Super-twisting Algorithm Research Articles

Recurrent neural network-based technique for synchronization of fractional-order systems subject to control input limitations and faults

Despite the existence of promising methods for controlling complex systems, there is still a need for further advancement in controlling and synchronizing fractional systems. This is even more monumental when it comes to practical applications with faults and physical constraints present in their control actuators. To address this issue, the current study proposes a new control technique that utilizes a recurrent neural network-based finite-time super-twisting algorithm for fractional-order systems. The proposed controller is enhanced with an intelligent observer to account for faults and limitations that may be present in the control actuator of the fractional-order systems. The proposed method allows the system to be regulated even in the presence of control input constraints and faults. Moreover, the proposed technique guarantees that the closed-loop system will converge in a finite amount of time. The control design is explained in detail, and its finite-time stability is proven. To evaluate the performance of the controller, we applied it to two different fractional-order systems that were subject to control input limitations and faults. The outcomes of the proposed approach were then compared with those obtained using a state-of-the-art technique for fractional-order systems to further validate the effectiveness of our proposed approach.

A new scheme of the fractional-order super twisting algorithm for asynchronous generator-based wind turbine

In this paper, the performance and efficacy of the super-twisting algorithm (STA) were improved by using fractional calculus theory (FCT). A new form is given to the STA controller based on the FCT technique to control the asynchronous generator (AG)-based wind power system (WPS). With the main focus on improving the characteristics and quality of reactive power, active power, and electric current, objective functions are calculated, including indices of ripples in active and reactive power, current and torque, and the total harmonic distortion (THD) value of the stator current. In this work, this proposed STA-FCT controller is used to obtain better performance and improve the features of the indirect field-oriented control (IFOC) for AG-based WPS. The designed AG control model has been validated using Matlab/Simulink software. In the first test, the THD of current, active power, and reactive power ripples of the AG-WPS was improved by 99.46%, 96.74%, and 94.07%, respectively. Also, the designed IFOC-STA-FCT technique provided a better dynamic response than the traditional IFOC technique. The robustness of the designed strategy was tested in the second test. In this test, the designed IFOC strategy significantly minimized the active and reactive power ripples compared to the classical IFOC technique (64.34% and 53.56%), and the THD value was tolerably decreased (98.85%) compared to the traditional IFOC strategy. While the dynamic response is always better in the case of the designed IFOC-STA-FCT technique.

Design of Sensorless Control System for Permanent Magnet Linear Synchronous Motor Based on Parametric Optimization Super-Twisting Sliding Mode Observer

To improve the chattering problem caused by the terminal sliding mode control (TSMC) and sliding mode observer (SMO) in permanent magnet synchronous linear motor (PMLSM) control systems, this study presents the design of a continuous terminal sliding mode control (CTSMC) controller and an improved SMO. By enhancing the sliding mode surface, CTSMC enhances the dynamic response and robustness of the system. The observer replaces the traditional sliding mode switching law with a super-twisting (ST) algorithm, a twisting algorithm that makes use of the structural characteristics of the second-order sliding mode to ensure output continuity and reduce the observed buffeting. The sliding mode gain of the ST algorithm is optimized using the particle swarm optimization (PSO) algorithm to acquire the optimal parameters and fully exploit the observer’s performance potential. Finally, the proposed method is simulated and tested. The comparison results show that the proposed method boosts the system’s dynamic response and robustness and reduces chattering.

A Generalized Supertwisting Algorithm.

The work proposes a generalized supertwisting algorithm (GSTA) and its constructive design strategy. In contrast with the conventional STA, the most remarkable characteristic of the proposed method is that the discontinuous term in the conventional STA is replaced with a fractional power term, which can fundamentally improve the performance of the conventional STA. It is shown that if the fractional power in the nonsmooth term becomes -1/2, the GSTA will reduce to the conventional STA. Under the GSTA, it will be rigorously verified by taking advantage of strict Lyapunov analysis that the sliding variables can finite-time converge to an arbitrarily small region in a neighborhood of the origin by tuning the gains and the fractional power. Finally, simulation studies are provided to demonstrate the superiority of the theoretically obtained results.

