Super-twisting Sliding Mode Control Research Articles

Adaptive Feedback Control for Four-Phase Interleaved Boost Converter Used with PEM Fuel Cell

Fuel cell electric vehicles (FCEVs) are among the devices that have emerged in recent years. To provide electricity to the electric motors, they use a proton-exchange membrane fuel cell (PEMFC) as the primary energy source and a secondary source consisting of an energy storage system (battery or supercapacitors). The addition of these sources to the motors and accessories of a vehicle requires the association of static converters to condition the different power sources. In addition, a high-efficiency and enhanced-reliability power converter is essential to connect the PEMFC to the vehicle’s DC bus. This paper proposes a robust feedback controller for a four-phase interleaved boost converter used with PEMFC. The proposed controller has double loops based on a state-feedback controller, and an inner loop which translates the differential equation of the system into a state representation by linearization around its operation points. The reference current is generated by state feedback in the outer loop; the state variable is defined by using a change variable. The strong robustness and highly dynamic characteristics of the proposed controller are demonstrated through its performance in terms of output voltage, source current, and settling time. The findings indicate that the proposed controller achieves a response time of 20 ms, resulting in an over 50% improvement compared to the controllers referenced in the literature. Additionally, it reduces both current and voltage ripple, keeping them each below 10%. Further, the controller gains synthesis is validated using the linear quadratic regulator (LQR) technique as well as boundary conditions, and its robustness is verified, taking into account the uncertainty of various operating conditions and discrepancies in circuit components. A double-loop super-twisting sliding mode controller, a backstepping control algorithm, and a PI controller are selected for comparison and discussion. Subsequently, the effectiveness of the proposed controller is evaluated through simulation with the parameters of a 500 W fuel cell system.

Model-based PD neural network control for pipe crack sealing manipulator

This study focuses on the control of a pipe crack sealing manipulator (PCSM) for concrete pipe crack sealing, with the capability to maneuver through horizontal and vertical pipes. This PCSM is a tree-type robot with five different branches. Observation and simulation studies indicate that only the fifth branch of the PCSM effectively executed the repair operation. However, in real application, the movement of these links is hindered by disturbances and uncertainties, preventing them from behaving as intended. Hence, a robust control scheme is essential to effectively manage the links of a pipe crack sealing manipulator. To address this need, this study introduces a Model-based PD neural network control (MBPDNNC) algorithm, which is then compared against modal-based PD (MBPD), Sliding mode control (SMC) with constant plus proportional rate reaching Law (CPPRL), and super twisting SMC (STSMC). The simulation study reveals that MBPDNN is characterized by greater accuracy and less chattering compared to the contrast control methods. The main contribution of this work is the compensation of disturbance by updating the weight by using the Radial basis function neural network (RBFNN). Through observation, it is evident that the neural network yields more promising results in the presence of disturbances and uncertainties.

Barrier function–based adaptive STSMC for steering feel feedback of SBW vehicle with uncertainty

As an essential component of human–computer interaction in steer-by-wire (SBW) vehicles, the steering feel feedback system provides drivers with accurate steering feel by precisely controlling the output torque of the steering feel motor. Meanwhile, the existence of uncertainties makes the accurate control of steering feel feedback torque become an acknowledged challenging issue. This article proposes an adaptive super-torque sliding mode control strategy based on barrier functions for the steering feel feedback system of SBW vehicles with highly complex dynamics in the presence of uncertainties. First, to achieve intelligent modeling under the influence of uncertainty factors, a dynamic system with unknown uncertainty based on adaptive fuzzy logic system (FLS) is proposed. In the framework of this model, the uncertainty factors introduced by unknown external disturbance, parameter uncertainty, and model couplings are considered as a lumped uncertainty function. Furthermore, the membership functions of the FLS are dynamically adjusted based on nearest neighbor clustering, aiming to enhance the modeling accuracy beyond traditional fuzzy modeling. To further offset the system uncertainty and FLS approximation error, an adaptive super-twisting sliding mode control (STSMC) method based on barrier function is proposed. This algorithm retains the advantages of traditional sliding mode control (SMC) methods in dealing with systems with uncertainty and eliminates the need for a priori knowledge of the upper bound of uncertainties by introducing the adaptive law based on barrier function, avoiding the use of complex identification algorithms. Moreover, it eliminates the gain of overestimation and significantly reduces chattering phenomenon in traditional sliding mode control. Finally, based on Lyapunov stability theory, this article proves the proposed system can achieve convergence within a finite time. Compared with STSMC, traditional SMC and proportional–integral–derivative (PID) control, the results verify the effectiveness of the proposed control method. The proposed strategy provides a new solution to reduce the steering feel feedback torque error under the influence of uncertain factors.

