Analyzing the Combination Effects of Repetitive Transcranial Magnetic Stimulation and Motor Control Training on Balance Function and Gait in Patients with Stroke-Induced Hemiplegia

Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.

Fault Detection for Motor Drive Control System of Industrial Robots Using CNN-LSTM-based Observers

The complex working conditions and nonlinear characteristics of the motor drive control system of industrial robots make it difficult to detect faults.In this paper,a deep learning-based observer,which combines the convolutional neural network(CNN)and the long short-term memory network(LSTM),is employed to approximate the nonlinear driving control system.CNN layers are introduced to extract dynamic features of the data,whereas LSTM layers perform time-sequential prediction of the target system.In terms of application,normal samples are fed into the observer to build an offline prediction model for the target system.The trained CNN-LSTM-based observer is then deployed along with the target system to estimate the system outputs.Online fault detection can be realized by analyzing the residuals.Finally,an application of the proposed fault detection method to a brushless DC motor drive system is given to verify the effectiveness of the proposed scheme.Simulation results indicate the impressive fault detection capability of the presented method for driving control systems of industrial robots.

THE EQUIVALENT CIRCUIT AND CONTROL SYSTEM OF TRAVELLING WAVE TYPE ULTRASONIC MOTOR

从压电振子的等效电路出发，得到了行波型超声波电动机定子环乃至整个电动机的等效电路．分别对电机控制系统各组成部分进行了分析，并利用电机等效电路达到简化控制系统的目的．实验对研究结果进行了验证．

Controller Design for Induction and Brushless Motors Using Matlab with Digital Signal Processor (DSP)

The automation process is a very important pillar for Industry 4.0.One of the first steps is the control of motors to improve production efficiency and generate energy savings.In mass production industries,techniques such as digital signal processing(DSP)systems are implemented to control motors.These systems are efficient but very expensive for certain applications.From this arises the need for a controller capable of handling AC and DC motors that improves efficiency and maintains low energy consumption.This project presents the design of an adaptive control system for brushless AC induction and DC motors,which is functional to any type of plant in the industry.The design was possible by implementing Matlab software and tools such as digital signal processor(DSP)and Simulink.Through an extensive investigation of the state of the art,three models needed to represent the control system have been specified.The first model for the AC motor,the second for the DC motor and the third for the DSP control;this is done in this way so that the probability of failure is lower.Subsequently,these models have been programmed in Simulink,integrating the three main models into one.In this way,the design of a controller for use in AC induction motors,specifically squirrel cage and brushless DC motors,has been achieved.The final model represents a response time of 0.25 seconds,which is optimal for this type of application,where response times of 2e-3 to 3 seconds are expected.

Improved single-neuron PID controller for DC motor applied in robot system

An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.

Application of Diagonal Recurrent Neural Network toDC Motor Speed Control Systems

A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.

DECOUPLING CONTROL OF TWO MOTORS SYSTEM BASED ON NEURAL NETWORK INVERSE SYSTEM

In accordance with the characteristics of two motors system, the unitedmathematic model of two-motors inverter system with v/f variable frequency speed-regulating isgiven. Two-motor inverter system can be decoupled by the neural network invert system, and changedinto a sub-system of speed and a sub-system of tension. Multiple controllers are designed, and goodresults are obtained. Tie system has good static and dynamic performances and high anti-disturbanceof load.

LQ Speed Control of Pump Controlled Motor System

A linear quadric (LQ) optimal speed control algorithm is proposed for the speed control of a pump controlled motor hydraulic system. The control theme consists of optimal state feedback and disturbing compensation based on observation. The optimal state feedback bases on LQ cost function. The disturbing compensation is realized through reconstructing the state of load torque. A series of simulation are performed, and the results show that the control performance is satisfactory and can be maintained under changes of load torque.

Linearizing Control of Induction Motor Based on Networked Control Systems

A new approach to speed control of induction motors is developed by introducing networked control systems （NCSs） into the induction motor driving system. The control strategy is to stabilize and track the rotor speed of the induction motor when the network time delay occurs in the transport medium of network data. First, a feedback linearization method is used to achieve input-output linearization and decoupling control of the induction motor driving system based on rotor flux model, and then the characteristic of network data is analyzed in terms of the inherent network time delay. A networked control model of an induction motor is established. The sufficient condition of asymptotic stability for the networked induction motor driving system is given, and the state feedback controller is obtained by solving the linear matrix inequalities （LMIs）. Simulation results verify the efficiency of the proposed scheme.

Decoupling Control of 5 Degrees of Freedom Bearingless Induction Motors Using α-th Order Inverse System Method

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 α-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 bearinglees 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．

Current Search: Performance Evaluation and Application to DC Motor Speed Control System Design

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two powerful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the derivatives of the objective function is unnecessary for the proposed CS. To evaluate its performance, the CS is tested against several unconstrained optimization problems. The results obtained are compared to those obtained by the popular search techniques, i.e., the genetic algorithm (GA), the particle swarm optimization (PSO), and the adaptive tabu search (ATS). As results, the CS outperforms other algorithms and provides superior results. The CS is also applied to a constrained design of the optimum PID controller for the dc motor speed control system. From experimental results, the CS has been successfully applied to the speed control of the dc motor.

