility of this system are verified by simulation results.

Magnetic suspension flywheel system is the actuator of spacecraft in high accurate position control, which requires the employed magnetic bearing possessing advantages of compact structure, small volume, light weight, low power loss, high efficiency and so on. A novel axial hybrid magnetic bearing in magnetic suspension flywheel is proposed, and the bias magnetic flux is provided with a permanent magnet ring. The cost and total volume of this structure can be reduced, which is especially suitable for magnetic suspension flywheel system. The structure and working principle of the axial magnetic bearing are explained, the mathematical expressions of the maximum bearing capacity are obtained, the detailed process of parameter design is presented, and the flux and maximum bearing capacity of the hybrid magnetic bearing are analyzed by using finite element analysis software. The analysis results validate the correctness of parameter design on the axial hybrid magnetic bearing.

In the paper, the decoupling control method based on least square support vector machine (LS-SVM) inverse system is proposed, and adopting the method realizes decoupling control of an AC-DC three degrees of freedom hybrid magnetic bearing (AC-DC-3DOF-HMB). Aimed at the complicated multivariate nonlinear, strong coupling system of the AC-DC-3DOF-HMB, the reversibility of original system was analyzed, by the ability of least square support vector machines (LS-SVM) in universal approximation and identification fitting to get inverse model of AC-DC three degrees of freedom hybrid magnetic bearing. Then according to the basic principle of inverse system method, the inverse system was connected with the original system. So the complex nonlinear multivariable system is decoupled into three independent pseudo-linear system. The simulation results show that the system was decoupled; the hybrid control method has good dynamic and static performance, verify the feasibility of the proposed control method.

The theory of direct torque control of traditional permanent magnet synchronous motor is applied to the radial suspension force control of a BPMSM in this paper.With the integration of the space vector pulse width modulation, a novelty SVPWM direct suspension force control system for the BPMSM is constructed.On the basis of mathematical modeling,the detail control algorithm is deduced.Then the control system is simulated with Matalab/Simulink,and the results show that the control algorithm is simplified and the torque ripples are restrained，fine static and dynamic performance is brought to the motor.

For the bearingless synchronous reluctance motor (BSRM) is a multivariable, strong coupling, multi-input and multi-output system, based on the adaptive inverse control theory, a decoupling control method based on the T-S fuzzy inverse model identification is put forward in this paper. According to the input and output information of the system, a fuzzy inverse model of the motor control system is established, then making the inverse model and the original control system in series forms pseudo linear hybrid system to realize the approximate linearization and dynamic decoupling of the motor control system. Building the composite system and proceeding research in the Matlab/Simulink environment, the simulation results show that the control strategy can realize dynamic decoupling among the electromagnetic torque subsystem and the radial suspension force subsystem and among thex- andy-direction of the suspension force, and with excellent static and dynamic performance and adaptive ability.

For more stable operation of radial AC hybrid magnetic bearing (radial AC HMB), it is particularly important to realize optimization design of parameters for its prototype. The paper focuses on solving the several typical defects of traditional methods and puts forward specific countermeasures on improving its disadvantages. Thus, a new parameter design method based on two sets of magnetic field system (the stator core magnetic field system and the air gap field system) is proposed to calculate the structure and electromagnetism parameters of the radial AC HMB. Using the proposed parameter design method, a finite element model of radial AC HMB based on the design results are simulated in finite element analysis software. The simulation results are consistent with the expected parameters calculation results very well, which show accuracy of the parameters and the proposed method. To illustrate the validity of the parameter design approaches further, the verification experiment is conducted. The operating experimental results show that the radial AC HMB has high stability, fast start of suspension and fine anti-disturbance. Moreover, system performance comparison results show the control system based on the new parameter design method has stronger anti-disturbance characteristics than that based on the traditional parameter design method.

A novel decoupling control method based on neural networks inverse system is presented in this paper for a bearingless synchronous reluctance motor (BSRM) possessing the characteristics of multi-input-multi-output, nonlinearity, and strong coupling. The dynamic mathematical models are built, which are verified to be invertible. A controller based on neural network inverse is designed, which decouples the original nonlinear system to two linear position subsystems and an angular velocity subsystem. Furthermore, the linear control theory is applied to closed-loop synthesis to meet the desired performance. Simulation and experiment results show that the presented neural networks inverse control strategy can realize the dynamic decoupling of BSRM, and that the control system has fine dynamic and static performance.