Feedforward Control Strategy of a DC-DC Converter for an Off-Grid Hydrogen Production System Based on a Linear Extended State Observer and Super-Twisting Sliding Mode Control

With the large-scale integration of renewable energy into off-grid DC systems, the stability issues caused by their fluctuations have become increasingly prominent. The dual active bridge (DAB) converter, as a DC-DC converter suitable for high power and high voltage level off-grid DC systems, plays a crucial role in maintaining and regulating grid stability through its control methods. However, the existing control methods for DAB are inadequate: linear control fails to meet dynamic response requirements, while nonlinear control relies on detailed model structures and parameters, making the control design complex and less accurate. To address this issue, this paper proposes a feedforward control strategy for a DC-DC converter in an off-grid hydrogen production system based on a linear extended state observer (LESO) and super-twisting sliding mode control (STSMC). Firstly, a reduced-order simplified model of the DAB was constructed through the structure of DAB. Then, based on the reduced-order simplified model, a feedforward control based on LESO and STSMC was designed, and its stability was analyzed. Finally, a simulation comparison of PI, LESO + terminal sliding mode control (TSMC), and LESO + STSMC control methods was conducted in a DC off-grid hydrogen production system. The results verified the proposed control method’s enhancement of the DAB’s rapid dynamic response capability and the system’s transient stability.

Control of a fixed wing unmanned aerial vehicle using a higher-order sliding mode controller and non-linear PID controller

Unmanned aerial vehicles (UAVs) have seen a rise in use during the last few years. Such aircrafts are now a convenient way to complete dangerous, dirty, and tedious tasks. Given that their operation involves a control problem which is non-linear and coupled, it is difficult to analyse. This paper presents the modeling and control of a fixed-wing unmanned aircraft as a contribution to this field. The system’s flight dynamics is derived using Newton’s second law of motion. The system is designed to have a non-linear Proportional Integral Derivative (NPID) controller and a higher-order sliding mode controller (HOSMC). When simulating the system using MATLAB Simulink software, an external disturbance was added to test the robustness of the controllers. Five performance indices which include mean square error (MSE), integral time square error (ITSE), integral absolute error (IAE), integral time absolute error (ITAE), and integral square error (ISE), were used to compare the controllers performance. These indices are used to provide a numerical assessment of the two controllers’ performance. The outcomes demonstrate that the roll, pitch, and yaw states performed better than the super-twisting sliding mode controller. On the airspeed control, the non-linear PID performed better than the super-twisting sliding mode controller.

Fast Supertwisting Sliding Mode Control With Antipeaking Extended State Observer for Path-Tracking of Unmanned Agricultural Vehicles

Fast Supertwisting Sliding Mode Control With Antipeaking Extended State Observer for Path-Tracking of Unmanned Agricultural Vehicles

Super Twisting Sliding Mode Control of Four-Phase Interleaved Boost Converter

This paper presents a novel control method that integrates super-twisting sliding mode (STSM) voltage control with proportional-integral (PI) current control for a four-phase interleaved boost converter (IBC) in fuel cell applications. The STSM control, employed in the outer voltage loop, provides robust voltage regulation by generating precise reference currents for each phase. The conventional PI control in the inner current loop utilizes these reference currents to generate pulse width modulation (PWM) signals for each phase. The effectiveness of the proposed control strategy is evaluated through comprehensive simulation studies in MATLAB/Simulink, demonstrating an improvement in dynamic performance and enhanced robustness compared to conventional methods. Quantitative analysis shows that the output voltage quickly rises to the reference voltage within approximately 0.25 seconds in the proposed STSM-PI control method and improves transient response by 16 times compared to the conventional PI-PI method. This integrated STSM-PI control strategy offers significant advancements in reliability and efficiency making it a promising solution for high-performance fuel cell power systems.

