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Summary: The low switching frequency in high‐power motor drives is mandatory for reducing thermal stress on power devices but often results in significant current harmonics. Synchronized space vector modulation (SynSVM), a widely used low‐carrier‐ratio PWM strategy, offers a simple implementation and reduced harmonics. However, implementing SynSVM in traditional AC motor current regulation poses challenges due to fixed voltage samples. To address this, a high‐performance control scheme based on SynSVM is proposed in this manuscript. It ensures the stator flux vector follows a predefined trajectory by integrating voltage pulses from the original SynSVM. The basic voltage vector switching is facilitated through high‐frequency monitoring and compensation of torque and flux errors, resulting in a fast torque response. Furthermore, synchronized and symmetrical voltage pulses, inherent in the original SynSVM, are equivalently generated, to effectively mitigate current harmonics. This proposed method liberates designers from the complexities of current regulation based on SynSVM. Both simulations and experiments validate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a saturation-optimized, quasi-sliding-mode model-free adaptive control (SM-MFAC) method to control the postcollision calming motion of an unstable free-flying space robot with saturated output torque. Initially, the dynamics model of the unstable free-flying space robot is transformed into a class of multiple-input, multiple-output (MIMO) discrete-time nonlinear systems. Here, the system characteristics can be estimated based on measured base attitude and joint angle data. The discrete sliding-mode control helps calculate the desired angular velocity at the current moment. Next, Hildreth's method is used to introduce constraints to the control input criterion function for real-time tracking of the desired angular velocity, which enables the completion of the calming motion control of the free-flying space robot. The proposed algorithm simplifies the traditional calming motion control process by avoiding complex and redundant modeling requirements, ensuring that the control torque remains within predefined limits to optimize possible saturation. It also proves the convergence of the system output theoretically, and good stability and dynamic characteristics of the control scheme are verified through numerical simulations. [ABSTRACT FROM AUTHOR]

Contactless microscale tweezers are highly effective tools for manipulating, patterning, and assembling bioparticles. However, current tweezers are limited in their ability to comprehensively manipulate bioparticles, providing only partial control over the six fundamental motions (three translational and three rotational motions). This study presents a joint subarray acoustic tweezers platform that leverages acoustic radiation force and viscous torque to control the six fundamental motions of single bioparticles. This breakthrough is significant as our manipulation mechanism allows for controlling the three translational and three rotational motions of single cells, as well as enabling complex manipulation that combines controlled translational and rotational motions. Moreover, our tweezers can gradually increase the load on an acoustically trapped cell to achieve controllable cell deformation critical for characterizing cell mechanical properties. Furthermore, our platform allows for three-dimensional (3D) imaging of bioparticles without using complex confocal microscopy by rotating bioparticles with acoustic tweezers and taking images of each orientation using a standard microscope. With these capabilities, we anticipate the JSAT platform to play a pivotal role in various applications, including 3D imaging, tissue engineering, disease diagnostics, and drug testing. The joint subarray acoustic tweezer platform offers 3D translation and rotation of bioparticles, enabling complex manipulation and cell deformation, with applications in tissue engineering, disease diagnostics, and drug testing. [ABSTRACT FROM AUTHOR]

In this paper, an energy-saving scheme in rotor field-orientated vector control is developed for induction motor drives. The energy-saving scheme minimizes copper and core losses in induction motors, which are equally applicable to induction generators. In efficiency optimization, an optimal stator angular velocity is uniquely obtained, and consequently, a corresponding optimal slip at any given rotor speed is determined. The challenge of determining a reference for rotor flux linkage that guarantees the minimal copper and core loss regime is overcome by developing a load torque observer loop. The torque observer is developed alongside a rotor speed observer for a sensorless speed operation. The observed mechanical torque is further used to enhance the outer-loop rotor speed control that generates an electromagnetic torque command used in building the reference for the inner-loop stator current control. The results obtained justified the effective operation of the torque and rotor speed observer, which consequently verified the effective minimal electrical loss regime at the optimal stator angular velocity and optimal rotor flux linkage. The results are further compared to results obtained from the equivalent induction machine drive on a finite-set model predictive control (FS-MPC) scheme with the same values of the optimal stator angular velocity and optimal rotor flux linkage. The developed efficiency-optimized vector control scheme gave lower ripples in developed electromagnetic torque and dampened overshoot better during step change in load torque. [ABSTRACT FROM AUTHOR]

Spin-orbitronics, exploiting electron spin and/or orbital angular momentum, offers a powerful route to energy-efficient spintronic applications. Recent research on orbital currents in light metals broadens the scope of spin-orbit torque (SOT). However, distinguishing and manipulating orbital torque in heavy metal/ferromagnet (HM/FM) remains a challenge, limiting the promising synergy of spin and orbital currents. Here, we design a HM/FM/FMSOC heterostructure and experimentally separate orbital torque contribution from spin torque by utilizing the distinct diffusion length of spin and orbital currents. Furthermore, we achieve the synergy of spin and orbital torques by controlling their relative strength, and obtain a 110% improvement in torque efficiency compared to the representative Pt/Co bilayer. Our findings not only contribute to a deeper understanding of SOT mechanisms and orbital current transport in HM/FM multilayers, but also highlight the promising prospect of orbital and spin torque synergy for optimizing the efficiency of next-generation spintronic devices. Eliminating the interference of spin current to distinguish and manipulate orbital torque in heavy metal/ferromagnet (HM/FM) heterojunction remains a challenge. Here, the authors design a HM/FM/FMSOC multilayer to separate orbital torque contribution and harness the synergy of spin and orbital currents for enhanced spin-orbit torque. [ABSTRACT FROM AUTHOR]

This article investigates the trajectory tracking control problem for wheeled mobile robot (WMR) subject to both velocity and torque constraints. Firstly, a more general model is established by considering the displacement between the centre of mass and the midpoint of the driving wheels of the WMR, based on which, a new bounded kinematic controller is proposed by combining the first-order filtering approach to keep the trajectory tracking error asymptotically stable. Then the dynamic controller is designed and the stability of the overall closed-loop system is proved by the Lyapunov stability theory and Barbalat's lemma. Some conditions are given to ensure that both the velocity constraints and torque constraints are satisfied. Finally, some numerical examples are given to show the effectiveness and advantages of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