Application of Ultrasonic Motor to Control of Moment Gyroscope Gimbal Servo System

Attitude control system is one of the most important subsystems in a spacecraft.As a key actuator,the control moment gyroscope(CMG)mainly determines the performance of attitude control system.Whereas,the control accuracy and output torque smoothness of the CMG depends more on its gimbal servo system.Considering the constraints of size,mass and power consumption for a small satellite,here,a mini-CMG is designed,in which the gimbal servo system is driven by an ultrasonic motor.The good performances of the CMG are obtained by both the ultrasonic motor and the rotary inductosyn.The direct drive of gimbal improves its dynamic performance,with the output bandwidth above 20 Hz.The angular and speed closed-loop control obtains the 0.02°/s gimbal rate,and the output torque resolution better than 2×10^(-3) N·m.The ultrasonic motor provides 1.0N·m self-lock torque during power-off,with 12arc-second position accuracy.

LMI Approach to Robust H_∞/H_2 Controller Design with Regional Poles Constraint of a Pump-Motor System

The time domain guideposts requirements of a pump-motor system is transfered into a series of constraints which express the robust performance upper bound and regional poles limits of the closed loop system. Then the servo system control problem is transferred into the problem of robust performance optimizing under regional poles constrains described by linear matrix inequality （LMI）. These LMIs are easy to solve through the Matlab LMI-toolbox. Simulations indicate that the controller has excellent dynamic, static and disturbance rejection performance, and the control system is robust and has perfect H2 performance to the bounded external torque disturbance.

Intelligent Control Algorithm of PTZ System Driven by Two-DOF Ultrasonic Motor

It is difficult for the traditional pan-tilt-zoom(PTZ)system driven by electromagnetic motor to meet the growing demand for video surveillance system.The key challenge is high positioning accuracy,high dynamic performance and miniaturization of the PTZ system.Here a PTZ system driven by two degree-of-freedom obeliskshaped ultrasonic motor with single stator is presented,and its intelligent control algorithm is studied.The structure and driving mechanism of the presented PTZ system are analyzed by both simulation and experiment.To solve the complex nonlinear factors,e.g.time-variation,dead zone,the fuzzy PID control algorithm and the variable gain cross-coupled control strategy are combined to improve the control performance.The results show that the proposed algorithm has faster response,higher precision than traditional control algorithm,and it also has a good robustness to prevent the effect of interference.

Impaired motor control after sport-related concussion could increase risk for musculoskeletal injury:Implications for clinical management and rehabilitation

This review presents a conceptual framework and supporting evidence that links impaired motor control after sport-related concussion(SRC)to increased risk for musculoskeletal injury.Multiple studies have found that athletes who are post-SRC have higher risk for musculoskeletal injury compared to their counterparts.A small body of research suggests that impairments in motor control are associated with musculoskeletal injury risk.Motor control involves the perception and processing of sensory information and subsequent coordination of motor output within the central nervous system to perform a motor task.Motor control is inclusive of motor planning and motor learning.If sensory information is not accurately perceived or there is interference with sensory information processing and cognition,motor function will be altered,and an athlete may become vulnerable to injury during sport participation.Athletes with SRC show neuroanatomic and neurophysiological changes relevant to motor control even after meeting return to sport criteria,including a normal neurological examination,resolution of symptoms,and return to baseline function on traditional concussion testing.In conjunction,altered motor function is demonstrated after SRC in muscle activation and force production,movement patterns,balance/postural stability,and motor task performance,especially performance of a motor task paired with a cognitive task(i.e.,dual-task condition).The clinical implications of this conceptual framework include a need to intentionally address motor control impairments after SRC to mitigate musculoskeletal injury risk and to monitor motor control as the athlete progresses through the return to sport continuum.

Optimal Design of Multi-channel Water Cooled Radiator for Motor Controller of New Energy Vehicle

In order to improve the heat dissipation capability of motor controller for new energy vehicles,the water cooled radiator with multiple channels is optimized in this paper.The heat conduction between the heat source IGBT and the radiator,the convective heat transfer between the radiator and the coolant,the mechanical strength and the manufacturing cost are comprehensively considered during the optimization process.The power loss and thermal resistance of the IGBT unit are calculated at first,and finite element model of the radiator is established.On this basis,multi-physics coupling analysis of the water cooled radiator is carried out.Secondly,the sensitivity analysis is applied to verify the influence of structural parameters on the heat dissipation performance of the radiator system.The influence of coolant inlet velocity v,number of cooling ribs n,height of radiator ribs H on the maximum temperature rise T,the temperature difference ΔT between phase U and W,and the coolant pressure lossΔP are analyzed in depth,and the optimal range of the structural parameters for heat dissipation is obtained.Finally,an experimental platform was set up to verify the performance of the proposed structure of water cooled radiator for motor controller of new energy vehicle.The results show that the heat dissipation capability of the proposed radiator is improved compared with the initial design.

CAN-based Synchronized Motion Control for Induction Motors

A control area network （CAN） based multi-motor synchronized motion control system with an advanced synchronized control strategy is proposed. The strategy is to incorporate the adjacent cross-coupling control strategy into the sliding mode control architecture. As illustrated by the four-induction-motor-based experimental results, the multi-motor synchronized motion control system, via the CAN bus, has been successfully implemented. With the employment of the advanced synchronized motion control strategy, the synchronization performance can be significantly improved.