Sliding Mode and Super-Twisting Sliding Mode Control Structures for Vertical Three-Tank Systems

Sliding Mode and Super-Twisting Sliding Mode Control Structures for Vertical Three-Tank Systems

Enhancing Robot End‐Effector Trajectory Tracking Using Virtual Force‐Tracking Impedance Control

This article presents an extended Cartesian space robot control framework that features a virtual force tracking impedance control to enhance the end‐effector trajectory tracking performance. Initially, the concept of a virtual surface is introduced, which is assumed to be at some constant distance from the desired end‐effector trajectory. This virtual surface generates a virtual contact force when interacting with the torque‐controlled robot end‐effector. The interaction is then manipulated using an impedance control model to track a constant desired force. If the robot end‐effector deviates from the desired trajectory, the constant force‐tracking impedance control generates a compliance trajectory that regulates the end‐effector movements, constraining it to the desired trajectory. For robust force tracking, impedance parameters are optimally tuned using a closed‐loop dynamic model incorporating both robot and impedance dynamics. Additionally, super twisting sliding mode control (STSMC) is integrated to overcome uncertainties and the impact of robot dynamics on force‐tracking performance. Experimental validation confirms the theoretical claims of the proposed approach. It demonstrates that force‐tracking impedance control improves the end‐effector trajectory tracking by quickly reacting to the dynamic trajectories compared to position control only and effectively maintains it on the desired trajectories.

Anti-swing position control of super-twisting sliding mode for underactuated tower crane based on nonlinear marine predator algorithm

Due to the nonlinear, underactuated, and strongly coupled characteristics of tower cranes, issues such as inaccurate load positioning and severe swinging are prone to occur during transportation, making the control problem extremely complex. To address these issues, this paper has designed a super-twisting robust sliding mode controller based on the nonlinear marine predator algorithm (NMPA) to ensure the accurate positioning of the desired location during the transportation process of the tower crane while reducing the oscillation of the load. First, a nonlinear dynamic model of a four-degree-of-freedom tower crane considering friction is constructed. Second, to address the difficulty of effectively controlling the underactuated tower crane system model due to its nonlinearity and strong coupling, the super-twisting algorithm is introduced, and a super-twisting sliding mode controller for anti-swing positioning during the crane transportation process is designed. Then, the parameters of the super-twisting sliding mode controller are optimized using the NMPA to suppress sliding mode chattering and quickly achieve the system’s steady state. Finally, the stability of the nonlinear tower crane system is analyzed using Lyapunov’s theory and LaSalle’s invariance principle to ensure the closed-loop stability of the error dynamics. The simulation results show that the proposed control method exhibits excellent load anti-sway performance and robustness.

Robust position regulation of a 2-DOF experimental helicopter using higher order super twisting sliding mode control

This study presents a third-order super twisting sliding mode control algorithm for robust position regulation of a two-degree-of-freedom (2-DOF) experimental helicopter. The proposed approach explores high-order sliding mode control, offering advantages such as finite-time convergence and continuous control signals. The controller is implemented and validated on the Quanser Aero 2 platform, an inherently unstable and nonlinear system that presents significant challenges for control design including cross-coupling effects, model uncertainties, and external disturbances. Extensive simulations and experimental results are presented to validate the efficacy and robustness of the proposed control strategy. They highlight the controller's ability to achieve precise position control while significantly mitigating the chattering phenomenon, a common drawback associated with traditional sliding mode control. This study contributes to the field of nonlinear control systems by demonstrating the potential of high-order sliding mode control in managing nonlinear, coupled dynamic systems. The successful implementation on a real-world platform underscores the practical applicability of the proposed method in aerospace and robotics applications.