A novel direct instantaneous torque control (DITC) strategy based on optimized conduction angle is proposed with the aim of reducing the torque ripple of permanent magnet-assisted switched reluctance motor (PMa-SRM) during the two-phase exchange (TpE) region in this paper. Firstly, according to the inductance characteristics, the TpE region is subdivided into TpE I and TpE II region where the turn-off angle is acted as the region separation point, and the corresponding torque hysteresis strategies are formulated in different regions. Secondly, K-fold extreme learning machine (ELM) method is used to optimize the turn-on angle in order that the current of incoming phase can quickly increase to maintain torque balance. In order to make full use of the ability of torque generation of two adjacent phases, the position where the torque of adjacent phases is equal is used as the turn-off angle of incoming phase. Finally, a 6/20 PMa-SRM prototype is simulated and verified. Compared with the conventional DITC strategy, the novel strategy not only diminish torque ripple and negative torque under different operating conditions, but also expands the operating range of the motor and improves the motor efficiency. [ABSTRACT FROM AUTHOR]

Aiming at the torque ripple caused by significant current ripple and non‐ideal back‐electromotive force (back‐EMF) of coreless brushless DC motor (BLDCM), an incremental predictive control strategy based on unipolar pulse width modulation (PWM) is proposed in the non‐commutation interval. Firstly, the unipolar PWM scheme is used to double the current ripple frequency, which can reduce the current ripple. On this basis, the current prediction equations of adjacent control periods are subtracted to obtain the incremental current prediction equation, and the influence of non‐ideal back‐EMF on torque ripple suppression is eliminated. Finally, combined with the author's previous research on the commutation torque ripple suppression strategy, an integrated suppression strategy for non‐commutation and commutation interval is proposed. The experimental results show that, compared with the PI control strategy, the total torque ripple of the proposed strategy is reduced to less than 35%, and the current ripple is reduced. Meanwhile, the commutation time is shortened, and the advantages of coreless motor rapid response are retained. The strategy is universal, not limited by motor parameters and operating conditions, and has theoretical and engineering value. [ABSTRACT FROM AUTHOR]

Background: The aim of the investigation was to evaluate if the inclination of the lower anterior teeth can be controlled reliably after lower premolar extraction for Class III camouflage treatment with completely customized lingual appliances (CCLAs). Treatment outcome was tested against the null hypothesis that lower premolar extractions for non-surgical camouflage treatment of a Class III malocclusion will lead to further compensation by retroclining mandibular incisors during CCLA treatment. Methods: This retrospective study included 25 patients (f/m 12/13; mean age 20.7 years, SD 9.5 years) with uni- or bilateral Class III molar relationship and a Wits value of ≤ -2 mm. In all consecutively debonded patients, lower premolars were extracted to correct the sagittal relationship with a non-surgical camouflage approach. Lateral head films prior to (T1) and at the end of lingual orthodontic treatment (T2) were used to evaluate skeletal and dentoalveolar effects. A paired t-test with alpha = 5% was used to define differences between the endpoints. The linear correlation between the inclination of the mandibular incisors at T1 and the achieved correction was measured with the Pearson correlation coefficient (PCC). A Schuirmann's TOST equivalence test was used to check if the final lower incisor inclination was within the defined norms. Results: The null hypothesis was rejected as the mean lower incisor inclination was improved by 1.8° despite lower premolar extractions (T1: 86.8°/ T2: 88.6°). There was a strong correlation (-0.75) between the lower incisor inclination at T1 and the achieved correction indicating a controlled correction towards the norm regardless of the initial incisor position. At T2, the interincisal angle as well as the lower incisor inclination were within the norm. Conclusion: Lower premolar extractions for non-surgical camouflage treatment of a Class III malocclusion will not lead to undesired retroclining of mandibular incisors during CCLA treatment even in severe cases. [ABSTRACT FROM AUTHOR]

The generation of sustainable energy through wind and hydrokinetic turbines, which convert the kinetic energy from fluid flows into mechanical energy, presents an attractive solution for diversifying the country energy matrix in response to climate change. Consequently, numerous studies have investigated the aerodynamic and hydrodynamic behaviors of various wind and hydrokinetic turbines using numerical simulations to understand their interaction with the surrounding fluid flows and enhance their performance. However, to validate these studies and aiming at improving the turbine design, experimental studies on a laboratory scale employing wind tunnels and hydraulic channels are essential. This work addresses the development and implementation of a reliable control system for experimentally evaluating the power coefficient (Cp) versus the tip speed ratio (TSR) curve of wind and hydrokinetic turbines. The control system, based on a DC motor acting as a generator and aligned with a commercial torque sensor, enables a precise control over the experimental setup. By obtaining and comparing the experimental performance curves of Cp versus TSR for both wind and hydrokinetic turbines with numerical results, the effectiveness and accuracy of the developed control system are demonstrated. A satisfactory fit between numerical and experimental results was achieved, underscoring the utility and reliability of the control system for assessing the turbine performance. [ABSTRACT FROM AUTHOR]

This paper proposes a method for the torque ripple reduction of an open-end winding interior permanent magnet synchronous motor (OEW-IPMSM) using direct self-control (DSC). The conventional DSC has been researched in high-power systems because of its advantages in terms of a low switching frequency and a fast response of torque. Nevertheless, high torque ripple is a disadvantage of the conventional DSC. This is because the trajectory of the stator flux is controlled in the shape of a hexagon for lower switching frequencies and by applying hysteresis torque control. In this paper, predictive torque control using a mathematical model of an OEW-IPMSM is presented to improve the quality of the torque control. In addition, the presented method addresses the trajectory control of the flux using the diverse voltage vectors of the dual inverter. The validity of the presented method is demonstrated by simulations and experimental results. [ABSTRACT FROM AUTHOR]

