Motor Control Strategies Research Articles

Dynamic characteristics analysis of gear system with time-varying torque of motor and load based on motor control strategy

Dynamic characteristics analysis of gear system with time-varying torque of motor and load based on motor control strategy

Stepper motor open-loop control system modeling and control strategy optimization

Stepper motor open-loop control system modeling and control strategy optimization

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot.

The Influence of Maturity Status on Drop Jump Kinetics in Male Youth

Abstract Kumar, NTA, Radnor, JM, Oliver, JL, Lloyd, RS, CSCSD, Pedley, JS, Wong, MA, and Dobbs, IJ. The influence of maturity status on drop jump kinetics in male youth. J Strength Cond Res 38(1): 38–46, 2024—The aim of this study was to examine the effects of maturity status on drop jump (DJ) kinetics in young male athletes (categorized as early-pre–peak height velocity [PHV] [<−2.51 years], late-pre-PHV [−1.99 to −1.00 years], circa-PHV [−0.50 to 0.50 years], and post-PHV [>1.00 years]). All athletes performed a DJ from a 30-cm box onto force plates with performance variables (jump height, ground contact time, and reactive strength index) and absolute and relative kinetic variables during the braking and propulsive phases assessed. Subjects were categorized into GOOD (no impact-peak and spring-like), MODERATE (impact-peak and spring-like), or POOR (impact-peak and not spring-like) stretch-shortening cycle (SSC) function. The post-PHV group exhibited significantly greater values for most absolute kinetic variables compared with early-pre-PHV, late-pre-PHV, and circa-PHV (p < 0.05). The differences observed between consecutive maturity groups were similar in magnitude for most absolute variables (Cohen's d = 0.53–1.70). Post-PHV male athletes outperform their less mature counterparts during a DJ, and this may be attributed to the growth and maturity-related structural and motor control strategy changes that occur in children. Stretch-shortening cycle function in boys seems to improve with maturity status reflected by a greater number of post-PHV participants displaying GOOD SSC function (65.8%) and a greater number of early-pre-PHV participants displaying POOR SSC function (54.4%). However, a number of mature boys displayed POOR SSC function (17.8%), suggesting that the development of SSC function is not exclusively related to maturation.

An adaptive discretized RNN algorithm for posture collaboration motion control of constrained dual-arm robots.

Although there are many studies on repetitive motion control of robots, few schemes and algorithms involve posture collaboration motion control of constrained dual-arm robots in three-dimensional scenes, which can meet more complex work requirements. Therefore, this study establishes the minimum displacement repetitive motion control scheme for the left and right robotic arms separately. On the basis of this, the design mentality of the proposed dual-arm posture collaboration motion control (DAPCMC) scheme, which is combined with a new joint-limit conversion strategy, is described, and the scheme is transformed into a time-variant equation system (TVES) problem form subsequently. To address the TVES problem, a novel adaptive Taylor-type discretized recurrent neural network (ATT-DRNN) algorithm is devised, which fundamentally solves the problem of calculation accuracy which cannot be balanced well with the fast convergence speed. Then, stringent theoretical analysis confirms the dependability of the ATT-DRNN algorithm in terms of calculation precision and convergence rate. Finally, the effectiveness of the DAPCMC scheme and the excellent convergence competence of the ATT-DRNN algorithm is verified by a numerical simulation analysis and two control cases of dual-arm robots.

Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer.

Aiming at the problems of poor adjustment effect, weak anti-disturbance ability, and low robustness of the traditional sliding mode algorithm for permanent magnet synchronous motor speed sensorless, a permanent magnet synchronous motor speed observation method combining super-twisting sliding mode control algorithm and fuzzy control is proposed to accelerate the convergence speed of the system and improve the anti-disturbance ability. Fuzzy rules are used to solve the problem of obtaining the upper bound of the boundary function in the super-twisting algorithm. Moreover, the fuzzy algorithm is used to output the variable sliding mode gain instead of the fixed sliding mode coefficient to improve the system robustness and suppress the jitter. The simulation results show that the overshoot of the control system is 4%, the lag time is not more than 0.003 ms, the speed error is not more than 1%, and the response and adjustment time is not more than 0.02 s. The proposed control strategy improves the tracking accuracy and response speed of the system, suppresses the sliding mode chattering, and enhances the anti-interference ability of the system.