3D dynamics and control of a snake robot in uncertain underwater environment

Abstract The snake robot can be used to monitor and maintain underwater structures and environments. The motion of a snake robot is achieved by lateral undulation which is called the gait pattern of the snake robot. The parameters of a gait pattern need to be adjusted for compensating environmental uncertainties. In this work, 3D motion dynamics of a snake robot for the underwater environment is proposed with vertical motion using the buoyancy variation technique and horizontal motion using lateral undulation. “The neutral buoyant snake robot motion in hypothetical plane and added mass effect is negligible”, these previous assumptions are removed in this work. Two different control algorithms are designed for horizontal and vertical motions. The existing super twisting sliding mode control (STSMC) is used for the horizontal serpentine motion of the snake robot. The control law is designed on a reduced-ordered dynamic system based on virtual holonomic constraints. The vertical motion is achieved by controlling the mass variation using a pump. The water pumps are controlled using the event-based controller or Proportional Derivative (PD) controller. The results of the proposed control technique are verified with various external environmental disturbances and uncertainties to check the robustness of the control approach for various path following cases. Moreover, the results of STSMC scheme are compared with SMC scheme to check the effectiveness of STSMC. The practical implementation of the work is also performed using Simscape Multibody environment where the designed control algorithm is deployed on the virtual snake robot.

A novel combined control of flexible single-link manipulator based on singularly perturbed theory

Purpose This study aims to improve the control accuracy and antidisturbance performance of the manipulator with the flexible link, a combined controller, which combines the novel backstepping sliding mode controller based on the extended state observer (ESO) and super-twisting sliding mode controller. Design/methodology/approach First, the dynamic of the system is constructed by Lagrange method and assumed mode method, and then the dynamic is decoupled by the singular perturbation theory to obtain the slow-varying subsystem and fast-varying subsystem. For the slow-varying subsystem, the novel backstepping sliding mode controller based on ESO is used to achieve joint tracking. For the fast-varying subsystem, the super-twisting sliding mode controller is used for vibration suppression. At the same time, to suppress chattering, the tanh function is used to replace the sign function in the reaching law. Findings The simulation results show that the combined control has better trajectory tracking performance, antiinterference performance and vibration suppression performance than traditional sliding mode control (SMC). Originality/value A novel backstepping sliding mode controller based on ESO is designed to guarantee the performance of the tracking trajectory. The new controller improves the converge rate. A super-twisting sliding mode controller, which can stabilize the fast-varying subsystem, is used to suppress the vibration of flexible link.

Direct torque control of bearingless induction motor based on super-twisting sliding mode control

A bearingless induction motor (BIM) is an innovative magnetic levitation motor that incorporates torque system and suspension systems. Aiming to improve the anti-interference and levitation performance of the BIM, a second-order super-twisting sliding mode direct torque control strategy (STSM-DTC) is proposed. Initially, the basic principles and convergence conditions of the super-twisting algorithm are analysed. Subsequently, corresponding sliding mode surfaces are constructed according to speed, torque, and stator flux error, and the corresponding super-twisting sliding mode controllers (STSMC) are designed in the torque system. The STSMCs are designed based on the rotor radial displacement error and further enhanced by incorporating a differential loop in the suspension system. The hyperbolic tangent function tanh(x) is used as the switching function. Simulation and experimental of the BIM STSM-DTC system show that the STSM-DTC strategy effectively improves the anti-interference ability and suspension performance of the BIM, and show better dynamic response.

