A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Performance and Safety Improvement of Induction Motors based on Testing and Evaluation Standards

The induction motor,which converts electrical energy into mechanical energy,has been recognized as the cornerstone of industrialization.The rotor of an induction motor can be either a squirrel cage rotor or a wound-type rotor,both existing as magnetless topologies.Three-phase squirrel cage induction motors are frequently utilized in industrial drives because they are dependable,have high starting torque,are selfstarting and affordable.Single-phase induction motors,on the other hand,are commonly used for small loads such as domestic appliances in form of modest fans,pumps and electric power tools.In South Africa,there have been reports of fires and explosions resulting in live and property loss because of induction motors that have not been thoroughly tested or are incorrectly labelled in terms of ratings,electrical safety and performance.The goal of this study is targeted at preventing end-user injuries and failures caused by non-compliant induction motors,by evaluating locally manufactured/imported induction motors based on tests and evaluation from standards(IEC and SANS).The study is conducted using experimental procedures at the Explosion Prevention Technology and Rotating Machines(EPT and RM)laboratory,South African Bureau of Standards(SABS),South Africa.The main finding from the study shows differences in the nameplate characteristics of various induction motors which could have detrimental effects such as production and operational downtime in their end-use industries,at later stages.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

Enhancement of motor functional recovery in thoracic spinal cord injury: voluntary wheel running versus forced treadmill exercise

Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery and morphological changes following thoracic contusive spinal cord injury. After a 7-day recovery period after spinal cord injury, mice were assigned to either a trained group(10 weeks of voluntary running wheel or forced treadmill exercise) or an untrained group. Bi-weekly assessments revealed that the exercise-trained group, particularly the voluntary wheel exercise subgroup, displayed significantly improved locomotor recovery, more plasticity of dopaminergic and serotonin modulation compared with the untrained group. Additionally, exercise interventions led to gait pattern restoration and enhanced transcranial magnetic motor-evoked potentials. Despite consistent injury areas across groups, exercise training promoted terminal innervation of descending axons. In summary, voluntary wheel exercise shows promise for enhancing outcomes after thoracic contusive spinal cord injury, emphasizing the role of exercise modality in promoting recovery and morphological changes in spinal cord injuries. Our findings will influence future strategies for rehabilitation exercises, restoring functional movement after spinal cord injury.

The burden of upper motor neuron involvement is correlated with the bilateral limb involvement interval in patients with amyotrophic lateral sclerosis:a retrospective observational study

Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.

TWO DOF POSITIONING STAGE USING LINEAR ULTRASONIC MOTORS

A two degrees of freedom （DOF） positioning stage using novel linear ultrasonic motors is presented. The stage mainly consists of two linear ultrasonic motors, linear guides and tables. It can realize the long stroke and reversible controlled motion in two directions. The wheel-shape linear ultrasonic motor applied in the stage utilizes two fourth-bending modes of non-uniform beam in orthogonal directions. Quick response, no backlash, high resolution, power-off self-braking, and long stroke are the attractive characteristics of the linear positioning stage. Experimental results show that z and y-direction tables can reach the destination without overshoot and the error is less than 2μm by using two linear encoders with a resolution of 1 μm. In the open-loop mode, the positioning stage achieves 1μm resolution at 0. 25 ms driving time.

ELLIPTIC MOTIONS ON MODAL CONVERSION ULTRASONIC MOTORS

The forming of elliptic motions on the modal conversion ultrasonic motors （MCUMs） is discussed. The principles of the modal conversion are investigated based on the coupling with the stator and the rotor, and using an independent coupler. The elliptical locus observed on the longitudinal-torslonal vibration converter with oblique slits is analyzed by using vibration theory. A method for the modal conversion is proposed by using the local mode of a substructure On a main structure. The method can be used to design the modal conversion type ultrasonic motors.