A new dual‐motor servo steering system with improved reliability and safety is proposed. But, despite the advantages of the proposed servo system, it is strongly coupled, non‐linear and multivariable, where the biggest challenge lies in its tracking and synchronization control. To improve the tracking and synchronization control performance of the proposed servo system, a tracking and synchronization control strategy based on backstepping super‐twisting control and multi‐level differential coupling is presented. First, a parallel model of the dual‐motor is established. Then, backstepping and super‐twisting control algorithms are integrated while adaptively optimizing key parameters to ensure the robustness and tracking performance of each motor. After that, an angular synchronization controller with multi‐level differential coupling and backstepping super‐twisting algorithm is proposed to compensate for the synchronization error of the dual‐motor system caused by parameter uncertainty. Finally, the simulation is carried out using Simulink to verify the effectiveness of the proposed control strategy. This paper proposes an adaptive multi‐level differential coupling control strategy to improve the synchronization accuracy of dual motors under external loads and disturbances by integrating the global backstepping theory and the super twisting theory. [ABSTRACT FROM AUTHOR]

Delta parallel robot is widely used in the high-speed sorting industry with a light load and constant load. Its motion control is based on kinematic planning, without considering the influence of load and disturbance. The gangue sorting robot has the characteristics of a large load and random mass change, so traditional kinematics planning can not meet the control requirements. A fuzzy adaptive robust control algorithm is proposed to solve the problems of unstable motion and jitter in the coal gangue sorting robot. By establishing the mathematical model of the fuzzy system, the uncertain terms of the dynamic parameters caused by the random changes in the load are approximated. At the same time, to reduce the number of fuzzy rules and the amount of fuzzy calculation, the uncertain terms are decomposed into velocity terms and acceleration terms and then approximated, respectively. The Lyapunov analysis of the system is carried out, and the convergence of the system is proved. The simulation results show that the fuzzy adaptive robust control algorithm has a smaller error and faster convergence compared with the computational torque control algorithm when the system is sorting gangue within 8 kg, which improves the stability of gangue grasping. [ABSTRACT FROM AUTHOR]

This article presents a cooperative controller that is specifically designed to enhance the stability of a distributed-drive vehicle during steering. The controller focuses on improving lateral stability during steering and achieving optimal torque allocation to meet numerous objectives. The article proposes a novel approach to improve the performance of the sliding mode controller for transverse stability control during steering. This is achieved by designing a fractional-order non-singular fast terminal sliding mode surface function, a fractional-order double-power exponential convergence law, and introducing a weighted integration term. Furthermore, the vehicle's torque was fine-tuned by employing an ant colony optimization (ACO) technique within the acceptable range defined by the lateral and longitudinal control requirements. To prevent the ACO algorithm from being stuck in local optima, a pseudo-random rule was implemented based on the original state transfer probability. This rule helps accelerate the convergence of the algorithm. Additionally, an elite approach and a dynamic change strategy for pheromone concentration were devised. Ultimately, the performance of the co-controller that was built is evaluated by simulation experiments conducted under both accelerated and decelerated driving situations. The test findings indicate that the technique effectively improves the lateral stability, tracking control, and energy economy of electric cars, with promising potential for practical use. [ABSTRACT FROM AUTHOR]

• A linear model-based controller is designed for the CEACS attitude regulation. • Takagi-Sugeno fuzzy model with parallel distribution approach has been used. • The fuzzy-MPC controller achieves the desired CEACS attitude pointing accuracy. • A replica of the fuzzy MPC controller is designed by using deep layer neural network (D-FMPC). • The D-FMPC controller performs equally well as FMPC controller but significantly reduces computational burden. Combined Energy and Attitude Control System (CEACS) reduces the size and mass budgets of typical satellites and consequently, increases their payload capacity. CEACS uses flywheels for a dual purpose, i.e., as both energy storage and attitude control device. This maiden work attempts to introduce a novel Deep-Learning capability of the fuzzy-Model Predictive Control (FMPC) controller for CEACS. The design approach for the fuzzy-MPC controller uses the Takagi-Sugeno (T-S) fuzzy model of satellite attitudes and computes the control torque through a parallel distribution compensation (PDC) approach. However, the MPC controller offers a high computational burden, and it becomes a significant problem for smaller satellites having limited computational power. Therefore, in this research work, a novel Deep-Learning-based fuzzy-MPC controller (D-FMPC) is designed for the CEACS attitude regulation subject to higher initial angles, actuator constraints, parametric uncertainties, and external disturbance torques. Here, the deep-layer neural network is trained offline with the MPC controller data to replicate the FMPC controller, thus ensuring its controllability. Numerical results validate that the D-FMPC controller successfully mimics the FMPC controller and produces the desired pointing accuracy effectively with smooth transient response and without violating the attitude control actuator constraints. The results also validate that the D-FMPC controller offers significantly reduced computational burden than the FMPC controller. Therefore, the novel Deep-Learning solution provides a feasible platform for applying more complicated and sophisticated attitude control techniques for the CEACS attitude regulation in small satellites as an example. [ABSTRACT FROM AUTHOR]

Space robots can assist astronauts in accomplishing a variety of space missions in high-risk environments. As spacecraft become increasingly lightweight, large-scale, and integrated, space robots are a type of large-scale robots with flexible links and flexible joints. However, the flexibility of the components complicates robot modeling and controller design. Therefore, to address the issue of stable trajectory tracking for multi-flexible space robots, a dynamics model of space robots with multiple flexibilities is established, and a composite controller is designed to enhance control stability. In modeling, comprehensively considering the rigid joints, joint flexibility and link flexibility, the kinematics is consistently described by using the component deformation matrix and recursive method. An accurate dynamics model is established by Lagrange's equations. In control, using fuzzy neural network sliding mode control, a rigid subsystem controller is designed to suppress the system jitter caused by sudden parameter changes. And it implements the robust tracking of the robot trajectory. Meanwhile, the weighted average fuzzy controller is designed to control the link deformation. The regulation of the flexible joint by the fast feedback controller is implemented using the virtual torque feedback control. Finally, the validity of the dynamics and control models is verified using Matlab and Adams. Compared with previous studies, this study considers multiple flexibility factors more fully. The vibration of multiple flexible components is suppressed during the stable trajectory tracking of the robot. [ABSTRACT FROM AUTHOR]