Speed Control for PMSM with Fast-Terminal Super-Twisting Sliding Mode Controller via Extended State Disturbance Observer

Since robustness is only maintained on the sliding-mode surface, sliding mode control is inherently non-globally stable. Therefore, reducing the time to reach the sliding mode is crucial for enhancing sliding mode robustness. To improve the performance of conventional super-twisting reaching law (CSTRL) further, we propose a fast-terminal super-twisting reaching law (FTSTRL) designed to improve the quality of sliding mode control. This approach incorporates a terminal term and an exponential term with the CSTRL to ensure rapid convergence. The effectiveness of the designed FTSTRL is validated by comparing it to the CSTRL and a new sliding mode reaching law, demonstrating its superior performance. Finally, integrated square error (ISE), integrated time square error (ITSE), integrated absolute error (IAE), and integrated time absolute error (ITAE) are employed for detailed comparative and quantitative analyses of the simulation results.

Multi-variable fuzzy adaptive time-varying sliding mode control (MVFATVSMC) of the reverse osmosis-photovoltaic desalination system

Among the different desalination systems, reverse osmosis is popular due to its specific characteristics. Two challenges in these systems are power supply and compensation for the imposed disturbances and uncertainties which affect the performance of the system. To study these two challenges all main subsystems of the photovoltaic-reverse osmosis (PV-RO) system are considered. A photovoltaic system is considered for power supply and robust controllers are proposed to deal with the uncertainties and disturbances. For these purposes, all parts of the PV-RO desalination process are considered. Maximum power is tracked in different sun radiations and temperatures using a Mamdani-type fuzzy controller optimized by the invasive weed algorithm (IWA). This new MPPT controller gets about 10 % more power, 60 % lesser fluctuations, and 20 % smaller rise time. The speed controller of the induction motor and the pressure controller are fuzzy-PID. An adaptive time-varying sliding mode control (ATVSMC) is proposed to control the RO system because this system is highly nonlinear with many uncertainties and disturbances. The controller has global robustness and regulates the system to the desired points at a specified time. In this controller, knowing the maximum limit of the system uncertainties is not essential, which is a practical advantage for the PV-RO system. The numerical simulations in different scenarios and a comparison to existing work show the superiority of the proposed controllers. This novel controller decreases the overshoot and settling time of the bypass stream velocity by about 3.5 % and 7.6 % in comparison to super-twisting sliding mode control (STSMC), respectively. The settling time of the retentate stream velocity has decreased by about 9 %. Moreover, there are no fluctuations in the control inputs and outputs, and the amplitude of the bypass stream control input has decreased by about 98 %.

Utilizing a Five-Level Inverter for Grid-Connected PV Systems: Implementing an MPPT Algorithm with Super Twisting Sliding Mode Control

Utilizing a Five-Level Inverter for Grid-Connected PV Systems: Implementing an MPPT Algorithm with Super Twisting Sliding Mode Control

Super-twisting ADRC for maximum power point tracking control of photovoltaic power generation system based on non-linear extended state observer

This paper proposed a new method for maximum power point tracking in photovoltaic power generation systems by combining super-twisting sliding mode control and active disturbance rejection method. An incremental guidance method is used to find the point of maximum power. The non-linear extended state observer is applied to estimate the unmodeled dynamics and external disturbance. The ADRC based on a super-twisting sliding mode is designed to bring the state variables to the desired state. In the next step, the stability of NESO and ADRC are theoretically proved. Finally, the simulation results have been compared with the results of the PI controller, classical sliding mode control, and terminal sliding mode control (TSMC) presented in other articles. The results show the effectiveness and superiority of the proposed method.Also, to check the performance of the proposal method in real-time, real-time results have been compared with non-real-time results. The results obtained from the real-time and non-real-time simulations exhibited a minimal difference. This fact indicates the high accuracy of the modeling and simulations performed. Indeed, the mathematical models and non-real-time simulations have been able to accurately mimic the actual behavior of the photovoltaic system under various operating conditions.

Adaptive Super-Twisting Sliding Mode Control of Microgrid Based on Fixed-Time Sliding Mode Observer

Adaptive Super-Twisting Sliding Mode Control of Microgrid Based on Fixed-Time Sliding Mode Observer

Enhanced Fuzzy-Based Super-Twisting Sliding-Mode Control System for the Cessna Citation X Lateral Motion

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC.