Search Results (18)

This paper introduces a novel sensorless speed control strategy for squirrel-cage induction motors, which ensures robust operation in the presence of external disturbances by applying the state feedback technique. Based on the induction motor model, the speed controller is synthesized by defining a sliding variable that is driven to zero through the supertwisting control law, ensuring the stabilization of the tracking error. The time derivative of the error variable is estimated using a robust differentiator based on the sliding-mode twisting algorithm, thereby eliminating the need to estimate the load torque. A robust observer is employed to estimate the rotor speed and flux linkages simultaneously. The convergence of the estimated rotor flux linkages is enforced through a discontinuous first-order sliding-mode input, while the convergence of the rotor speed estimate is attained via a quasi-continuous super-twisting sliding-mode input. In the proposed model, the inductance parameters are determined from the magnetizing inductance and the leakage inductances of the stator and rotor. A procedure is also presented for adjusting the stator resistance and leakage inductances, taking into account the squirrel-cage rotor type and the skin effect in alternating current conduction. The performance of the sensorless speed control system under variations in load torque and reference speed is validated through experimental testing. The rotor speed estimation provided by the robust observer is accurate. The reference speed tracking control, evaluated using a 1600–1700 rpm pulse train phase-shifted by 4 s with respect to a 0–0.5 N·m pulse train, demonstrates high precision. Full article

This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. This hybrid approach effectively mitigates the inherent chattering issue commonly associated with sliding-mode control while maintaining high levels of control system precision. We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. During the guidance phase, a pre-trained reinforcement learning model is employed to directly map the missile’s state variables to the optimal adaptive parameters, thereby significantly enhancing the guidance performance. Additionally, a generalized super-twisting extended state observer (GSTESO) is introduced for estimating and compensating the lumped uncertainty within the missile guidance system. This method obviates the necessity for prior information about the target’s maneuvers, enabling the proposed guidance law to intercept maneuvering targets with unknown acceleration. The finite-time stability of the closed-loop guidance system is confirmed using the Lyapunov stability criterion. Simulations demonstrate that our proposed guidance law not only meets a wide range of impact angle constraints but also attains higher interception accuracy and faster convergence rate and better overall performance compared to traditional NTSM and the super-twisting NTSM (ST-NTSM) guidance laws, The interception accuracy is less than 0.1 m, and the impact angle error is less than 0.01°. Full article

Traditional low-order flux sliding mode observer (FSMO) and quadrature phase-locked loop (QPLL) structures generally encounter issues such as estimated signal chattering and inadequate dynamic performance. To overcome these challenges, this paper proposes an iterative fast super-twisting flux sliding mode observer (IFST-FSMO) and a tangent quadrature phase-locked loop (TQPLL) for sensorless control of surface-mounted permanent magnet synchronous motors (SPMSMs). Building on the traditional super-twisting algorithm (STA), the IFST-FSMO is proposed to accelerate convergence and enhance chattering suppression, which incorporates a linear term and utilizes the hyperbolic tangent function to replace the intrinsic sign function. Notably, the feedback matrix is redesigned to ensure the algorithm’s stability during speed reversal. Furthermore, an iterative calculation strategy is implemented under low-speed and light-load conditions, improving steady-state accuracy of estimated flux while avoiding increased computational burden at medium and high speeds. Regarding position estimation, a novel TQPLL with correction factor is proposed, utilizing the tangent function of the electrical angle error to achieve normalization and bandwidth adaptation. Ultimately, the proposed method is implemented on a motor test platform. Comparative experimental results demonstrate that the IFST-FSMO combined with TQPLL exhibits superior dynamic response and steady-state accuracy, while achieving efficient speed reversal. Full article

In order to improve the observation accuracy of rotor positions in the sensorless control of permanent magnet synchronous motors and to simplify the parameter adjustment process, this paper proposes an improved finite-time adaptive super-twisting sliding mode observer. First, a linear gain term is introduced into the conventional super-twisting sliding mode observer model as a way of improving the identification accuracy of the observer. Then, for the multi-parameter variable problem in the traditional observer model, a rotational speed variable function design is presented, which simplifies the multi-variables into a single adaptive variable. This reduces the complexity of the observer model while further improving the observation accuracy and stability of the improved observer algorithm (which is verified using Lyapunov’s stability theory). A new back EMF filter and an adaptive phase-locked loop are then used to improve the model’s speed tracking capability. Finally, through simulation and experimental tests, the improved algorithm’s ability to quickly observe changes in rotor position and speed, as well as its fast convergence, small jitter and high accuracy characteristics, are verified. Full article

This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). The SOSMC-STA is suggested for overcoming the shortcomings of the Proportional Integral Controller (PIC) and the Conventional Sliding Mode Controller (CSMC). Indeed, the main limitations of the PIC are the slower speed response, the tuning difficulty of its parameters, and the sensitivity to changes in system parameters, including variations in process dynamics, load changes, or changes in setpoint. It is also limited to linear systems. Regarding the CSMC technique, its limitation is the chattering phenomenon, characterized by the rapid switching of the control signal. This phenomenon includes high-frequency oscillations which induce wear and tear on mechanical systems, adversely affecting performance. Secondly, this paper also proposes a Loss Model Controller (LMC) for FPIM energy optimization. Thus, the suggested LMC chooses the optimal flux magnitude required by the FPIM for each applied load torque, which consequently reduces the losses and the FPIM efficiency. The performance of the optimized DFOC-SOSMC-STA based on the LMC is verified using numerical simulation under the Matlab environment. The analysis of the simulation results shows that the DFOC-SOSMC-STA guarantees a high dynamic response, chattering reduction, good precision, and robustness in case of external load or parameter disturbances. Moreover, the DFOC-SOSMC-STA, combined with the LMC, reduces losses and increases efficiency. Full article

This paper delves into a comprehensive study of a wide-speed-range sensorless control approach for surface-mounted permanent magnet synchronous motors (SPMSMs). In the low-speed range, a novel high-frequency pulse voltage injection (HFPVI) method is introduced for rotor position estimation, which does not depend on motor saliency and is well-suited for SPMSMs. This method incorporates a second-order generalized integrator (SOGI) and a new modulation signal to enhance the accuracy of rotor position estimation. For medium-to-high speeds, an improved super-twisting sliding mode observer (STSMO) utilizing a continuous hyperbolic tangent function is proposed to mitigate chattering. Additionally, a new phase-locked loop (NPLL) is introduced to accurately obtain the rotor position. Furthermore, this paper designs an exponential weighted switching function to facilitate a smooth transition of the motor from the low-speed domain to the medium- and high-speed domains. The effectiveness and superiority of the proposed methods are validated through simulations and experiments conducted on an RTU-BOX platform. The rotor position estimation errors of the proposed new HFPVI method and the improved STSMO method under various operating conditions are both approximately 0.05 rad (2.8 elc·deg), and the SPMSM can switch smoothly from the low-speed range to the medium- and high-speed ranges. Full article

This paper focuses on the real-time implementation of an optimal high-performance control applied to an interleaved nonisolated DC/DC converter designed for fuel cell applications. Three-phase interleaved boost converters are utilized to minimize input current undulation, increase efficiency, and provide a high output voltage in order to ensure the performance of the FC stack. The proposed control strategy contains an outer loop that generates the reference current based on a two-degree-of-freedom PID controller. This controller provides a robust setpoint tracking and disturbance rejection, which improves the system’s response and efficiency. A fast inner regulation loop based on a super-twisting integral sliding mode (STISM) algorithm is developed to achieve a fixed converter output voltage, equitable phase current sharing, and fast regulation against load disturbances in failure operation. The STISM algorithm exhibits a rapid convergence property of the sliding mode and effectively avoids the chattering phenomena frequently observed in conventional sliding modes. The proposed controller’s gains are determined using the atom search optimization algorithm, which ensures exceptional reliability and a high degree of robustness and stability of the controllers under a variety of operational conditions. This method is inspired from the behavior of atoms and their electrons during the excitation process leading to a one-of-a-kind optimization technique which contributes to the controller’s reliability. Using Matlab-Simulink simulation tools, the efficacy and performance of the designed control have first been evaluated and assessed and compared with other optimization algorithms, and then with a dual loop based on a PID controller. Then, they have been verified by real-time hardware implementation on a 1.2 KW prototype FC converter driven by the dSPACE-1104 card under a variety of tests. The suggested approach offers impressive experimental results in dynamic and steady states. Full article

This study investigates the influence of high-order twisting phases on polarization states and optical angular momentum of a vector light field with locally linear polarization and a hybrid state of polarization (SoP). The twisted vector optical field (TVOF) is experimentally generated based on the orthogonal polarization bases with high-order twisting phases. The initial SoP of a TVOF modulated by the high-order twisting phase possesses various symmetric distributions. The propagation properties of a high-order TVOF with locally linear polarization and hybrid SoP are explored, including the intensity compression, expansion, and conversion between the linear and circular polarization components. In particular, orbital angular momentum (OAM) appears in a high-order TVOF during propagation where no OAM exists in the initial field. The variation of OAM distribution in cross-section becomes more frequent with the increase of the twisting phase order. In addition, a non-symmetric OAM distribution appears in a non-isotropic TVOF, leading to the rotation of the beam around the propagation axis during propagation. The optical energy flow distribution of a high-order TVOF provides a more profound understanding of the propagation dynamics of high-order TVOF. These results provide a new approach for optical field manipulation in a high-order TVOF. Full article

The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM. Full article

The induction motor (IM) drives are prone to various uncertainties, disturbances, and non-linear dynamics. A high-performance control system is essential in the outer loop to guarantee the accurate convergence of speed and torque to the required value. Super-twisting sliding mode control (ST-SMC) and fractional-order calculus have been widely used to enhance the sliding mode control (SMC) performance for IM drives. This paper combines the ST-SMC and fractional-order calculus attributes to propose a novel super-twisting fractional-order sliding mode control (ST-FOSMC) for the outer loop speed control of the model predictive torque control (MPTC)-based IM drive system. The MPTC of the IM drive requires some additional sensors for speed control. This paper also presents a novel machine learning-based Gaussian Process Regression (GPR) framework to estimate the speed of IM. The GPR model is trained using the voltage and current dataset obtained from the simulation of a three-phase MPTC based IM drive system. The performance of the GPR-based ST-FOSMC MPTC drive system is evaluated using various test cases, namely (a) electric fault incorporation, (b) parameter perturbation, and (c) load torque variations in Matlab/Simulink environment. The stability of ST-FOSMC is validated using a fractional-order Lyapunov function. The proposed control and estimation strategy provides effective and improved performance with minimal error compared to the conventional proportional integral (PI) and SMC strategies. Full article

The effects of measuring devices/sensors on improving the power quality (PQ) of electric networks are studied in this paper. In this context, improving the performance of an LCL-type grid connected to a three-phase three-wire shunt active filter (SAF) in the presence of voltage perturbations is studied. In order to ensure the high-quality performance of LCL-SAF in the presence of voltage perturbations, the robust continuous second-order sliding mode controller (2-SMC), including twisting and super-twisting controllers, and continuous higher-order sliding mode controller (C-HOSMC)-based approaches are employed. These controllers, whose outputs are processed by pulse-width modulation (PWM), allow minimization of the phase shift and prevent the generation of discontinuous chattering commands, which can severely damage the VSI components. Moreover, an integration of a generalized instantaneous power identification algorithm with an advanced phase locked loop (PLL) was proposed and experimentally tested to validate the effective performances of SAF under severe perturbations. Additionally, the studied approaches were tested via simulations taking into account a conventional nonlinear industrial load in a real textile factory environment, using measurements provided by power quality analyzers. Finally, the effects of the measuring devices, including the current and voltage sensors, on the accuracy and reliability of the SAF and, consequently, on the PQ of the electric power grid were studied via simulations and experimentally. The results of this study support the validity of the recently published patent. Full article

This article focuses on the trajectory tracking problem in the actuation control section of autonomous vehicles. Based on a two-degrees-of-freedom dynamics model, this paper combines adaptive preview control with a second-order sliding mode control method to develop a new control method. By designing an objective function based on lateral deviations, road boundaries, and the corresponding characteristics of the overall vehicle motion, the method adaptively adjusts the preview time to obtain the ideal yaw rate and then uses a second-order sliding mode control algorithm named Super-Twisting to calculate the steering wheel angle. Combining the low-pass filter with this controller can effectively suppress the chattering caused by the switching of the sliding mode plane while proposing a concept of smoothing based on gradient derivative, the smoothness after filtering is one-seventeenth of that before filtering, whereas the phase plane is used to prove its effectiveness and stability, it can be seen from the phase diagrams that all the state points are in the stable region. A joint simulation model of Matlab/Simulink and Carsim was built to verify the control effectiveness of the controller under the double-shift road, and the simulation results show that the designed controller has good control effect and high tracking accuracy. Meanwhile, the simulation model is also used for other simulations, firstly, simulation comparison tests were carried out with the Model Predictive Control algorithm at speeds of 36 and 54 km/h, compared to the MPC controller, the tacking accuracy of the ST controller has improved to 64.42% and 51.02% at 36 and 54 km/h; secondly, taking simulation of the designed controller against a conventional sliding mode controller based on isokinetic law of convergence, compared to the CSMC controller, the tracking accuracy of the ST controller has improved 41.78% at 54 km/h, and the smoothness of the ST controller is one-nineteenth of that of the CSMC controller; thirdly, carrying out simulations on parameter uncertainties, and replacing parameter uncertainty with Gaussian white noise, the maximum tracking error at 36 and 54 km/h did not exceed 0.3 m, and tracking remains good. Small fluctuations in the steering wheel angle do not affect the normal actuation of the actuator. Full article

In this article, a model-free control (MFC) using super twisting nonlinear fractional order sliding mode for aerodynamic heating ground simulation of hypersonic vehicles (AHGSHV) is proposed. Firstly, the mathematical model of AHGSHV is built up. To reduce order and simplify the dynamic model of AHGSHV, an ultra-local model of MFC is taken into consideration. Then, time delay estimation can be used to estimate systematic uncertainties and external unknown disturbances. On the basis of the original fractional order sliding mode surface, the nonlinear function fal is introduced to design the nonlinear fractional order sliding mode surface, which can guarantee stability, increase convergence rate, and reduce static error and saturation error. In addition, the super twisting reaching law is used to improve the control performance of the reaching phase, resulting from the existence of sign function in the integral term, and it can effectively reduce the high-frequency chattering. Moreover, the Lyapunov function is used to prove the stability of the whole system. Finally, several numerical simulations show that the designed controller has more advantages than others. Full article

The twist-bend nematic phase (N_TB) exhibits a complicated hierarchy of structures responsible for several intriguing properties presented here. These are: the observation of a fast electrooptic response, the exhibition of a large electroclinic effect, and the observation of an unusual pattern of the temperature dependence of birefringence of bent-shaped bimesogens in parallel-rubbed planar-aligned cells. These unusual effects inspired the use of highly sophisticated techniques that led to the discovery of the twist-bend nematic phase. Results of the optical retardation of a parallel-rubbed planar-aligned cell show that the ‘heliconical angle’ (the angle the local director makes with the optical axis) starts increasing in the high temperature N phase, it exhibits a jump at the N–N_TB transition temperature and continues to increase in magnitude with a further reduction in temperature. The liquid crystalline parallel-rubbed planar-aligned and twist-aligned cells in this phase exhibit fascinating phenomena such as a demonstration of the beautiful stripes and dependence of their periodicity on temperature. The Fréedericksz transition in the N_TB phase is found to be of the first order both in rubbed planar and homeotropic-aligned cells, in contrast to the second order transition exhibited by a conventional nematic phase. This transition shows a significant hysteresis as well as an abrupt change in the orientation of the director as a function of the applied electric field. Hierarchical structures are revealed using the technique of polymer templating the structure of the liquid crystalline phase of interest, and imaging of the resulting structure by scanning electron microscopy. Full article

In this paper, the tracking control problem of underwater robot manipulators is investigated under the influence of the lumped disturbances, including unknown ocean current disturbances and parameter uncertainties. The proposed novel continuous nonsingular finite–time (CNFT) control method is twofold. Firstly, the modified adaptive super–twisting algorithm (ASTA) is proposed with a nonsingular fast terminal sliding mode (NFTSM) manifold to guarantee the finite–time convergence both in the sliding mode phase and the reaching phase. Secondly, a higher–order super–twisting disturbance observer (HOSTDO) is exploited to attenuate the effects of the lumped disturbances. Considering the time–varying gain matrix of the closed–loop control system, the bounded stability is strictly proved via the Lyapunov theory. Hence, the superiority of the proposed controller is singularity–free, fast convergence, chattering–free, high steady–state tracking performance, and good robustness by resorting to the methods of CNFT control and ASTA in combination with a disturbance observer. Finally, numerical simulations are conducted on a two degree–of–freedom (DOF) underwater robot manipulator to demonstrate the effectiveness and high tracking performance of the designed controller. Full article