This contribution examines the control problem for very large wind energy converters during shutdown operation and analyses the most important control approaches. The control methods make use of the built-in conventional control infrastructure, but control system reconfigurations are undertaken in order to meet the demands of the shutdown control operation. Hence, the torque controller as well as the collective pitch controller (CPC) are redesigned from their regulator functions to reference tracking control systems with constraints. In addition, the CPC is combined with a feedforward controller in order to gain responsiveness. Constraints in magnitude and rate are managed by a modified anti-windup mechanism. Simulations of a 20 MW reference wind turbine verify the performance of the approaches. [ABSTRACT FROM AUTHOR]

This article starts from the premise that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) control strategy, is characterized by the fact that the internal flux and torque control loop usually uses ON–OFF controllers with hysteresis, which offer easy implementation and very short response times, but the oscillations introduced by them must be cancelled by the external speed loop controller. Typically, this is a PI speed controller, whose performance is good around global operating points and for relatively small variations in external parameters and disturbances, caused in particular by load torque variation. Exploiting the advantages of the DTC strategy, this article presents a way to improve the performance of the sensorless control system (SCS) of the PMSM using the Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead–Lag under constant flux conditions. Sliding Mode Control (SMC) and FOSMC are proposed under conditions where the flux is variable. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system performs better is verified. The article also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance for the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional-Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM-SCS based on the DTC strategy in a complete Hardware-In-the-Loop (HIL) implementation. [ABSTRACT FROM AUTHOR]

The Finite Control Set-Predictive Torque Control (FSC-PTC) is a practical and intuitive method to control an Induction Motor (IM). However, the challenge of this technique is the difficulty of tuning the weighting factor so that it performs optimally at all speeds. Hence, this paper proposes a new method for improving the optimization technique by automatically tuning the weighting factor using a flux controller. The flux controller is represented as a DC gain and designed to be proportional to the absolute value of the predicted stator flux error. This method eliminates the need for complex computation to select the suitable weighting factor while also efficiently regulating flux and torque. The proposed method is experimentally validated on a DS1104 controller board and compared to a constant flux weighting factor method that was tested under speed conditions. The results demonstrate that the new method can further decrease the torque ripple compared to the constant weighting factor while maintaining the flux ripple and harmonic distortion limits. [ABSTRACT FROM AUTHOR]

This work is an overview of one of the renewable energy sources, wind power. The high cost of testing wind turbines and analyzing their characteristics in research laboratories prompted us to create the Wind Emulator. In this article, we will proceed with the development of an emulator of a wind turbine conversion chain based on an asynchronous machine. This emulator would be capable of faithfully reproducing the dynamic characteristics of a real wind turbine and of integrating them optimally into a real electrical system so as to be able to study its operation at laboratory level, so our objective is to have an emulator that will provide the characteristics (speed-torque-current) in real time and with realistic conditions. Our development approach is based on the use of two classical control strategies under the MATLAB/Simulink closed-loop environment: direct torque control (DTC) and indirect rotor flux vector control (IRFOC) in dynamic and static regimes. The simulation results presented and discussed in this work enable us to determine the operating limits of our proposed wind emulator, in order to validate the most suitable emulator model. Ultimately, this model will be integrated into an intelligent computing board such as the DSP1104. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the issue of distributed finite‐time attitude coordination control of spacecraft formations with multiple constraints on angular velocities and control torques. First, the multiple constrained problem is transformed into a bounded issue by virtue of the nonlinear transformation technique and an input saturation model. Next, the nearest neighbor rule is applied to deal with the problem of the unavailability of the leader's information to all followers. Then, a distributed attitude coordination control algorithm is derived to enforce that all attitude tracking errors can converge to a neighborhood around the origin in finite time even when there exist multiple constraints and external disturbances imposed on spacecraft systems. Finally, several numerical simulation examples are presented to illustrate the efficiency of the derived method. [ABSTRACT FROM AUTHOR]

Since aircraft icing will decrease the ability of aircraft to generate lift, it is significant to consider the aircraft deicing problem. The paper presents an aircraft deicing method based on the cracking of the ice layer caused by the large deformations of wings. To describe the deformation of wings, the absolute coordinate-based formulation is used. The aircraft with high aspect ratio wings is simplified as a hub-beam system. Such a rigid-flexible system with the fast rotation speed of hub and the large deformation of the beam is modeled using absolute coordinate-based formulation accurately. The maneuver of the rigid body will lead to the large deformation of wings to do the de-icing. Numerical examples are presented to reveal that the maximum tensile strength on the wing surface with sinusoidal control torques with some amplitudes and frequencies is larger than the ice's tensile strength. Hence, the proposed de-icing method based on the aircraft maneuvering is potential. [ABSTRACT FROM AUTHOR]

The use of electric automobiles, or EVs, is essential to environmentally conscious transportation. Battery EVs (BEVs) are predicted to become increasingly accepted for passenger vehicle transportation within the next 10 years. Although enthusiasm for EVs for environmentally friendly transportation is on the rise, there remain significant concerns and unanswered research concerns regarding the possible future of EV power transmission. Numerous motor drive control algorithms struggle to deliver efficient management when ripples in torque minimization and improved dependability control approaches in motors are taken into account. Control techniques involving direct torque control (DTC), field orientation control (FOC), sliding mode control (SMC), intelligent control (IC), and model predictive control (MPC) are implemented in electric motor drive control algorithms to successfully deal with this problem. The present study analyses only sophisticated control strategies for frequently utilized EV motors, such as the brushless direct current (BLDC) motor, and possible solutions to reduce torque fluctuations. This study additionally explores the history of EV motors, the operational method between EM and PEC, and EV motor design techniques and development. The future prospects for EV design include a vital selection of motors and control approaches for lowering torque ripple, as well as additional research possibilities to improve EV functionality. [ABSTRACT FROM AUTHOR]

