Super Twisting Research Articles

Active disturbance rejection control for systems with uncertainties and noise using super twisting differentiator-based event-triggered ESO

This paper focuses on the noise suppression issue of high-gain extended state observer (ESO) for systems with uncertainty and unknown measurement noise in the active disturbance rejection control (ADRC) paradigm. A special combination of super twisting differentiator (STD) and event-triggered ESO is devised with a designed event-triggered mechanism. Specially, the proposed STD-ETESO incorporates a finite-time switching strategy, which improves the poor transient performance of the STD acting as a pre-filter to prepare relatively smooth signals for the ESO. The locally asymptotic boundedness of the estimation error can be guaranteed by the Input-state-stability (ISS) and existing research for the STD. The effectiveness of the proposed method is validated by a general example and a practical motion control system. Different integral criteria is introduced to evaluate the overall tracking accuracy and energy usage for comparison with existing different ESOs, which reveals the superiority of the proposed STD-ETESO in noise attenuation and disturbance rejection.

A Robust Super Twisting Controller Algorithm for Dual Star Induction Motor Based on Particle Swarm Optimization Algorithm

This research introduces an optimized control approach for a dual star induction motor (DSIM) using a combination of the Super Twisting Algorithm (STA) and Particle Swarm Optimization Algorithm (PSO) within the framework of indirect field-oriented control (IFOC) and two pulse width modulation (PWM) voltage sources. The primary aim of this study is to reduce torque fluctuations, minimize variations in stator current, and enhance the precision of speed control. The DSIM consists of two sets of three-phase windings with separate neutrals and a 30-degree electrical phase shift. The utilization of the STA control method addresses issues related to response time, steady-state error, and the impact of load disturbances, ultimately improving speed control. The Simulation conducted in MATLAB/SIMULINK are used to compare the performance of the proposed STA-PSO controller against a conventional Proportional-Integral (PI) controller. The outcomes demonstrate the substantial enhancements achieved by the STA-PSO controller in speed control, including reduced response time, improved steady-state error, and increased resilience against external disturbances. The proposed STA-PSO control strategy effectively mitigates torque and stator currents fluctuations in DSIM’s while offering superior speed control performance. These findings underscore the potential of the STA controller for enhancing control in various DSIM applications.

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.

Adaptive terminal sliding combined super twisting control design and flight tests for automatic carrier landing system

Considering the challenges posed by external disturbances on carrier-based aircraft landing control, higher demands are required for the precision and convergence of the carrier landing control system. First, this paper proposes an Adaptive Terminal Sliding Combined Super Twisting Control (ATS-STC) method to address the issues of low precision, slow convergence, and poor disturbance rejection capability resulting from external disturbances, such as carrier air-wake and deck motion. By introducing a nonlinear term into the sliding surface and employing an integral approach, the proposed ATS-STC method can ensure finite-time convergence and mitigate the chattering problem. An adaptive law is also utilized to estimate the external disturbances, thereby enhancing the anti-disturbance performance. Then, the stability and convergence time analysis of the designed controller are conducted. Based on the proposed method, an Automatic Carrier Landing System (ACLS) is developed to perform the carrier landing control task. Furthermore, a multi-dimensional validation is carried out. For the numerical simulation test, the Terminal Sliding Mode Control (TSMC) method and Proportion Integration Differentiation (PID) method are introduced as comparison, the quantitative assessment results show that the tracking error of TSMC and PID can reach 1.5 times and 2 times that of the proposed method. Finally, the Hardware-in-the-Loop (HIL) test and real flight test are conducted. All the experimental results demonstrate that the proposed control method is more effective and precise.

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

Application of Robust Super Twisting to Load Frequency Control of a Two-Area System Comprising Renewable Energy Resources

The main concern of the present article is to design a robust load frequency control for a two-area power system (TAPS) comprising renewable energy resources. Three different controllers are suggested. The first is based on a robust super twisting (ST) technique, which is an enhanced approach of the sliding mode control and is considered to be one of the most excellent control techniques. The second and the third are based on two recent metaheuristic techniques, namely the one-to-one based optimizer (OOBO) and hippopotamus optimizer (HO). The studied TAPS contains different energy resources, such as solar thermal, photovoltaic, wind energy, hydropower and energy storage in addition to other conventional sources. The OOBO and HO are used to determine the parameters of PI controllers, and the objective function is to minimize the integral square error of frequency and tie line power. The obtained results verify the high performance of the suggested three controllers with superiority to ST because of its intrinsic capability to cope with parameter changes.

Sliding Mode Controller for Temperature Control Lab Arduino Kit

Sliding Mode Control, a resilient and efficient control technique widely adopted in engineering, addresses the challenges of managing systems operating in uncertain environmental conditions. To quickly evaluate and validate the effectiveness of Sliding Mode Control, researchers can select a simple test bench like an open-source APMonitor Temperature Control Lab kit. This kit comes with MATLAB-Simulink/Python to support real-time simulation and testing. The novelty of the work is to design and implement non-linear controllers like Sliding Mode Control and Super Twisting Control techniques. Closed loop hardware in loop simulation with the designed non-linear controllers and detailed analysis is performed under tracking and disturbance rejection conditions.

Ultralocal Model-Free Adaptive Supertwisting Nonsingular Terminal Sliding Mode Control for Magnetic Levitation System

The magnetic levitation technology has attracted blooming attention from all walks of life thanks to its superiorities such as non-contact and active control. While the intrinsic features of open-loop instability and strong nonlinearity, along with the uncertain external disturbance make the levitation control particularly significant and difficult. For speeding up the convergence and obtaining a better stability and disturbance robustness, this paper proposes an ultra-local model-free adaptive super-twisting nonsingular terminal sliding mode control (ULMF-ASTNTSMC) strategy for the magnetic levitation system. Different from the conventional model-based control, ultra-local model-free control breaks the constraint of a precise system model. Therefore, an improved second-order ultra-local model is established for the magnetic levitation system. For the benefit of finite time convergence and non-singularity, the nonsingular terminal sliding mode surface is chosen. As a second-order algorithm, super-twisting (ST) algorithm can fundamentally suppress the chattering effect of the sliding mode control (SMC). An adaptive super-twisting algorithm is designed for the further improvement of the system dynamic response. The stability of the proposed scheme is strictly verified based on the Lyapunov stability theory. Simulation and experimental comparisons with the existing control methods validate the exceeding performance of the proposed strategy under various operating conditions.

Real-time adaptive super twisting algorithm based on PSO algorithm: application for an exoskeleton robot

Abstract In this paper, an online adaptive super twisting sliding mode controller is proposed for a non-linear system. The adaptive controller has been designed in order to deal with the unknown dynamic uncertainties and give the best trajectory tracking. The adaptation is based on an optimal Particle Swarm Optimization (PSO) algorithm whose goal is online tuning the parameters through focusing on decreasing the objective function. The novelty of this study is online handling parameters setting in the conventional super twisting algorithm, bypass heavy offline calculation, and also avoid the instability and abrupt changing of the controller’s parameters for better actuators lifetime. This novel approach has been applied on an upper limb exoskeleton robot for arm rehabilitation. Despite the changes of the dynamic model of the system which defers from one patient to another due to the direct interactions between the wearer and the exoskeleton, this control technique preserves its robustness with respect to bounded external disturbances. The effectiveness of the proposed adaptive controller has been proved in simulation and then in real-time experiment with two human subjects. A comparison between the proposed approach and classic super twisting algorithm has been conducted. The obtained results show the performance and efficiency of the proposed controller.

Nonlinear control strategies for a floating wind turbine with PMSG in Region 2: A comparative study based on the OpenFAST platform

This study examines new control strategies for floating offshore wind turbines (FOWTs) equipped with permanent magnet synchronous generators (PMSG), and operating in Region 2. The aim is to maximize power production while minimizing fatigue loads within wind speed limits. This is achieved by maintaining optimal tip speed ratio (TSR) using diverse control strategies. Control design based on the OpenFAST model is not trivial due to FOWTs’ dynamics. Adaptive gain versions of super-twisting (STW) control methods are proposed to address this, requiring minimal system knowledge while simplifying controller gains tuning. These controllers also adapt to parameter changes, ensuring robustness. A comparative analysis of STW-based control versus baseline control demonstrates its effectiveness in maximizing power production under numerous different conditions.