Active Disturbance Rejection Control Strategy for a Novel Wide-rotor Bearingless Switched Reluctance Motor

Active Disturbance Rejection Control Strategy for a Novel Wide-rotor Bearingless Switched Reluctance Motor

Sensorless control strategy for permanent magnet synchronous motor based on adaptive non-singular fast terminal sliding mode observer

Sensorless control strategy for permanent magnet synchronous motor based on adaptive non-singular fast terminal sliding mode observer

Research on intelligent control and sensor application strategy of motor based on RFID technology

Abstract People widely use permanent magnet brushless DC motors because of their simple structure, high operating efficiency, simple control, and easy maintenance. This paper constructs an EFID sensor network by merging EFID and sensor technologies and then designs the motor’s intelligent control system and strategy around it. In this paper, the SVR-PSO algorithm is used to localize the motor rotor, which nonlinear SVR trains to construct a nonlinear system of equations for calculating the position of the target tag, and then the PSO algorithm is used to seek the position coordinates of the target tag. The fuzzy PID is utilized to control the brushless DC motor, and the integral separation method is adopted to improve the control strategy. The SVR-PSO positioning algorithm and the improved fuzzy PID control strategy are applied and analyzed. For 12 tags to be measured, the positioning accuracy of SVR-PSO has improved by 56.8% compared to that of LANDMARC. Although SVR-PSO’s positioning algorithm is influenced by mutual coupling and multipath effects, the overall accuracy is still superior to that of LANDMARC. Based on the fuzzy PID controller optimized by the integral separation method, the motor rotational speed has a fast response, a small overshoot, and a small fluctuation of rotational speed, and can automatically regulate and restore stability under the situation of a sudden change of load. The motor speed response is fast, the overshoot is small, and the speed fluctuation is small, and the motor speed can be automatically adjusted and stabilized under the sudden load change, which has better dynamic and static performance than the traditional PID controller and fuzzy PID controller. The purpose of this paper is to provide a strategy reference for the use of RFID technology in the intelligent control of motors.

Novel Snap-Layer MMPC Scheme via Neural Dynamics Equivalency and Solver for Redundant Robot Arms With Five-Layer Physical Limits.

To obtain smoother kinematic control of minimum motion, a novel snap-layer minimum motion scheme, otherwise known as the minimum motion planning and control (MMPC) scheme for redundant robot arms, is proposed for the first time in this study. With the primary task of tracking planned paths and the consideration of satisfying five-layer physical limits, the snap-layer MMPC problem is transformed into a quadratic programming (QP) problem. Five-layer physical limits include angle-layer, velocity-layer, acceleration-layer, jerk-layer, and snap-layer limits, which are all considered and then transformed into a unified-layer bounded constraint through Zhang neural dynamics (ZND) equivalency. Furthermore, the snap-layer performance index and equation constraint are derived by utilizing the ZND formula. Therefore, the proposed snap-layer MMPC scheme is formulated as a standard QP that can avoid the potential physical damage of redundant robot arms. The snap-layer projection neural dynamics (PND) solver is presented and used to acquire the neural solution of the QP. Simulation results on a 6-degrees-of-freedom (DOF) planar redundant robot arm are presented to substantiate the effectiveness and superiority of the proposed snap-layer MMPC scheme by comparing it with the jerk-layer MMPC scheme and the minimum snap norm (MSN) scheme.

EMG Activity of Core and Global Muscles of Spine during Functional Exercises in Basketball Players with Chronic Ankle Instability: A Pilot Study

Introduction: Assessing the Electromyography (EMG) activity of core muscles during various exercises might be extremely important to understand the neuro-muscular strategies used by basketball athletes with Chronic Ankle Instability (CAI). Aim: To compare the EMG activity of the core/global muscles during different functional exercises in basketball athletes with versus without CAI. Materials and Methods: A pilot study was conducted in the Department of Physiotherapy, SGT University, Gurugram, Haryana, India. A total of eight basketball players subjects aged 18-30 years with (n=4) and without CAI (n=4) were recruited using convenience sampling. Players with atleast 2 years of competitive experience were enrolled. CAI was diagnosed if there was a history of atleast two ankle inversion injuries in the same ankle for the past 2 years, which had required a period of protected weight bearing or immobilisation or any complaint of giving way of the ankle during functional activities and score of less than 24 on the Cumberland ankle instability tool. Surface EMG was recorded for multifidus, rectus abdominis, transverse abdominis and erector spinae during six functional exercises (single leg squat, Y balance exercise, quadrant hop, toe touch down, box jump and medicine ball slams). 2×5×4 repeated measures Analysis of Variance (ANOVA) was employed to test the study hypothesis. Results: A significant difference was found between the activation patterns of the core and global muscles in basketball players with CAI and without CAI. Conclusion: It can be concluded that CAI alters the activation of core and global spinal muscles significantly. CAI is not restricted to distal joint but has an impact on proximal muscles as well. Neuromuscular training for the muscles, which alters motor control strategy because of CAI, could be taken into consideration when planning rehabilitation for CAI.

