Super-twisting Sliding Mode Control Research Articles

Finite-Time Containment Control for Nonlinear Multi-Agent Systems Based on High Order Sliding Mode

Several finite-time containment control issues under stationary and dynamic leadership are the main emphasis of this thesis, which is concerned with a typical class of second-order nonlinear multi-agent systems susceptible to outside intervention. According to a given network topology, the second-order super-twisting sliding mode control is a technique for distributed control that has been developed. In this paper, we mainly consider the situation that the leader moves at a uniform speed. With the proposed method, the followers update status in real time via communication with each other such that all of them are able to eventually converge to the convex hulls consisting of stationary leaders and dynamic leaders in finite time. It leads to make the followers remain stationary or keep moving within the designed region. Eventually, according to the matrix theory and finite-time stability theorem, the paper proves the stability of the finite-time on the proposed control protocol and validates its effectiveness and correctness through simulation.

An Adaptive Sliding Mode Control for a Dual Active Bridge Converter With Extended Phase Shift Modulation

This paper introduces an adaptive super-twisting sliding mode control (ASTSMC) approach for controlling a dual active bridge (DAB) converter with an extended phase shift (EPS) modulation. The conventional single-phase shift (SPS) modulation-based DAB converter is known to be inefficient. Hence, an optimization algorithm based on the Lagrange multiplier method (LMM) is proposed to minimize both backflow power and inductor current stress simultaneously. Unlike the conventional schemes that use an offline optimization (OFFO) method to derive the phase shift ratios, this paper proposes an online optimization method and an ASTSMC method for generating the inner and outer phase shift ratio respectively. Initially, a generalized average modeling (GAM) for the DAB converter under EPS modulation is derived, and then the proposed ASTSMC is introduced according to this model. The conventional STSMC with constant gains suffers from low performance under disturbances such as load current perturbations, input voltage variations, and output voltage reference variations. Additionally, it requires an overestimated gain under steady-state conditions. To address these issues, a variable gain-based STSMC scheme is proposed to enhance the performance of the converter under all operating conditions. The effectiveness of the proposed method is verified through simulation and experimental results, which are compared with the results of the conventional STSMC method.

Super-Twisting Sliding Mode Control for the Stabilization of a Linear Hyperbolic System

This letter deals with the stabilization of a linear hyperbolic system subject to a boundary disturbance. Our feedback design relies on a super-twisting control algorithm, which leads to a feedback that is continuous with respect to the state, in contrast with the classical sliding mode design. Our first result is the existence of solutions of the closed-loop system. Moreover, the global asymptotic stability, that is our second result, is proved together with the guarantee that the disturbance is rejected.

Adaptive modified super-twisting sliding mode control based on PSO with neural network for lateral dynamics of autonomous vehicle

Adaptive modified super-twisting sliding mode control based on PSO with neural network for lateral dynamics of autonomous vehicle

Adaptive modified super-twisting sliding mode control based on PSO with neural network for lateral dynamics of autonomous vehicle

In this article, we have developed a strategy for controlling the lateral dynamics of an autonomous vehicle. The bicycle model of the autonomous vehicle is used. In order to improve the systems performance, we take a new dynamic surface of the sliding mode and a novel expression of the super twisting part of the controller. The parameters of the controller are determined using the particle swarm optimisation (PSO). The objective of this strategy is to follow the reference trajectory of the autonomous vehicle while reducing the lateral displacement error. The steering angle is the control input, the outputs of this system are the lateral displacement and the yaw angle. The radial basis function neural network (RBFNN) is used to approximate the unknown nonlinear dynamic. Simulation results show some improvements over the literature.

Neural-Network based Swing-up and Stabilization Control of Rotary Inverted Pendulum Systems

We propose the neural-network based control (NNC) approach for rotary inverted pendulum (RIP). The control structure for RIP consists of two phases: (i) swing-up phase, which drives the pendulum up towards the desired upright position; and (ii) stabilization phase, which enables the pendulum to keep the desired upright position. In our paper, the swing-up controller is designed based on energy control approach with feedback linearization technique, where the corresponding control gain Kec is determined by the proposed NNC. Next, the stabilization controller is designed based on modified super-twisting sliding-mode control (MSTSMC) algorithm, which requires to design a new sliding surface in order to achieve the asymptotic stability of RIP. Similar to the swing-up phase, the control gain KSS of the MSTSMC is determined intelligently by the proposed NNC. In fact, the proposed NNC allows to select Kec and KSS adaptively based on the operation of RIP. Finally, we provide the experimental comparisons between the proposed NNC and the control system of RIP without the neural-network framework. Through the experimental results, we show that by the NNC, the proposed control system of RIP provides the better swing-up and stabilization performances.

Robust path following control of 4WID autonomous vehicle with driving condition adaptive mechanism

This paper proposes a novel integrated path following control scheme for a 4-Wheel Independent Drive (4WID) autonomous vehicle that can adaptively change its mechanism according to the driving conditions. The proposed integrated system handles the lateral steering controller, longitudinal speed, and yaw moment controls considering tire force capacity of each corner. For the lateral controller, the cornering stiffness uncertainties and the transient performance are considered and combined into an H∞ robust controller based on linear matrix inequality (LMI) theory. A super-twisting sliding mode controller (STSMC) based longitudinal controller is designed to deal with disturbances and suppress chattering. When encountering extreme conditions, the active yaw moment controller with hierarchical structure is adaptively activated to prevent large deviation from the reference path and maintain the stability of vehicle. For the tire force allocation, an optimization algorithm is proposed, which has flexible equality constraints to coordinate the longitudinal and lateral motions according to the driving conditions. Simulations based on Carsim-Simulink co-simulation platform show that the proposed method is effective and has excellent performance in both normal and extreme driving conditions.

Sliding Mode Based Load Frequency Control and Power Smoothing of Power Systems with Wind and BESS Penetration

This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. A novel comprehensive control framework is proposed for power systems integrated with wind farms and BESS based on an adaptive fuzzy super-twisting sliding mode control (AF-SSMC) method. Firstly, the sliding functions and control laws of subsystems are designed according to different relative degrees. Then, the super-twisting algorithm is applied to suppress the chattering of the sliding mode control law. Furthermore, an adaptive fuzzy control method is used to adjust the control gains online for better control performance of the controllers. The Lyapunov stability theory is employed to prove the asymptotic stability of the subsystems. The model of an interconnected thermal power system with wind and BESS penetration is also constructed for simulation analyses. The results indicate that the AF-SSMC method effectively reduces the chattering, and the proposed framework stabilizes the frequency of the power system under system uncertainties and external disturbances. Moreover, the wind farm and BESS combined system accurately tracks a reference power to reduce wind power fluctuations.

Adaptive disturbance observer-based improved super-twisting sliding mode control for electromagnetic direct-drive pump

In this study, to enhance the frequency-flow characteristics of the novel electromagnetic direct-drive pump (EDDP). An adaptive disturbance observer-based improved super-twisting sliding mode control (ISTSMC-ADOB) is proposed to address the problem in which the response quality is deteriorated by factors such as parameter mismatch and disturbance. An adaptive disturbance observer (ADOB) is designed to achieve adaptive compensation, avoid the use of high-gain feedback, and extend the applicability of the conventional disturbance observer. An improved super-twisting sliding mode control (ISTSMC) based on the fast terminal sliding mode algorithm is designed to ensure faster convergence of the error in finite time. By combining the ADOB with the ISTSMC, the conservative parameter selection of the sliding mode control (SMC) is avoided, and the accuracy and robustness are further strengthened. The stability is analyzed based on Lyapunov. The results show that the proposed method effectively improves the steady-state accuracy, response speed, and robustness in trajectory tracking of the electromagnetic linear actuator for the EDDP. This further enhances the frequency-flow characteristics of the system.

Position and stiffness control of an antagonistic variable stiffness actuator with input delay using super-twisting sliding mode control

Motor dynamics in antagonistic variable stiffness actuator (AVSA) is generally disregarded in control system design. This ignorance can lead to an inaccurate system model, affecting the performance of the closed-loop system. The motor dynamics can be modeled as an input-delay in actuator model. In this paper, the motor dynamics is modeled as the input time-delay for an AVSA for the first time. The stiffness of AVSA is a nonlinear function of system states; thus, stiffness tracking for an AVSA is a challenging task. Specifically, many of the existing delay compensation controllers cannot be used for stiffness tracking when the model contains input delay. To handle this issue, a nonlinear transformation is introduced and a super-twisting sliding mode control is then utilized to reach position and stiffness tracking simultaneously. Prediction-based feedback is involved together with some disturbance observers for estimating the external disturbance to compensate for the input time-delay. Simulation results show that the proposed design approach is successful in position and stiffness tracking and simultaneously in attenuating the external disturbance effect.