It is important to clarify the rotor eddy current losses in bearingless permanent magnet synchronous (BPMSM) for temperature rising to induce irreversible demagnetization. In this paper, the torque and radial suspension force producing mechanisms of BPMSM are introduced. The relative motion relationships among radial suspension force, rotor magnetic field and suspension winding magnetic field are analyzed. The necessary conditions of producing stable controllable radial suspension force in single direction are concluded. The rotor eddy current losses in BPMSM with PB=PM+1 and PB=PM-1 are calculated and compared using 2D time-steeping finite element method. The research results have shown that the BPMSM with PB=PM+1 is the most suitable for high speed operation with the minimum eddy current losses in rotor.

In this paper, a novel radial hybrid magnetic bearing is proposed, which is driven by an AC 3-phase power converter, and biased magnetic fluxes are provided by an axial magnetized permanent magnet ring. Based on the introduction of the configuration and principle of the radial AC hybrid magnetic bearing (AC HMB), the methods in parameter design and design results for the prototype are presented. The parameter design results for the prototype of the radial AC HMB are simulated by 3D electromagnetic finite element method and the simulation results show that the obtained parameter is reasonable. The manufactured prototype applying to the parameter is operated and the test results also show that the design result for the prototype is available, and the AC HMB has good dynamic and static performance.

A dynamic decoupling control method based on neural network inverse system theory is developed for the 5 degrees of freedom (5-DOF) rotor system. The rotor system suspended by AC hybrid magnetic bearings (HMBs) is a multivariable, nonlinear and strong coupled system. Firstly, the configuration of 5-DOF HMBs and the mathematical equations of suspension forces are set up. Secondly, it is demonstrated the system is reversible by analyzing mathematical model. On the basis, the neural network inverse system which is composed of the static neural networks and integrators, and original system are in series to constitute pseudo linear systems. Finally, linear system theory is applied to these linearization subsystems for designing close-loop controllers. The simulation results show that this kind of control strategy can realize dynamic decoupling control, and control system obtains good dynamic and static performances.

A bearingless permanent magnet-type synchronous motor (BPMSM) is a complicated non-linear and strongly coupled system. The decoupling control among the electromagnetic torque and radial suspension forces, and the dynamic decoupling control between the two orthogonal suspension forces are key techniques for the stable operation of a BPMSM. In this paper, a comprehensive system model, which consists of two Park inverse transformations, two Clark inverse transformations, two current following inverters and load model of BPMSM is given. The reversibility of the complex-controlled object is proved. Combining an artificial neural network (ANN) based inverse model, which consists of a static ANN and five integrators with the controlled object, the control system is decoupled into two independent second-order linear subsystems and a first-order linear subsystem, i.e., two displacement subsystems and a rotor speed subsystem. It then becomes much easy to design the close-loop linear regulators to control each of the subsystems. The simulation test results have shown that the proposed method can achieve strong robustness, good static and dynamic decoupling performance.

The state equations of the active magnetic bearing (AMB) multivariable system are established, and the configuration and working principle of active disturbances rejection controllers (ADRCs) are introduced. Based on the principle of ADRC and the mathematics model of AMB, an active disturbances rejection decoupling control strategy for the AMB multivariable system is put forward. The configuration of control system is built and the corresponding control arithmetic is given. According to the parameters of the experiment rig, the decoupling control simulation system is set up with MATLAB software. The step response of system, the start-up experiment of the rotor and the system antidisturbance performance are simulated. The simulation results have shown that the decoupling control system succeeds in decoupling control of the AMB multivariable system and has good static and dynamic performance.

A 5-degrees-of-freedom bearingless induction motor is a multi-variable, nonlinear and strong-coupled system. In order to achieve rotor suspension and operation steadily, it is necessary to realize dynamic decoupling control among torque and suspension forces. In the paper, a method based on a-th order inverse system theory is used to study dynamic decoupling control. Firstly, the working principles of a 3-degrees-of-freedom magnetic bearing and a 2-degrees-of-freedom bearingless induction motor are analyzed, the radial-axial force equations of 3-degrees-of-freedom magnetic bearing, the electromagnetic torque equation and radial force equations of the 2-degrees-of-freedom bearingless induction motor are given, and then the state equations of the 5-degrees-of-freedom bearingless induction motor are set up. Secondly, the feasibility of decoupling control based on dynamic inverse theory is discussed in detail, and the state feedback linearization method is used to decouple and linearize the system. Finally, linear control system techniques are applied to these linearization subsystems to synthesize and simulate. The simulation results have shown that this kind of control strategy can realize dynamic decoupling control among torque and suspension forces of the 5-degrees-of-freedom bearingless induction motor, and that the control system has good dynamic and static performance.