Personalized Alpha-Motoneuron Pool Models Driven by Neural Data Encode the Mechanisms Controlling Rate of Force Development.

The central nervous system employs distinct motor control strategies depending on task demands. Accordingly, the activity of alpha-motoneuron (MN) pools innervating skeletal muscle fibers is modulated based on muscle force and rate of force development (RFD). In human subjects, biophysical MN models enable inferring in vivo the neural processes (e.g., synaptic input, activity of the entire MN pool, etc.) underlying this modulation, which are otherwise challenging to measure experimentally. Due to unique neurophysiological characteristics of individuals, personalizing these models is essential to study motor control in humans. Therefore, this work studied the mechanisms involved in the modulation of RFD using person-specific MN pool models driven by in vivo common synaptic input estimates (i.e., derived from surface high-density electromyography). Specifically, we assessed how in vivo MN activity changed across RFD and muscle force. This included modulation of recruitment and rate coding in the complete MN pool, as well as model-based estimates of excitatory synaptic gains ( ∆ IF). We found RFD-specific changes in MN activity associated to changes in ∆ IF. Moreover, we showed that MN pool models driven by RFD-specific ∆ IFs reproduced in vivo MN firing features and associated force profiles at different RFDs. Altogether, this work represents a step towards modelling the mechanisms of force generation in humans and creating person-specific models of the spinal circuitry. This will open a window for studying in vivo human neuromechanics and motor restoring interventions.

Collective Neural Dynamics for Sparse Motion Planning of Redundant Manipulators Without Hessian Matrix Inversion.

Redundant manipulators have been widely used in various industries whose applications not only improve production efficiency and reduce manual labor but also promote innovation in robotics and artificial intelligence. Kinematic control plays a fundamental and crucial role in robot control. Over the past few decades, numerous motion control schemes have been proposed and applied to trajectory tracking tasks. However, most of these schemes do not consider the introduction of sparsity into the motion control of redundant manipulators, resulting in excessive joint movements, which not only consume extra energy but also increase the risk of unexpected collisions in complex environments. To solve this problem, we transform the issue of increasing the sparsity into a nonconvex optimization problem. Furthermore, a collective neural dynamics for sparse motion planning (CNDSMP) scheme for motion planning of redundant manipulators is proposed. By incorporating sparsity into the control scheme, the excessive joint movements are minimized, leading to improved efficiency and reduced collision risks. Through simulations, comparisons, and physical experiments, the effectiveness and superiority of the proposed scheme are demonstrated.

Cascade motion control with synchronised saturation

This paper introduces an innovative motion control scheme tailored for traction systems, employing a cascade PI controller architecture. The internal loop regulates speed, and the external loop generates the necessary speed setpoint for position control. Two feedforward actions are strategically implemented in each loop to address potential disturbances and optimise overall performance. An inherent challenge in cascade control systems is the phenomenon known as windup, where integral components accumulate errors due to persistent disturbances or sudden changes in position reference. In order to mitigate this phenomenon, a control approach which integrates corresponding saturations for each loop and ensures synchronisation between them is developed. In this way, the external loop does not generate speed setpoints beyond physical thresholds during internal loop saturation. This strategic limitation prevents overly aggressive responses and eliminates undesired traction demands during saturation events. The proposed control scheme is validated through simulations that incorporate various disturbances, and the analysis of results confirms its suitability, showcasing improvements in the performance of such control schemes, especially in scenarios prone to windup.

A New Active Motion Control Strategy for Built-in Wave Energy Converter of Ocean Data Buoys

A New Active Motion Control Strategy for Built-in Wave Energy Converter of Ocean Data Buoys

A Deep Reinforcement Learning-Based Decentralized Hierarchical Motion Control Strategy for Multiple Amphibious Spherical Robot Systems With Tilting Thrusters

A Deep Reinforcement Learning-Based Decentralized Hierarchical Motion Control Strategy for Multiple Amphibious Spherical Robot Systems With Tilting Thrusters

Direct electromagnetic force control of linear induction motor with end effects using fuzzy controller