Convergence Trajectory Optimization of Supertwisting Sliding-Mode Current Control for Induction Motor Drives

For the induction motor (IM) current loop, the supertwisting sliding-mode control (ST-SMC) has been considered as an effective approach to achieve chattering suppression and steady-state errorless control. However, due to the system disturbance, the conventional ST-SMC suffers from control delay in the convergence trajectory, resulting in decreased antidisturbance capability. To address this problem, this article proposed a ST-SMC with convergence trajectory optimization. First, a nonlinear sliding-mode manifold is designed to achieve the ideal ST-SMC convergence trajectory. Then, a disturbance compensation term is added into the control law to eliminate the system control delay. Compared with the conventional ST-SMC, the studied method can effectively enhance the antidisturbance capability of IM current loop, leading to improved transient performance. Finally, the superiority of the investigated method is verified by the experimental results from a 3.7 kW IM test bench.

A Fractional Order Super Twisting Sliding Mode Controller for Energy Management in Smart Microgrid Using Dynamic Pricing Approach

A real-time energy management strategy using dynamic pricing mechanism by deploying a fractional order super twisting sliding mode controller (FOSTSMC) is proposed for correspondence between energy users and providers. This framework, which controls the energy demand of the smart grid’s users is managed by the pricing signal provided by the FOSTSMC, issued to the smart meters, and adjusts the users’ demand to remove the difference between energy demand and generation. For the implementation purpose, a scenario based in MATLAB/Simulink is constructed where a sample renewable energy–integrated smart microgrid is considered. For the validation of the framework, the results of FOSTSMC are compared with the benchmark PI controller’s response. The results of the benchmark PI controller are firstly compared in step response analysis, which is followed by the comparison in deploying in renewable energy–integrated smart grid scenario with multiple users. The results indicate that the FOSTSMC-based controller strategy outperformed the existing PI controller-based strategy in terms of overshoot, energy balance, and energy price regulation.

Cooperative payload transportation with real-time formation control of multi-quadrotors in the presence of uncertainty

This paper considers the trajectory tracking for a cable-suspended rigid body carried by multiple quadrotors while maintaining the desired formation. A three-loop control structure is proposed based on the Super Twisting Sliding Mode (STSM) controller with high robustness to compensate for uncertainties and disturbances. In the proposed structure, a proper formation based on a centralized approach creates advantages such as collision avoidance and non-entanglement of the cables, which leads to uniform load distribution on all quadrotors to optimize energy consumption. The corresponding equations are formulated as a convex constrained optimization problem with an analytical solution for calculating the cables' tension. This approach is a straightforward and computationally efficient method for real-time applications. In addition to proving the system's stability by Lyapunov theory, the simulation results show good performance in the presence of disturbance and uncertainty.

Publisher’s Note

Medium Voltage DC (MVDC) integrated power systems are anticipated to feed the submarines and surface combatants. The MVDC based power systems use dc/dc converters tightly regulated via high bandwidth controllers act as constant power loads (CPL’s). The negative incremental impedance of the CPL’s may result in voltage instability in the system under disturbance. Thus for the efficient and robust control of the MVDC based power system, this paper proposes a high order sliding mode control (HOSMC) paradigm based on model-free adaptive super twisting sliding mode control (ASTA-SMC). This paper initially designs a first-order sliding mode control (FOSMC) and super twisting sliding mode control (STA-SMC) based on HOSMC DC link voltage controllers. The difficult task of gain tuning in timely varying conditions is resolved by incorporating adaptive control to STA-SMC. The proposed controller is validated and compared with pre-presented control schemes under two test cases using simulation and experimental workbench carried out in dSPACE based hardware in the loop (HIL) workbench. The adaptive STA-SMC (ASTA-SMC) is compared with FOSMC and feedback linearization-based control schemes. The stability of ASTA-SMC in finite time is validated using the Lyapunov stability theorem.