Traditional model predictive torque control (MPTC) predicts the torque and flux values for the next time step and selects the voltage vector that minimizes the cost function as the optimal vector to apply to the inverter. This control approach is straightforward and allows for multi-objective control, but it has some issues in terms of the dynamic steady-state performance and parameter robustness. Therefore, this paper proposes a weightless model predictive control method based on an extended state observer (ESO). By designing an improved ESO to observe and compensate for motor parameter disturbances in real time, and employing a novel 2-D switching table and voltage vector sector selection diagram, the method evaluates three out of eight voltage vectors based on the torque and stator flux error signals. This reduces the computational load while increasing the number of candidate voltage vectors. Finally, a cost function without weighting factors is designed to lower the computational complexity. The simulation results show that the proposed new control method effectively reduces the torque and flux ripple and improves the current waveform compared to traditional MPTC. [ABSTRACT FROM AUTHOR]

Aiming at the problems of jittering waveforms and poor power quality caused by external disturbances during the operation of a dual-pulse-width-modulation (PWM) converter, an improved terminal sliding mode control and an improved active disturbance rejection control (ADRC) are investigated. The method is based on mathematical models of grid-side and machine-side converters to design the controllers separately, and the balance between the two sides is maintained by the capacitor voltage. An improved terminal fuzzy sliding mode control and equivalent input disturbance (EID)-error-estimation-based active disturbance rejection control are presented on the grid side to improve the voltage response rate, and an improved support vector modulation (SVM)–direct torque control (DTC)–ADRC method is developed on the motor side to improve the robustness against disturbances. Finally, theoretical simulation experiments are built in MATLAB R2023a/Simulink to verify the effectiveness and superiority of this method. [ABSTRACT FROM AUTHOR]

This manuscript presents a novel control approach for Permanent Magnet Synchronous Motors (PMSMs) by integrating the widely used Direct Torque Control (DTC) method with Deep Reinforcement Learning (DRL), specifically the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The TD3 algorithm is well-suited to address the challenges posed by high-dimensional state and action spaces in PMSM drives. The conventional Proportional–Integral (PI) controller in the outer loop of DTC is replaced with the DRL based TD3 agent to overcome the limitations of traditional PI controllers, such as model dependency and complex parameter tuning. The DRL technique allows the agent to learn optimal control policies from experience, making it suitable for complex and nonlinear control problems. Extensive simulation studies demonstrate the effectiveness of the TD3-based control in achieving accurate speed tracking under varying operating conditions. Real-time experimental validation using a TMS320F28379D digital signal processor confirms the feasibility of the proposed DRL based approach. The research offers new insights into improving the performance of PMSM drives and paves the way for future advancements in electric drive control. [ABSTRACT FROM AUTHOR]

The uncontrollable angles (UAs) in direct torque control (DTC) algorithm is an important issue through which the effects of voltage vectors (VEs) on the magnetic flux and the torque are accurately determined. In this paper, a unique analysis of UAs is performed at different operating conditions, including parameters variations in two different strategies: Direct torque and stator flux control (DTC_SC) and (DTC_RC). Values of Those angles were accurately determined for wide speed, stator and rotor variations, and load changes. In addition, a detailed numerical comparison was performed in terms of these angles in the two strategies mentioned above for each operating condition. The comprehensive comparison showed the superiority of the DTC_RC strategy over its DTC_SC counterpart, being the maximum values of UAs in DTC_RC were 8°, 33°, and 21° versus 15°, 45°, and 38° in DTC_RC strategy for the following operations: Variable speed with variable stator resistance, variable speed with variable stator and rotor resistances, variable speed with variable load, respectively. MATLAB/Simulink results of the contributed analysis and comparisons were accomplished and validated. In addition, DS1103‐based experimental tests supported and verified the theoretical analysis. [ABSTRACT FROM AUTHOR]

Direct torque control is the most appropriate strategy for induction motor drive systems due to its considerable ability to reduce the impact of machine parameter variations while offering fast dynamic response and simplified control implementation. However, persistent problems associated with high torque ripples and variable switching frequencies prevent its widespread adoption. To overcome these limitations, several techniques have been developed, in particular the use of multi-level inverters and fuzzy logic algorithms. This article proposes an in-depth evaluation of these techniques in a MATLAB/Simulink environment under various operational conditions. The main objective is to provide a detailed performance analysis of these approaches, examining their effectiveness in torque and flux ripple reduction, switching frequency management, robustness, computation time, cost, current harmonic distortion, and algorithm complexity. These results will help to select the most appropriate control strategy for specific applications. [ABSTRACT FROM AUTHOR]

When the tractor is undertaking the forestry carrying operation, due to the complex road conditions in the forest, it mostly runs at a low speed, has a high steering demand, and often has a load unit, so it pays more attention to its driving stability and steering sensitivity. In this paper, CarSim software is used to build the physical model and load unit model of the tractor, the control strategy of the tractor is designed based on Simulink software combined with the two-degree-of-freedom dynamic model, and the two-degree-of-freedom model of tractor is established. The braking torque feedback control is carried out by combining the yaw rate and the side deflection angle of centroid with the fuzzy control theory. In addition, the proportional control strategy of front and rear wheel angle is introduced according to the four-wheel steering mode of the tractor. Under the CarSim-Simlulink co-simulation platform, combined with the complex road conditions of forestry operations, the low-speed driving and steering experiments of tractor under different control strategies are carried out. The results show that the control strategy adopted in this paper can effectively reduce the steering radius of the tractor under complex road conditions, increase the steering speed, and limit the side deflection angle of centroid to a small range. The tractor has high stability, the steady state value of yaw rate is closer to the ideal state, and the steering is more sensitive. [ABSTRACT FROM AUTHOR]

This work presents a predictive torque vectoring controller that optimally monitors the vehicle limits of handling using active torque distribution in the rear axle of a fully electric vehicle. It works in combination with a feedforward controller designed to improve the vehicle's agility. The overall torque vectoring strategy is described together with the vehicle lateral dynamics, sideslip angle estimator, and torque allocation method. Numerical simulations for various scenarios and road profiles show the benefits of predicting the vehicle's handling limits and the enhancement of vehicle stability in terms of reduced vehicle sideslip angle and driver effort. The proposed optimal control method for predicting vehicle handling limit violations does not require a dedicated solver, making it a promising candidate for real-time applications. The case study is a vehicle equipped with two rear in-wheel motors in the framework of , an ECSEL Joint Undertaking (JU) European research project. Hardware-in-the-loop (HiL) tests were performed on a dedicated e-axle test bench to integrate the torque vectoring controller with the real e-motors and a dual inverter. The results of the HiL testing demonstrate that the torque-vectoring requirements are satisfied by the hardware configuration in use. [ABSTRACT FROM AUTHOR]