Speed Control of Travelling Wave Type Ultrasonic Motors Using Artificial Neural Network

Ultrasonic motor (USM) is a newly developed motor, and it has some excellent performances and useful features, therefore, it has been expected to be of practical use. However, the driving principle of USM is different from that of other electromagnetic type motors, and the mathematical model is complex to apply to motor control. Furthermore, the speed characteristics of the motor have heavy nonlinearity and vary with driving conditions. Hence, the precise speed control of USM is generally difficult. This paper proposes a new speed control scheme for USM using an artificial neural network. An accurate tracking response can be obtained by random initialization of the weights of the network owing to the powerful on line learning capability. Two prototype ultrasonic motors of travelling wave type were fabricated, both having 100 mm outer diameters of stator and piezoelectric ceramic. The usefulness and validity of the proposed control scheme are examined in experiments.

Nonlinear Decoupling Control of the Bearingless Induction Motors Based on the Airgap Motor Flux Orientation

The bearingless induction motor, which combines the inductionmotor and magnetic bearing is a strongly coupled complicatednonlinear system; the decoupling control of the electromag- net toqueand readial levitation force is the base of the stable operation ofthe benaringless motor. In this paper, the air-gap motor fluxoriented vector control is proposed to realize the decoupling controlof this nonlinear system even in the transient case based on thelevitation principle. Simulations show the stable suspension and goodperformance of the proposed algorithm.

An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

Induction motors （IMs） are commonly used in various industrial applications. To improve energy con- sumption efficiency, a reliable IM health condition moni- toring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is pro- posed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are syn- thesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air- gap eccentricity diagnosis. The effectiveness of the pro- posed harmonic synthesis technique is examined experi- mentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

Influence of Magnetic Reluctances of Magnetic Elements on Servo Valve Torque Motors

The current research of electro-hydraulic servo valves mainly focuses on the vibration, pressure oscillating and source of noise. Unfortunately, literatures relating to the study of the influence of the magnetic reluctances of the magnetic elements are rarely available. This paper aims to analyze the influence of the magnetic reluctances of the magnetic elements on torque motor. Considering these magnetic reluctances ignored in previous literatures, a new mathematical model of servo valve torque motor is developed and proposed based on the fundamental laws of electromagnetism. By using this new mathematical model and the previous models, electromagnetic torque constant and magnetic spring stiffness are evaluated for a given set of torque motor parameters. A computer simulation by using AMESim software is also performed for the same set of torque motor parameters to verify the proposed model. The theoretical results of electromagnetic torque constant and magnetic spring stiffness evaluated by the proposed model render closer agreement with the simulation results than those evaluated by the previous models. In addition, an experimental measurement of the magnetic flux densities in the air-gaps is carried out by using SFL218 servo valve torque motor. Compared with the theoretical results of the magnetic flux densities in the air-gaps evaluated by the previous models, the theoretical results evaluated by the proposed model also show better agreement with the experimental data. The proposed model shows the influence of the magnetic reluctances of the magnetic elements on the servo valve torque motor, and offers modified and analytical expressions to electromagnetic torque constant and magnetic spring stiffness. These modified and analytical expressions could provide guidance more accurately for a linear control design approach and sensitivity analysis on electro-hydraulic servo valves than the previous expressions.

Impulsive control of permanent magnet synchronous motors with parameters uncertainties

The permanent magnet synchronous motors （PMSMs） may have chaotic behaviours for the uncertain values of parameters or under certain working conditions, which threatens the secure and stable operation of motor-driven. It is important to study methods of controlling or suppressing chaos in PMSMs. In this paper, robust stabilities of PMSM with parameter uncertainties are investigated. After the uncertain matrices which represent the variable system parameters are formulated through matrix analysis, a novel asymptotical stability criterion is established. Some illustrated examples are also given to show the effectiveness of the obtained results.

FORCE RIPPLE SUPPRESSION TECHNOLOGY FOR LINEAR MOTORS BASED ON BACK PROPAGATION NEURAL NETWORK

Various force disturbances influence the thrust force of linear motors when a linear motor （LM） is running. Among all of force disturbances, the force ripple is the dominant while a linear motor runs in low speed. In order to suppress the force ripple, back propagation（BP） neural network is proposed to learn the function of the force ripple of linear motors, and the acquisition method of training samples is proposed based on a disturbance observer. An off-line BP neural network is used mainly because of its high running efficiency and the real-time requirement of the servo control system of a linear motor. By using the function, the force ripple is on-line compensated according to the position of the LM. The experimental results show that the force ripple is effectively suppressed by the compensation of the BP neural network.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

Current research in broken rotor bar （BRB） fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estima- tion cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the fre- quencies of the fundamental and fault characteristic com- ponents with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Feedback control of two-headed Brownian motors in flashing ratchet potential

We presented a detailed investigation on the movement of two-headed Brownian motors in an asymmetric potential under a feedback control. By numerical simulations the direct current is obtained. The current is periodic in the initial length of spring. There is an optimal value of the spring constant. And the dependence of the current on the opposing force is reversed. Then we found that when the change of the temperature and the opposing force have optimal values, the Brownian motors can also obtain the optimal efficiency.

Genetic Algorithms for the Optimal Design of Electromagnetic Micro-Motors

The genetic algorithm (GA) to the design of electromagnetic micro motor to optimize parameter design. Besides the different oversize from macro motor, the novel structure of micro motor which the rotor is set between the two stators make its design different, too. There are constraint satisfaction problems CSP) in the design. It is shown that the use GA offers a high rate of global convergence and the ability to get the optimal design of electromagnetic micro motors.

Adaptive synchronization of chaos in permanent magnet synchronous motors based on passivity theory

An adaptive synchronization control method is proposed for chaotic permanent magnet synchronous motors based on the property of a passive system. We prove that the controller makes the synchronization error system between the driving and the response systems not only passive but also asymptotically stable. The simulation results show that the proposed method is effective and robust against uncertainties in the systemic parameters.

Mode switching control strategy of dual motors coupled driving on electric vehicles

Based on analyzing the structure and working principle on electric vehicles （EVs） with dual motors coupled by planetarY gears, the control strategy of mode switching was proposed. The power interruption problem on EVs with automatic mechanical transmission （AMT） shifting was resolved. Based on the speed-torque characteristics of the planetary gears and the principle of the auxiliary motor＇ s zero speed braking, control features of mode switching were introduced. The mode shifting between the main motor mode and dual motors coupled driving were studied. Matlab/Simulink was adopted as a platform to develop the simulation model of EVs with dual motors drive system and 3 gears AMT. Simulation results demonstrated that the power interruption of dual motors drive system was solved during mode switching. The power requirements of EVs were satisfied, too.

Torque Distribution of Electric Vehicle with Four In-Wheel Motors Based on Road Adhesion Margin

With the worsening of energy crisis and environmental pollution,electric vehicles with four in?wheel motors have been paid more and more attention. The main research subject is how to reasonably distribute the driving torque of each wheel. Considering the longitudinal motion,lateral motion,yaw movement and rotation of the four wheels,the tire model and the seven DOF dynamic model of the vehicle are established in this paper. Then,the torque distribution method is proposed based on road adhesion margin,which can be divided into anti ? slip control layer and torque distribution layer. The anti?slip control layer is built based on sliding mode variable structure control,whose main function is to avoid the excessive slip of wheels caused by road conditions. The torque distribution layer is responsible for selecting the torque distribution method based on road adhesion margin. The simulation results show that the proposed torque distribution method can ensure the vehicle quickly adapt to current road adhesion conditions,and improve the handling stability and dynamic performance of the vehicle in the driving process.

Comparison of Two Novel MRAS Based Strategies for Identifying Parameters in Permanent Magnet Synchronous Motors

Two model reference adaptive system （MRAS） estimators are developed for identifying the parameters of permanent magnet synchronous motors （PMSM） based on the Lyapunov stability theorem and the Popov stability criterion, respectively. The proposed estimators only need online measurement of currents, voltages, and rotor speed to effectively estimate stator resistance, inductance, and rotor flux-linkage simultaneously. The performance of the estimators is compared and verified through simulations and experiments, which show that the two estimators are simple, have good robustness against parameter variation, and are accurate in parameter tracking. However, the estimator based on the Popov stability criterion, which can overcome parameter variation in a practical system, is superior in terms of response speed and convergence speed since there are both proportional and integral units in the estimator, in contrast to only one integral unit in the estimator based on the Lyapunov stability theorem. In addition, the estimator based on the Popov stability criterion does not need the expertise that is required in designing a Lyapunov function.