Study on a Second-Order Adaptive Sliding-Mode Observer Control Algorithm for the Sensorless Permanent Magnet Synchronous Motor

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.

Direct Power Control for Three-Level Multifunctional Voltage Source Inverter of PV Systems Using a Simplified Super-Twisting Algorithm

This study proposes a simplified super-twisting algorithm (SSTA) control strategy for improving the power quality of grid-connected photovoltaic (PV) power systems. Some quality issues are considered in this study including the power factor, reducing the total harmonic distortion (THD) of current, compensating the reactive power, and injecting at the same time the energy supplied by the PV system into the grid considering non-linear load. This improvement is achieved by two topologies; controlling both the boost DC–DC converter and the DC–AC inverter that links the PV system to the grid. The DC–DC converter is controlled using proportional-integral (PI) and SSTA to maximize the power generated from the PV panel regardless of its normal and abnormal conditions, while the DC–AC inverter is employed to direct power control strategy with modified space vector modulation using the phase-locked loop (PLL) technique of a three-level neutral-point-clamped (NPC) inverter based on the proposed strategies (PI and SSTA). In addition, a shunt active power filter (SAPF) is used to connect the PV system to the AC grid and feed a non-linear load. To validate the simulation results presented in this paper using Matlab software, a comparative study between the PI controller and the SSTA is presented. The results show the effectiveness and moderation of the suggested SSTA technique in terms of feasibility, tracking performance, less power ripple, dynamic response, THD value, overshoot, steady-state error, and robustness under varying irradiation, temperature, and non-linear conditions.

A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators

With the increasing demand for high-performance controllers in micro- and nano-systems, it is crucial to account for the effects of unexpected faults in control inputs during the design process. To tackle this challenge, we present a new approach that leverages an estimator-based super-twisting control technique that is capable of regulating chaos in fractional-order arch micro-electro-mechanical system (MEMS) resonators. We begin by studying the governing equation of a fractional-order arch MEMS resonator, followed by a thorough exploration of its chaotic properties. We then outline the design process for our novel control technique. The proposed technique takes into consideration the effects of uncertainty and faults in the control input by utilizing a finite time estimator and a super-twisting algorithm. The proposed technique addresses important challenges in the control of MEMS in real-world applications by providing fault tolerance, which enables the controller to withstand unexpected faults in the control input. We apply our controller to the fractional-order arch MEMS resonator, conducting numerical simulations. The numerical findings reveal that our proposed control technique is capable of stabilizing the system’s dynamics, even in the presence of a time-evolving fault in the control actuator. These results provide compelling evidence of the efficacy of our approach to control, despite the presence of an evolving fault.

Adaptive super-twisting-based nonsingular fast terminal sliding mode control of permanent magnet linear synchronous motor

In this study, to reduce the impact that permanent magnet linear synchronous motor (PMLSM) servo system on the sensitivity of external and internal interferences, an adaptive super-twisting-based nonsingular fast terminal sliding mode control (AST-NFTSMC) scheme is put forward. First of all, the mathematical model of PMLSM contains uncertainties is set up, and the control law is established to make position signal converge to given state asymptotically. Second, by introducing the super-twisting algorithm, the chattering caused by nonlinear switching function in traditional method is weakened. However, in actual industrial situations, it is difficult to determine the boundary of lumped disturbance, which makes the switching gains in super-twisting algorithm cannot be accurately selected. Therefore, an adaptive law is introduced to adjust the switching gains online, so that the gains can be dynamically adjusted within a limited range during operation, so as to further weaken chattering. Finally, the practicability of AST-NFTSMC is proved in theory and verified by system experiments. The experimental results prove that AST-NFTSMC can significantly weaken chattering, and result in robust control performance.

Adaptive finite time smooth nonlinear sliding mode tracking control for surface vessels with uncertainties and disturbances

A study of the tracking control design for surface vessels is presented in this paper. A nonlinear adaptive approximation of the Super-Twisting algorithm (STW) is used to design a control law which provides desired stability properties even in the presence of unknown uncertainties and disturbances. By using this procedure, a desired trajectory is followed successfully and the tracking error is reduced to a small set containing the origin over the course of a finite period of time. An algorithmic solution was developed based on a small number of parameters with physical significance, which simplifies the process of determining the configuration. A numerical example is used to verify the effectiveness and robustness of the controller designed.