Optimal super twisting sliding mode control strategy for performance improvement of islanded microgrids: Validation and real-time study

It is essential to improve optimal control for an autonomous microgrid operation. This paper presents a novel application of an artificial hummingbird algorithm for achieving optimal control of an autonomous microgrid. It also suggests a comparative analysis for the optimal super-twisting sliding mode control with both optimal fuzzy logic control and optimal proportional-integral control. The proposed super-twisting sliding mode controller parameters are adequately designed by using the AHA optimization method; meanwhile, the FLC and PI controllers are designed by using the African vultures and the Gorilla troops optimization algorithms, respectively. A MATLAB/Simulink environment is used to verify the effectiveness of the suggested microgrid control methods. The overall system detailed approaches for modeling, designing, and controlling are introduced. The investigation of the ST-SMC approach is also tested in a real-time setting. OPAL-RT 4510 rapid control prototyping and OPAL-RT 8660 data acquisition are used to implement the suggested controller. The verification results prove the superiority of the ST-SMC based on the AHA optimization technique compared with other optimal control techniques.

An improved nonsingular adaptive super twisting sliding mode controller for quadcopter.

This paper presents an improved nonsingular adaptive super twisting sliding mode control for tracking of a quadrotor system in the presence of external disturbances and uncertainty. The initial step involves developing a dynamic model for the quadrotor that is free from singularities, achieved through the utilization of the Newton-Quaternion formalism. Then, the super twisting algorithm is used to develop a novel sliding mode control that mitigates chattering. Particle Swarm Optimization (PSO) is employed for the adjustment of the controller gains. Moreover, to maintain stable control of the quadcopter, even in scenarios where the upper limit of disturbances is unknown, an adaptive rule grounded in Lyapunov stability is applied. Simulation results demonstrate that the proposed controller reduces tracking errors to 0.1% for roll, 0.05% for pitch, and 2.2% for altitude, outperforming other state-of-the-art sliding mode controllers. Additionally, the proposed controller effectively rejects disturbances, maintaining minimal steady-state errors of 0.01° for roll, 0.02° for pitch, and 0.001° for yaw, significantly better than conventional controllers. These results highlight tracking and disturbance rejection capabilities of the proposed controller, making its real-time implementation for quadrotor Unmanned Aerial Vehicles (UAVs) feasible.

Real-Time Implementation of a Hybrid ESC Approach for Maximising the Extracted Photovoltaic Power Under Partial Shading Conditions

Abstract Solar energy, an available and renewable resource, can be efficiently transformed into electrical energy through the use of photovoltaic (PV) cells. The primary emphasis lies in the significance of maximising power output for economic considerations. In terms of optimising power generation, the implementation of maximum power point tracking (MPPT) techniques is imperative. A range of approaches, such as super twisting (ST) control and modified extremum seeking control (ESC-mod), are explored for their potential in enhancing the efficiency of power-generation systems. The novelty is a combination of these methods; the modified ESC has the role of finding the optimum voltage value of the global maximum power point (MPP) during the partial shading, while the super-twisting improves the performance of the system. The efficacy of the MPPT algorithm is assessed across diverse conditions, encompassing scenarios with load variations and fluctuating irradiances (uniform and non-uniform). The experimental setup involves essential components such as a PV generator, a boost converter and a resistive load. This comprehensive testing aims to evaluate the algorithm’s performance under varying circumstances, providing insights into its adaptability and effectiveness across different operational conditions. The system is modelled, simulated using Matlab–Simulink and implemented using a dSPACE 1104 card. Simulation results indicate that ST control is faster in reaching the permanent regime, but ESC-mod provides smoother performance in the permanent regime. The integration of both ST control and ESC-mod methods proves advantageous by diminishing the response time in the seeking process while concurrently ensuring a consistent and smooth operation in the permanent regime. This combined approach has undergone practical implementation and testing across diverse conditions, encompassing both optimal, healthy states and shaded environments. The results affirm the method’s ability to deliver efficient and stable performance across a spectrum of operating conditions.

Trajectory Tracking of Tracked Robot Using Super Twisting Algorithm With Enhanced Boundary Layer and Dynamics Incorporating Gravity Center Offset

Trajectory Tracking of Tracked Robot Using Super Twisting Algorithm With Enhanced Boundary Layer and Dynamics Incorporating Gravity Center Offset

Dynamical analysis and decision support system of production management

Nonlinear system dynamics and feedback control theory are presented for management optimization of supply chain systems. Linearization and simplification methods are widely used in analyzing the system dynamics of supply chains because actual production models are highly complex and nonlinear systems. With advanced system dynamics, it is possible to deal directly with nonlinear dynamical problems without linear approximate methods so that the decision-makers can obtain more accurate results for systematic management strategies. This paper proposes a nonlinear system theory to explore dynamical behavior and control synthesis of production-distribution systems using Forrester’s model. A novel super-twisting sliding mode control (SWT-SMC) algorithm has been presented based on adaptation law, ensuring management optimization against disruptions. The closed-loop system stability has been guaranteed by using the Lyapunov theory. Extensive numerical simulations have been conducted to validate the efficacy and reliability of the adaptive super-twisting sliding mode control (ASWT-SMC) algorithm. Four types of decision criteria have been employed to compare system performance between control strategies. With a superb decision scheme powered by a control algorithm, novel supply chain software can learn an ever-fluctuating production flow and anticipate the need for changes in a real market.

Improved super-twisting sliding mode control strategy in permanent magnet synchronous motors for hydrogen fuel cell centrifugal compressor

This paper rigorously addresses the intricate control demands of high-speed, high-pressure, wide adjustable speed range, and high energy utilization efficiency required in hydrogen fuel cell centrifugal compressor, with a focus on the speed control of 40,000 RPM permanent magnet synchronous motors (PMSMs). An improved second-order super twisting sliding mode control (STSMC) strategy is proposed to enhance system stability and robustness by integrating the beetle antennae search (BAS) algorithm and grey wolf optimization (GWO) algorithm. The global search capability of BAS is used to improve the local optima issues of GWO, and then the improved GWO algorithm is utilized to address the issues related to parameter selection and convergence speed inherent in the STSMC. Theoretical validity of the proposed strategy is asserted through Quadratic Lyapunov Function, and its practicality is affirmed by thorough simulation. Comparative analyses are conducted with PI controller, traditional Sliding Mode Controller (SMC), and standard Super-Twisting Sliding Mode Controller (ST) under several case studies to show the superiority of the propose STSMC.

Enhanced Control of Dual Star Induction Motor via Super Twisting Algorithm: A Comparative Analysis with Classical PI Controllers

Enhanced Control of Dual Star Induction Motor via Super Twisting Algorithm: A Comparative Analysis with Classical PI Controllers

Model‐free based adaptive finite time control with multilayer perceptron neural network estimation for a 10 DOF lower limb exoskeleton

SummaryThis article presents a Model‐Free Adaptive Nonsingular Fast Terminal Sliding Mode Controller with Super Twisting and Multi‐Layer Perceptron (MLP) neural network for motion control of a 10 DOFs lower limb exoskeleton used in rehabilitation. The proposed controller employs a second‐order ultra‐local model to replace the complex dynamics of the exoskeleton and uses an MLP neural network to estimate the lumped disturbance of the ultra‐local model. To ensure accurate tracking of the desired trajectory and address the estimation errors of the MLP, an Adaptive Nonsingular Fast Terminal Sliding Mode Controller is introduced. Moreover, a Super Twisting approach is employed to eliminate the chattering phenomenon. The system's stability is analyzed using Lyapunov theory, and the desired trajectories are obtained from surface electromyography (EMG) signal measurements. The effectiveness of the proposed controller is validated through co‐simulation experiments using SolidWorks, Simscape Multibody, and MATLAB/Robotics Toolbox. Results demonstrate significant improvements in stability and precision compared to existing model‐free controllers.

Fuzzy super twisting mode control of a rigid-flexible robotic arm based on approximate inertial manifold dimensionality reduction.

The control of infinite-dimensional rigid-flexible robotic arms presents significant challenges, with direct truncation of first-order modal models resulting in poor control quality and second-order models leading to complex hardware implementations. To address these issues, we propose a fuzzy super twisting mode control method based on approximate inertial manifold dimensionality reduction for the robotic arm. This innovative approach features an adjustable exponential non-singular sliding surface and a stable continuous super twisting algorithm. A novel fuzzy strategy dynamically optimizes the sliding surface coefficient in real-time, simplifying the control mechanism. Our findings, supported by various simulations and experiments, indicate that the proposed method outperforms directly truncated first-order and second-order modal models. It demonstrates effective tracking performance under bounded external disturbances and robustness to system variability. The method's finite-time convergence, facilitated by the modification of the nonlinear homogeneous sliding surface, along with the system's stability, confirmed via Lyapunov theory, marks a significant improvement in control quality and simplification of hardware implementation for rigid-flexible robotic arms.