Summary: Permanent magnet synchronous motors (PMSM) are widely employed in the application of electric vehicles (EVs) due to their simplicity of operation. Model predictive current control (MPCC) is an advanced technique used to control the PMSM owing advantages like multi‐variable cost function and good dynamic performance. Cost function of predictive current control (PCC) does not require the flux weighting factor; hence, it is simple in the selection of suitable voltage vector (VV). The conventional PCC (C‐PCC) applied to interior PMSM (IPMSM) contains more torque and flux ripples as it includes only one set of voltage vectors for all speed ranges. In proposed PCC (P‐PCC), the magnitude and location of voltage vectors is to be selected as large and small VVs to reduce torque ripples. The P‐PCC in this article utilizes two set of extended voltage vectors (large and small VVs) based on the applied speed change in dynamic conditions and hence reduces the ripple content. Incorporating maximum torque per ampere (MTPA) control in this article serves the purpose of optimizing the machine performance. By adding MTPA to the proposed method, it is aimed to enhance the machine performance with less ripples and improved torque response. Simulation results are presented for conventional and P‐PCC to highlight the effectiveness and efficacy of the P‐PCC. The P‐PCC is experimentally verified with 3.7 kW PMSM using d‐SPACE controller. [ABSTRACT FROM AUTHOR]

Severe torque ripple and determination of the weighting factor pose significant challenges in traditional predictive torque control. A deadbeat predictive torque control scheme designed to minimize torque ripple for dual three-phase permanent magnet synchronous motors is proposed in this paper, eliminating the need for a cost function. Additionally, a novel method for calculating action time based on geometric principles is proposed. First, the deadbeat direct torque and flux control is employed to obtain the reference voltage vector. To reduce the computational burden, the nearest virtual voltage vector is selected directly without a cost function. Subsequently, the torque ripple is further reduced by calculating the corresponding action time based on the introduced geometric relationship in the volt-sec coordinate system. Finally, experimental results demonstrate the effectiveness of the torque ripple reduction method under different working conditions. [ABSTRACT FROM AUTHOR]

In view of the disadvantages of negative torque and low operation efficiency in the traditional direct torque control (DTC) for the switched reluctance motor drive (SRD), a novel DTC strategy based on optimal turn-on angle is proposed in this paper. First, the flux hysteresis controller of the traditional DTC is cancelled and the SRM is only controlled by the torque hysteresis controller. The actual rotor position angle is used to divide the sectors instead of the angle calculated by the stator flux, which does not need to select the optimal given flux value, and makes the division of sectors more in line with the inductance characteristics of the SRM. Second, the function for calculating the optimal turn-on angle is designed and the sectors are reallocated. The optimal voltage vector is selected according to the output signal of the torque hysteresis controller and sector position. Finally, the 12-sector DTC method is selected as comparison algorithm and the correctness of the proposed method is confirmed by simulation and experimental results. It is demonstrated that the proposed strategy retains the advantages of the simple structure of the traditional DTC. In addition, it eliminates negative torque, improves the DC bus voltage utilization and torque ampere ratio, and reduces the torque ripple, switching frequency and copper losses. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced indirect instantaneous‐torque‐control is proposed based on the torque sharing function approach of switched reluctance motor drives for electric vehicles by employing the jelly fish search. The major goal is to attain vehicle desires that include minimal torque ripple, maximum torque per ampere (MTPA), and huge performance and extend speed limit. First, a simplest analytic design is developed a determine more proficient turn‐on angle for the torque product. Second, an altered torque sharing function (TSF) is used for compensating the faults of torque tracking. The proposed technique is calculated to represent an accurate switched reluctance motor and its magnetized features. They have worked to create the machine model and execute the necessary transmits. The torque fault is evaluated and compensated inside the torque sharing function. The adapting TSF is compensates for the torque fault with receiving the phase because it is the minimal flux rate connecting variation. Finally, the jellyfish search technique is accepted to determine the optimal control parameters. The proposed strategies are done in MATLAB and its performance is contrasted with different existing strategies. According to the simulation result, the proposed strategy‐based accuracy is 94.2% at 50 iteration and 80% at 100th iteration which is higher than the existing methods. From this analyses, it proved that the proposed technique gives superior performance to existing one. [ABSTRACT FROM AUTHOR]

In this paper, an optimized adaptive human-machine collaborative torque control methodology is developed for a class of autonomous vehicle systems with unknown disturbances by employing a reinforcement learning technology with identifier-critic-actor architecture. The criticism method is proposed to assess the performance of the control and to give feedback to the actor. Furthermore, a human-vehicle-road model with steering torque as input is constructed to describe the vehicle's dynamic response and the driver's maneuvering behavior. The stability of the control system is analyzed by means of the Lyapunov theory. Finally, the effectiveness of the control methodology is illustrated by means of a numerical example. [ABSTRACT FROM AUTHOR]

In order to solve the issues of large computation and control performance affected by motor parameters in the conventional model predictive torque control (MPTC) of permanent magnet synchronous motors (PMSMs), a robust model predictive torque control strategy with online parameter identification based on an improved differential evolution extended Kalman filter (IDEEKF-RMPTC) is proposed To begin with, and a steady-state voltage vector at the next time is obtained through a low-pass filter and used as the reference voltage vector to select the alternative voltage vector. The parameter robustness of the PMSM system is enhanced, and the computational effort is reduced. In addition, an improved differential evacuation algorithm for the extended Kalman filter (EKF) is designed, and the system noise matrix Q and measurement noise matrix R of the EKF are optimized. The estimation error is reduced; the stability of the system is enhanced; and the accuracy of the identification of the motor parameters is improved. Finally, the computational effort of the system is effectively reduced by the proposed IDEEKF-RMPTC strategy, and the parameter robustness of the PMSM drive system under parameter mismatch conditions is enhanced which are proved by the experimental results. [ABSTRACT FROM AUTHOR]

In response to the complex working conditions and poor driving stability of high-clearance self-propelled sprayers, a nonlinear model of the chassis power system was established based on the independently controllable torque of each wheel of the developed electric sprayer. A layered-architecture chassis drive control strategy was formulated, and a stability control framework comprising an instability judgment module, an upper controller, and a lower controller was constructed based on the analysis of the impact of the centroid slip angle, the yaw rate, and the wheel slip rate on driving stability. An ideal reference model was established based on the seven-degree-of-freedom model of the sprayer, and the current state of the sprayer body was determined using the instability judgment module. A drive anti-slip controller and a yaw moment controller based on fuzzy PID theory and sliding mode control theory were designed. Additionally, an optimal torque distribution algorithm was developed based on tire characteristics to rationally allocate drive torque to each wheel, ensuring the stability of the sprayer during operation. Simulation tests were conducted using MATLAB/Simulink to evaluate the sprayer under four different driving conditions during transport and field operations. The test results showed that the "SMC + optimal distribution" control method in the chassis stability control strategy reduced the maximum deviations of the yaw rate and centroid slip angle by an average of 89.5% and 13.6%, respectively, compared to no control. The wheel slip rate during straight driving was well maintained at around 15%, enhancing the driving stability of the sprayer. [ABSTRACT FROM AUTHOR]

Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors as execution motors, achieving redundancy from hardware. A torque vector-space-decoupling control method is introduced for these motors to ensure balanced and stable torque output. Upon a fault, fault-tolerant measures are taken by disconnecting power supply to the affected motor, which, despite reducing system functionality, allows for normal steering control. This research starts with modeling the dual three-phase motors to construct a simulation model. It then proceeds with hardware-in-the-loop testing integrated with the dual-redundancy steer-by-wire control system, conducting tests under dual-lane-change trajectory conditions. Finally, a steering system fault is simulated to assess fault handling and functional degradation. These experiments confirmed that the proposed method enabled balanced torque output from the dual three-phase motors in the redundant steering control and facilitated fault-tolerant processing post fault, ensuring the vehicle's steering functions were maintained. [ABSTRACT FROM AUTHOR]

The requirement for high-speed and high-precision contouring with free-form surfaces in the CNC machining process is increasing. The contour error is an essential criterion for the quality of CNC machining. For the problem of contour error control, the present research is mainly based on position tracking, and the control method directly aiming at contour control has not been well studied. This paper proposed a new type of coordinate transformation-based direct contour control method (CT-DCC) for free-form surface machining trajectories. By real-time monitoring of the contour error and the foot point of the free-form parametric trajectory, the contouring task is decomposed into the contour error control task in the normal direction and the velocity control problem in the feed direction. Using coordinate transformation, the output commands of the two tasks are converted to the axial motion command. CT-DCC completely eliminates position tracking in the traditional control to achieve direct control of the contour error, which provides a new solution for the contour control problem of free-form surface machining. Both the axial velocity control and the axial torque control-based CT-DCC scheme were studied, and the two-axis and three-axis direct contour controllers were tested. The simulation and experiment results show the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

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The hybrid AC-DC microgrid is a system that links AC and DC microgrids using a bidirectional AC-DC interface converter. The presence of dynamic loads is a major obstacle to the implementation of the microgrid concept, and those 50 % include asynchronous motors. This paper presents a control system for a hybrid microgrid that powers an electrical motor using the field-oriented control (FOC) method. This study investigates the significance of third-harmonic injected PWM (THIPWM) in reducing the necessary voltage across the DC bus while still achieving the required AC voltage at motor terminals. MATLAB/Simulink simulation tool and OPAL-RT for real-time simulations were used for validation of the proposed control. The outcomes show the tracking of the reference currents, achieving accurate torque control, managing various operating modes like grid-connected having SPWM and THIPWM, or operation with PV and battery sources. The research also highlights lower settling time values as well as lower total harmonic distortion (THD) compared to SPWM in different load conditions using THIPWM.

Abstract Background The aim of the investigation was to evaluate if the inclination of the lower anterior teeth can be controlled reliably after lower premolar extraction for Class III camouflage treatment with completely customized lingual appliances (CCLAs). Treatment outcome was tested against the null hypothesis that lower premolar extractions for non-surgical camouflage treatment of a Class III malocclusion will lead to further compensation by retroclining mandibular incisors during CCLA treatment. Methods This retrospective study included 25 patients (f/m 12/13; mean age 20.7 years, SD 9.5 years) with uni- or bilateral Class III molar relationship and a Wits value of ≤ -2 mm. In all consecutively debonded patients, lower premolars were extracted to correct the sagittal relationship with a non-surgical camouflage approach. Lateral head films prior to (T1) and at the end of lingual orthodontic treatment (T2) were used to evaluate skeletal and dentoalveolar effects. A paired t-test with alpha = 5% was used to define differences between the endpoints. The linear correlation between the inclination of the mandibular incisors at T1 and the achieved correction was measured with the Pearson correlation coefficient (PCC). A Schuirmann’s TOST equivalence test was used to check if the final lower incisor inclination was within the defined norms. Results The null hypothesis was rejected as the mean lower incisor inclination was improved by 1.8° despite lower premolar extractions (T1: 86.8°/ T2: 88.6°). There was a strong correlation (-0.75) between the lower incisor inclination at T1 and the achieved correction indicating a controlled correction towards the norm regardless of the initial incisor position. At T2, the interincisal angle as well as the lower incisor inclination were within the norm. Conclusion Lower premolar extractions for non-surgical camouflage treatment of a Class III malocclusion will not lead to undesired retroclining of mandibular incisors during CCLA treatment even in severe cases.

Abstract A new dual‐motor servo steering system with improved reliability and safety is proposed. But, despite the advantages of the proposed servo system, it is strongly coupled, non‐linear and multivariable, where the biggest challenge lies in its tracking and synchronization control. To improve the tracking and synchronization control performance of the proposed servo system, a tracking and synchronization control strategy based on backstepping super‐twisting control and multi‐level differential coupling is presented. First, a parallel model of the dual‐motor is established. Then, backstepping and super‐twisting control algorithms are integrated while adaptively optimizing key parameters to ensure the robustness and tracking performance of each motor. After that, an angular synchronization controller with multi‐level differential coupling and backstepping super‐twisting algorithm is proposed to compensate for the synchronization error of the dual‐motor system caused by parameter uncertainty. Finally, the simulation is carried out using Simulink to verify the effectiveness of the proposed control strategy.

Abstract Aiming at the torque ripple caused by significant current ripple and non‐ideal back‐electromotive force (back‐EMF) of coreless brushless DC motor (BLDCM), an incremental predictive control strategy based on unipolar pulse width modulation (PWM) is proposed in the non‐commutation interval. Firstly, the unipolar PWM scheme is used to double the current ripple frequency, which can reduce the current ripple. On this basis, the current prediction equations of adjacent control periods are subtracted to obtain the incremental current prediction equation, and the influence of non‐ideal back‐EMF on torque ripple suppression is eliminated. Finally, combined with the author's previous research on the commutation torque ripple suppression strategy, an integrated suppression strategy for non‐commutation and commutation interval is proposed. The experimental results show that, compared with the PI control strategy, the total torque ripple of the proposed strategy is reduced to less than 35%, and the current ripple is reduced. Meanwhile, the commutation time is shortened, and the advantages of coreless motor rapid response are retained. The strategy is universal, not limited by motor parameters and operating conditions, and has theoretical and engineering value.

This paper proposes a combination of a nonlinear feedback linearization control (FLC) and a second-order sliding mode (SOSM) controller to enhance the effectiveness and performance of variable speed control in an open-ended winding induction motor (OEWIM). The literature indicates that the traditional FLC with a PI controller is susceptible to disruptions from its internals as well as outside interference. The conventional sliding-mode controller can offer robust control. However, it suffers from the chattering phenomenon. The SOSMC, based on a super-twisting algorithm (STA), was designed and implemented to overcome all of these drawbacks. It is extremely difficult to obtain the optimum parameters for each FLC and SOSM controller that give good results using traditional methods due to the relatively large number of parameters. Moreover, a novel approach based on the linearly decreasing method for both inertia weight and learning constant of the particle swarm optimization (PSO) algorithm was presented to improve the variable speed control of the OEWIM. To maintain a constant switching frequency, decrease harmonic distortion, and reduce common-mode voltage (CMV), a space vector modulation technique of a seven-level inverter is suggested and implemented by supplying each end of an open-ended stator winding induction motor with three-level inverters. The advantages of the suggested control system have been confirmed using simulated results of various tests of the complete system. [ABSTRACT FROM AUTHOR]

The BLDC motor is becoming more popular in electric vehicles than other motors because of its high torque, robust control, etc. Antithetically, it is more challenging to regulate the torque ripples of a BLDC motor under various real-time conditions. To overcome these shortcomings, this study uses novel methodology to analyse the effectiveness of BLDC motor with different energy management controllers. In this study, to control the torque variations of a BLDC motor, supervisory, hybrid, intelligent, and PID controllers are designed using MATLAB/Simulink. This study integrates experimental and modelling techniques to understand the behaviour of a BLDC motor with various EMCs in real-time conditions. The simulation finding indicates that the supervisory controller exhibits a minimal settling time (0.05 s), rise time (0.01 s), and overshoot (0.93%) than other conventional controllers. It integrates knowledge of real-time rules and numerical data with a neural network in order to forecast and reduce error statistics in the BLDC motor. As well, the proposed supervisory approach significantly reduces the torque fluctuations of BLDC motors under various real-time operating conditions. Further, an experimental study is conducted to validate the results of the simulation; this work entails the development of efficiency maps for a variety of energy management controllers. The efficiency of the various controllers is 97, 91, 85, and 78%, respectively. The recommended supervisory strategy surpasses other controllers in terms of time-domain characteristics under different conditions. Therefore, the proposed controller will enhance the efficiency of the BLDC motor and extend driving range of EVs under various real-time driving situations. [ABSTRACT FROM AUTHOR]

Multimode processes are common in modern industry and refer to processes that work in multiple operating modes. Motivated by the torque control process of a wind turbine, we determine that there exist two types of changes in multimode processes: (i) mode transitions and (ii) parameter changes. Detecting both types of changes is an important issue in practice, but existing methods mainly consider one type of change, and thus, do not work well. To address this issue, we propose a novel modeling framework for the offline change point detection problem of multimode processes, which simultaneously considers mode transitions and parameter changes. We characterize each mode with a parametric cost function and formulate the problem as an optimization model. In the model, two penalty terms penalize the number of change points, and a series of constraints specify the multimode characteristics. With certain assumptions, the asymptotic property ensures the accuracy of the model solution. To solve the model, we propose an iterative algorithm and develop a multimode-pruned exact linear time (multi-PELT) method for initialization. The simulation study and the real case study demonstrate the effectiveness of our method against the state-of-the-art methods in terms of the accuracy of change point detection, mode identification, and parameter estimation. [ABSTRACT FROM AUTHOR]

The issue of velocity‐free practical predefined‐time (PPT) attitude coordination control (ACC) for multiple rigid spacecraft under directed topology and subject to bounded external disturbances is investigated in the article. To gain precise estimates of the spacecraft's velocities together with external disturbances, PPT extended‐state observers are presented by virtue of a time‐varying function technique. Next, distributed PPT state observers are designed to estimate the leader's attitude which is accessible to only some of the followers. One advantage of the designed distributed observers is that the information required to transmit among neighbor spacecraft is only the estimated attitudes, which results in a reduction of the communication burden. Then, a distributed velocity‐free PPT ACC law is put forward in terms of the backstepping approach and the PPT observers. The present control protocol can ensure that the settling time is bounded by a predefined time with no reliance on any other controller parameters or initial conditions. Finally, the efficiency of the developed ACC scheme is illustrated by numerical simulation examples, and it is shown that the designed control law possesses one further salient advantage of required reduced magnitudes of control torques to reach accurate ACC performance. [ABSTRACT FROM AUTHOR]