Generalized Super-Twisting Backstepping Sliding Mode Control for Electro-Hydraulic Servo Systems Considering the Coexistence of Matched and Mismatched Uncertainties

Aiming at the problem of the coexistence of matching and mismatching uncertainties in electro-hydraulic servo systems, disturbance observers and a backstepping sliding mode controller based on the generalized super-twisting algorithm (GSTA) are proposed in this paper. First, in order to compensate for the uncertainty in the controller, two generalized super-twisting disturbance observers (GSTDOs) are constructed to effectively reduce the discontinuous gain of the controller. Then, the GSTA is introduced to optimize the backstepping sliding mode controller to obtain a better control effect. Finally, the proposed control strategy is compared and simulated on the electro-hydraulic servo system. The experimental results verify that the proposed control strategy has better tracking performance. The effect of asymptotic tracking in the presence of parameter uncertainties and disturbances is achieved, while transient tracking performance and final tracking accuracy are guaranteed in the presence of time-varying uncertain nonlinearities.

Anti-unwinding adaptive super-twisting attitude control for spacecraft

This article addresses the attitude maneuver control without unwinding based on variable gain(i.e. adaptive) super-twisting algorithm and the modified Rodrigues parameters(MRPs). First, a selection logic for the MRP set and its shadow set is designed in order to construct an attitude control system model for rigid spacecraft. Second, a nonlinear sliding function is presented, and on the sliding phase, finite-time convergence and anti-unwinding performance are guaranteed. As a result, a first order sliding mode controller is created to ensure finite-time convergence and anti-unwinding performance on the reaching phase. To alleviate the chattering and improve convergence speed, an adaptive super-twisting algorithm is presented, and the finite-time convergence and anti-unwinding performance are guaranteed on the reaching phase. Furthermore, the adaptive gains are designed based on dual-layer adaptive law, which allows the gains to be increased and decreased as appropriate. It is further demonstrated that when the controller gains are time-varying according to adaptive law, the convergence property and anti-unwinding performance are guaranteed. Numerical simulations are carried out to illustrate the closed-loop system's performance under the proposed control scheme.

Real-time Super Twisting Algorithm based fuzzy logic dynamic power management strategy for Hybrid Power Generation System

Energy generation through the combination of renewable systems is becoming attractive and applied in various applications, principally for water pumping applications. This paper presents the development and real time implementation of a robust power control strategy for a Hybrid Power Generation System (HPGS). The studied system consists of a photovoltaic renewable energy source associated with a hybrid energy storage system (HESS) composed of batteries and supercapacitors to supply a PMDC motor unit for water pumping applications. The control objectives are, to enhance the existing control laws which are based on linear PI controller with others based on non-linear Super-Twisting Algorithm (STA) to regulate the output power of the hybrid system and to satisfy the total demand, on the other hand, to prolong the durability of batteries by maintaining their state of charge in safe margins in order to overcome the ageing problem. For this purpose, a Fuzzy Logic-based Power Management Strategy (FL-PMS) is developed to identify the appropriate mode of operation for the system. Numerical simulations in Matlab/Simulink are performed to prove the effectiveness of the proposed control to reduce chattering and overshoot rates under fluctuating load demand and climatic conditions, as well as the accuracy of the FL-PMS in balancing the power requirements of the batteries and supercapacitors to ensure an optimal energy distribution. Finally, a test bench of the entire HPGS has been implemented and its real-time performance is intended to validate the simulation analysis. The obtained results show that the proposed control and FL-PMS strategies can improve the overall behaviour of the system and ensures a well-guided energy exchange, resulting in batteries protection.

Speed Regulation for PMSM with Super-Twisting Sliding-Mode Controller via Disturbance Observer

This paper focuses on the speed regulation of a permanent-magnet synchronous motor (PMSM) with an uncertain extended load disturbance. A novel super-twisting sliding-mode control (NSTSMC) was proposed via a nonlinear integral sliding surface and a modified reaching law, effectively suppressing the chattering phenomenon. In addition, the NSTSMC can improve the convergence performance with a 0.04 s settling time, satisfying the super-twisting algorithm stability condition. For the novel integral sliding surface, the integral power term of the system state variables was incorporated into the conventional sliding surface to effectively improve the convergence rate and anti-disturbance ability. Moreover, an extended sliding-mode disturbance observer (ESO) was used to estimate the lumped extended disturbance and add the corresponding feedback compensation value from the sliding-mode disturbance observer to the output of the speed controller for the improved robustness of the system. The ESO-NSTSMC was developed to improve the performance of PMSM speed regulation by combining the advantages of the novel integral sliding surface, achieving a settling time of 0.01 s without overshoot. We confirm the performance of the proposed NSTSMC through a PMSM speed simulation and demonstrate that the controller can enhance the dynamic performance and robustness of the system.

A Direct Backstepping Super-Twisting Algorithm Controller MPPT for a Standalone Photovoltaic Storage System: Design and Real-Time Implementation

Abstract In this paper, we introduce a novel direct maximum power point tracking (MPPT) approach that combines the backstepping controller (BSC) and the super-twisting algorithm (STA). The direct backstepping super-twisting algorithm control (BSSTAC) MPPT was developed to extract the maximum power point (MPP) produced by a photovoltaic (PV) generator connected to the battery through a boost DC-DC converter. To reduce the number of sensors required for the BSSTAC implementation, a high gain observer (HGO) was proposed to estimate the value of the state of the PV storage system from measurements of the PV generator voltage and current. The suggested technique is based on the quadratic Lyapunov function and does not employ a standard MPPT algorithm. Results show that the suggested control scheme has good tracking performance with reduced overshoot, chattering, and settling time as compared to the prevalent MPPT tracking algorithms such as perturb and observe (P&O), conventional sliding mode control (CSMC), BSC, and integral backstepping controller (IBSC). Finally, real-time findings using the dSPACE DS 1104 software indicate that the generator PV can accurately forecast the MPP, as well as the efficacy of the suggested MPPT technique. The provided approach’s effectiveness has been validated by a comprehensive comparison with different methods, resulting in the greatest efficiency of 99.88% for BSSTAC.

Performance evaluation of an improved non-singular sliding mode attitude control of a perturbed quadrotor: Experimental validation

In this paper, a new control scheme, that combines the Super-Twisting (ST) algorithm with the Nonsingular Terminal Sliding Mode Control (NTSMC), is adopted to robustly stabilize the quadrotor attitude while compensating for the impact of uncertainties/perturbations. The main merit of the proposed ST-NTSMC is to take advantage of the robustness and chattering avoidance allowed by the ST algorithm and the finite-time convergence, the fast transitions, and the high trajectory tracking accuracy allowed by the NTSMC algorithm. Lyapunov criterion is used to analyze the closed-loop stability of the proposed ST-NTSMC controller. Experimental tests are conducted on a quadrotor prototype under various flight conditions in order to test and evaluate the performance of the new controller. Comparisons with multiple linear and nonlinear controllers are also performed to highlight the outperformance of the suggested approach. Experimental results demonstrate the high performance of the developed controller in terms of tracking accuracy, robustness, and chattering reduction.

Adaptive super-twisting fast nonsingular terminal sliding mode control with ESO for high-pressure electro-pneumatic servo valve

In this paper, an adaptive super-twisting fast nonsingular terminal sliding mode controller (ASTFNTSMC) with active disturbance rejection is proposed to improve the response speed, control accuracy, and disturbance rejection ability of the high-pressure electro-pneumatic servo valve (HESV). This controller effectively combines sliding mode control (SMC), active disturbance rejection control (ADRC), and adaptive control. An improved fast nonsingular terminal sliding surface is constructed to speed up the dynamic response. This surface is characterized by the mutual decoupling between the control input and the system state in its derivative, so a super-twisting algorithm (STA) can be implemented to mitigate chattering. By using ADRC, system nonlinearities and external disturbances are regarded as a total disturbance. An extended state observer (ESO) is incorporated into the controller to estimate the total disturbance, and the estimation is applied as feedforward compensation. As a result, the switching term of STA only needs to suppress the residual disturbance, so chattering is further mitigated and disturbance rejection ability is enhanced simultaneously. Furthermore, an adaptive law is employed to reduce the conservativeness in the parameter selection. Finally, comparative experiments are carried out for HESV on the test platform. Experimental results are consistent with the theoretical analysis, showing that the proposed method can achieve faster dynamic response, higher tracking accuracy, and better disturbance rejection performance.

Super-twisting sliding mode control for brushless doubly fed reluctance generator based on wind energy conversion system

Introduction. Recently, wind power generation has grown at an alarming rate in the past decade and will continue to do so as power electronic technology continues to advance. Purpose. Super-twisting sliding mode control for brushless doubly-fed reluctance generator based on wind energy conversion system. Methods. This paper deals with the robust power control of a grid-connected brushless doubly-fed reluctance generator driven by the variable speed wind turbine using a variable structure control theory called sliding mode control. The traditional sliding mode approach produces an unpleasant chattering phenomenon that could harm the system. To eliminate chattering, it is necessary to employ a high-order sliding mode controller. The super-twisting algorithm is one type of nonlinear control presented in order to ensure the effectiveness of the control structure we tested these controllers in two different ways reference tracking, and robustness. Results. Simulation results using MATLAB/Simulink have demonstrated the effectiveness and robustness of the super-twisting sliding mode controller.

Improving the DC-Link Voltage of DFIG Driven Wind System Using Modified Sliding Mode Control

The grid-connected doubly fed induction generator (DFIG) driven wind turbine (WT) system encounters voltage fluctuations due to severe grid faults. The rise in DC-link voltage imbalances the system under voltage sag condition. The system’s protection should ensure that the WT generator meets the grid requirements through a low voltage ride through (LVRT) technique. This paper proposed the modified 2nd order sliding mode (MSOSM) control with gain added super twisting algorithm (GAST) for LVRT enhancement under voltage sag. This controller adds the low positive gains to the switching functions of the super twisting (ST) algorithm. As a result, it maintains the proper variation margins and constant DC-link voltage of the WT-DFIG system under grid fault. The MSOSM controller suppresses the chattering effect, achieves better zero convergence, and eliminates the coordinate transformations. Moreover, the performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the performance of the WT-DFIG system under transient conditions.

An Extended Super-Twisting Algorithm for simultaneous estimation of reaction rates and input disturbance in bioprocess

The present contribution deals with the simultaneous estimation of the reaction rates and input disturbances in a bioprocess. Online estimation of just the reaction rates is possible by sliding mode observer techniques or high-gain observers, in finite-time or with exponential convergence, respectively. However, these techniques are not robust against unpredictable input bioreactor disturbances and are not readily adaptable to treat external disturbances. Motivated by these facts, we propose a novel extended super-twisting algorithm for a class of nonlinear systems, such that the estimation of uncertain parameters, unknown internal dynamics, and external disturbances converge in a finite time or a neighborhood near its nominal values. The effectiveness of the developed algorithm is tested through simulations in an anaerobic digestion process using a batch and a continuous bioreactor. Simulation results show good robustness performance of the extended super-twisting algorithm.

A novel robust adaptive sliding mode control using stochastic gradient descent for PEMFC power system

This study represents a comparison of novel robust adaptive sliding mode control using stochastic gradient descent (ASMCSGD) versus the super twisting algorithm (STA) for the proton exchange membrane fuel cell (PEMFC) power system. PEMFC has been constantly encountered with external disturbances such as inlet gas pressures and temperature fluctuations which a novel adaptive control law should be designed to be robust against the mentioned perturbations. The proposed ASMCSGD is based on the conventional sliding mode control (SMC), which guarantees robustness and restraining external disturbances. As is common, the main drawback of conventional SMC is the generation of a chattering phenomenon. Therefore, by using the stochastic gradient descent (SGD), a novel adaptive control law is designed. Hence, the SGD can continuously calculate the adaptive gain and then guarantee robustness besides minimizing the chattering phenomenon. The stability of the PEMFC power system for both controllers ASMCSGD and STA is demonstrated via the Lyapunov theorem. Simulation results have been studied and illustrate the effectiveness of the proposed controller successfully using Matlab/Simulink.