In this article is a present dynamic model of a linen induction motor with end effects, occurs when the electromagnetic system of the motor is open. Instead of the angular speed and electromagnetic torque as a rotation motor, in the linear induction motor we have linear speed and linear electromagnetic force, which are sufficiently influenced by the open electromagnetic system of the primary and secondary elements of the linear motor. The choice of an appropriate control system for a linear induction motor is of particular importance considering the use of this type of motor in manufacturing. There are different types of control schemes for standard rotary motors that have their own advantages and disadvantages. When choosing a motor control scheme, we strive to achieve the following parameters, such as smoothness of regulation, ability to regulate in all four quadrants, accuracy of regulation, range of regulation and last but not least, simplicity of regulation. One such method that meets these criteria for rotary motors is the direct torque control method with space vector modulation. The control system of the linear induction motor proposed in this paper is based on this method, taking into account the open electromagnetic system and the occurrence of the end effects of the linear induction motor. Instead of the angular reference velocity as a rotary motor, in this case we have a linear reference velocity to the input, which is compared to the current linear velocity of the motor. The present paper also uses the vector modulation method by analogy with direct torque control with space vector modulation of the rotary motor. For the conversion of a linear velocity to a linear electromagnetic force, instead of a standard PI controller, it is using a fuzzy controller to convert a linear velocity to a reference electromagnetic force.

Elastic Resistance and Shoulder Movement Patterns: An Analysis of Reaching Tasks Based on Proprioception.

This study departs from the conventional research on horizontal plane reach movements by examining human motor control strategies in vertical plane elastic load reach movements conducted without visual feedback. Here, participants performed shoulder presses with elastic resistances at low, moderate, and high intensities without access to visual information about their hand position, relying exclusively on proprioceptive feedback and synchronizing their movements with a metronome set at a 3 s interval. The results revealed consistent performance symmetry across different intensities in terms of the reach speed (p = 0.254-0.736), return speed (p = 0.205-0.882), and movement distance (p = 0.480-0.919). This discovery underscores the human capacity to uphold bilateral symmetry in movement execution when relying solely on proprioception. Furthermore, this study observed an asymmetric velocity profile where the reach duration remained consistent irrespective of the load (1.15 s), whereas the return duration increased with higher loads (1.39 s-1.45 s). These findings suggest that, in the absence of visual feedback, the asymmetric velocity profile does not result from the execution of the action but rather represents a deliberate deceleration post-reach aimed at achieving the target position as generated by the brain's internal model. These findings hold significant implications for interpreting rehabilitation approaches under settings devoid of visual feedback.

Flow match and precision motion control of asymmetric electro-hydrostatic actuators with complex external force in four-quadrants

Asymmetric Electro-hydrostatic actuators (EHAs) have been widely applied in the aerospace and manufacturing industries owing to their small installation space. However, some challenges must be considered in precision control. First, a deficient or excess flow rate forms in the closed hydraulic circuit because of the different piston areas between the cap and rod sides of the asymmetric actuators. In addition, a complex external force, which is difficult to measure directly, always emerges and declines the control performance when EHAs are operated. In this study, a modified hydraulic circuit and an integrated flow-matching valve were developed to address the mismatched flow rate. Subsequently, a high-performance motion control scheme was proposed based on the extended state observer (ESO) and backstepping method. Within this controller, the forward dynamic compensation was designed in terms of the four-quadrant flow compensation model. Meanwhile, the nonlinear gain and updated law of compensations for observer error were synthesized to suppress tracking errors. Comparative experiments demonstrated the higher precision tracking performance of the proposed motion controller in all four quadrants.

Integrated optimization of the in-wheel motor driving system considering the ride comfort of the electric vehicle under multiple operating conditions

In this paper, a multi-objective optimization scheme integrating structural parameters with control parameters is proposed to address the adverse effects of an unbalanced magnetic pull of the wheel motor on vehicle dynamics. Firstly, the unbalanced magnetic pull under the air gap eccentricity of a switched reluctance motor is analyzed using both Maxwell’s stress method and the principle of virtual displacement. Then, a current chopper control strategy for the in-wheel motor is developed, and the influence of relevant control parameters on the output characteristics of the motor driving system under different driving conditions is discussed. Finally, a multi-objective optimization model of a motor under multiple operating conditions is developed with the aid of multidisciplinary optimization software. Integration of structural and control parameters for optimization. The results show that the motor design parameters determined by the integrated optimization scheme can improve the vehicle’s response characteristics under a wide range of operating conditions. In particular, the negative effect caused by an unbalanced magnetic pull during the operation of the vehicle is greatly suppressed.