Super-Twisting Sliding Mode Control with SVR Disturbance Observer for PMSM Speed Regulation

Sliding mode control and disturbance compensation techniques are applied to a nonlinear speed control algorithm for a permanent magnet synchronous motor (PMSM). Optimizing the speed control performance of PMSM systems with various disturbances and uncertainties is challenging. To achieve a satisfactory performance, a sliding mode control method based on the super-twisting algorithm reaching law (STRL) is presented. STRL can adapt dynamically to the variations of a controlled system. The STRL maintains a high tracking performance of the controller and allows the control input to eliminate chattering. To estimate the uncertainties and compensate for disturbances, a support vector regression-disturbance observer (SVR-DOB) is presented. The estimated uncertainties were used to minimize modeling errors and improve the disturbance rejection. A controller using SVR-DOB achieves a high precision, and the simulation results demonstrated the validity of the proposed control approach.

Distributed total-amount optimal coordinated control of multi-motors with input and output saturation

Specific to the double saturation constraints of input and output in multimotor network systems, an anti-windup control framework with distributed total-amount optimal coordination is constructed, and a new saturated super-twisting sliding mode control strategy is designed in this paper. First, a mathematical model of direct torque and flux control of a multipermanent magnet synchronous motor is established. Next, the consistency of the total amount and output saturation are taken as the constraint conditions. Considering the lowest total energy consumption, the optimal multi-axis total-amount coordinated allocation algorithm is designed on the basis of the Karush-Kuhn-Tucker (KKT) condition. Then, the input saturation is introduced into the dynamic integral part of the super-twisting algorithm. A new saturated super-twisting sliding mode tracking control algorithm is designed, and the barrier Lyapunov function is used to prove the input constraint. Finally, the Matlab/Simulink simulation and RT-LAB semi-physical experiments verify that the anti-windup control strategy of distributed total-amount optimal coordination can effectively solve the double saturation constraints of input and output.

Guest editorial: Decision making and control for connected and automated vehicles

Guest editorial: Decision making and control for connected and automated vehicles

Super-twisting control design of speed regulation and tracking for a surface-mounted PMSM

This work is devoted to presenting a second-order sliding mode control for speed regulation and tracking for a surface-mounted permanent magnet synchronous motor. We tune the conventional PI controllers using the field-oriented control scheme. On the other hand, we design a generalized super-twisting sliding mode control, improving the performance characteristics when the machine is under the effects of external torque. Finally, a high-precision emulator is used to validate the theoretical results.

Fractional‐order sliding mode attitude coordinated control for spacecraft formation flying with unreliable wireless communication

This paper investigates the coordinated attitude control problem with fractional order sliding mode control theory for spacecraft formation flying by considering of unknown disturbance, inertia uncertainty, partial loss of actuators, and communication delay. Two types of fractional order sliding mode control laws are proposed to solve the considered design problem. The first one is based on the Chebyshev neural network technique, and the second one is involved with the integral-type and super-twisting sliding mode control methods. Compared to traditional sliding mode control methods, the developed fractional order sliding mode control strategies can achieve a faster convergence speed. Simulation results based on a group of three spacecrafts are presented to demonstrate the performance of the proposed coordinated attitude control approaches.

Super-twisting Sliding Mode Control for a Multifunctional Double Stage Grid-connected Photovoltaic System

This paper proposes a super-twisting sliding mode control for a multifunctional system that includes a Photovoltaic (PV) system connected to the grid through the Active Power Filter (APF). The latter is implemented to improve the power quality in the grid side, and injecting the provided photovoltaic power into the grid. Sliding mode control is known as a powerful control with good performance in transient and steady-state conditions. In this work, a Super-Twisting Sliding Mode Control (ST-SMC) is applied to extract the maximum power from the PV source, corresponding to the irradiation level, as well as to the three-phase inverter-based-APF power control. For the system to inject the generated power from the PV source into the grid with respect to the international standards, fulfilling the active power filtering, synchronous reference frame theory is used to generate the appropriate reference signals for harmonic and reactive power compensation. To test the multi-functionality of the system (PV-APF), this one is connected to a grid supplying nonlinear loads that absorb non-sinusoidal currents. Through the simulation results, it has successfully achieved the multi-functionality of the proposed system under steady-state and dynamic conditions. The results also show the effectiveness and moderation of the proposed super-twisting sliding mode control. Furthermore, a comparative study has been established over the conventional PI controller, showing the clear superiority of the proposed control in every aspect.