Sliding Mode Algorithm Research Articles

Research on ride control strategy of electromagnetic suspension based on sliding mode algorithm

This study proposes a main inner loop control technique to address the dynamic response of the electromagnetic suspension during vehicle driving. The genetic algorithm is employed to optimize the control parameters of the linear quadratic adjustment controller in the control main loop, with the aim of achieving the desired control force. In the control inner loop, a closed-loop sliding mode controller is designed based on the exponential approximation law to regulate the current. The Lyapunov function was utilized to assess the stability of the controller in terms of its theoretical feasibility. The simulation results of Matlab/Simulink show that under the given working conditions, compared with the passive suspension, sliding mode control and fuzzy sliding mode control for references, the root mean square value and peak value of the vertical acceleration of the body and the dynamic load of the tire with the improved sliding mode control are significantly reduced, the root mean square value of the dynamic deflection of the suspension was not improved. However, on the whole, the ride comfort of the vehicle has been improved.

Self-sensing sliding mode control of workpiece chatter based on accurate prediction of machining vibration

The previous works concerning active chatter suppression in milling systems are generally carried out based on specially designed tool holders or spindles. Due to the continuous removal of materials, however, the workpiece system cannot be treated as quasi-static or rigid. In this paper, a manufacturing system based on the digital twins (DT) model and sliding mode (SM) controller is developed to suppress the milling chatter of thin-walled workpieces. A single degree of freedom (DOF) model of the workpiece is adopted to describe the milling system. The developed SM algorithm exhibits a good performance under the variations of modal parameters, cutting parameters, unmodeled dynamics, etc. To provide accurate control feedback, a DT model of workpiece vibration is established by presenting a self-sensing predictive method. The predictive methods are implemented based on the cooperation of the combination methods of beam functions (CMOBF) and the mode superposition method (MSM). In addition, the predictive accuracy is discussed quantitatively by establishing a dataset of error coefficients. The data of error coefficients are trained by the support vector machine (SVM) model, which is introduced to the predictive methods for further error modification. Finally, a DT framework is introduced briefly to combine the machining system and the control process. Based on the developed DT-driven manufacturing system, the information interaction between the control process and the vibrating system can be realized.

COMBINED FIRST AND SECOND-ORDER SLIDING MODE CONTROL OF INDUCTION MOTOR

This paper uses hybrid sliding mode control to solve an output feedback tracking problem for the induction motor (IM). The main idea of this approach lies in the design of a law that ensures a smooth transition between two sliding regimes based on the choice of two sliding surfaces, one being linked to the other. The control is a combination of first and second-order sliding modes. The proposed approach controls the speed and rotor flux amplitude of the induction motor and guarantees the stability of the decoupled speed and rotor flux by using a Lyapunov method. The hybrid sliding mode algorithm provides robustness despite external disturbances and parameter variations. The controller has been implemented on an experimental setup, and results are presented to confirm the proposed method's effectiveness, robustness, and good performance.

Control of Stewart platform using adaptive smooth integral sliding mode algorithm

The Stewart platform, renowned for its remarkable dexterity, high stiffness, and positioning accuracy, is increasingly employed in a wide range of applications. For the Stewart platform, a novel adaptive super-twisting based smooth integral sliding mode controller (ASTSISMC) is suggested through modifications to the integral sliding mode algorithm. Specifically, the discontinuous portion of the integral sliding mode control law is replaced by the super-twisting control to ensure smooth cumulative control. Additionally, the gains associated with the super-twisting control law are made adaptive, or they are made to vary in accordance with the amplitude of the disturbances. As an alternative to the previous one, an adaptive twisting smooth integral sliding mode controller (ATSISMC) is also suggested for the Stewart platform. The efficacy of the newly proposed controllers is validated using the results obtained from MATLAB simulation.

Robust blade pitch control of semi-submersible floating offshore wind turbines based on the modified super-twisting sliding-mode algorithm

In this paper, a novel robust collective blade pitch controller (CBPC) is proposed for the semi-submersible floating offshore wind turbine (FOWT) above the rated wind speed. The proposed CBPC is based on the modified super-twisting sliding-mode (MSTSM) algorithm. Firstly, based on a control-oriented model of the semi-submersible FOWT, the dynamics of the rotor speed and the platform pitch rate considering the lumped disturbances, which consist of external disturbances, parametric uncertainties and unmodeled dynamics, are derived. Afterward, the MSTSM algorithm-based CBPC (MSTSM-CBPC) is designed for regulating the generator power to its rated value and reducing the platform pitching motion. Comparative co-simulation tests among the gain-scheduling proportional-integral CBPC, the standard STSM algorithm-based CBPC and the proposed MSTSM-CBPC are performed. Simulation results validate the effectiveness and the superiority of the proposed MSTSM-CBPC.

Vehicle Stability Control Based on Vehicle Motion State and Tire Force Estimation

The direct yaw moment control system is able to greatly enhance the vehicle stability when driving on challenging road surfaces. This paper introduces a direct control approach for managing the vehicle yaw moment, utilizing terminal sliding mode control and a Square Root Cubature Kalman Filter (SRCKF). Initially, the longitudinal and lateral forces acting on the vehicle's tires are estimated through a sliding mode observer. Subsequently, the SRCKF algorithm and the four-wheel tire force are employed to accurately estimate the yaw rate and sideslip angle. Based on these estimations, additional yaw moments are determined using the terminal sliding mode control algorithm, and a combined control of yaw rate and sideslip angle is achieved through a threshold method. A rule-based braking force distribution strategy is then implemented to ensure vehicle stability control. Simulation results demonstrate that the tire force estimations from the sliding mode observer and the vehicle yaw rate and sideslip angle estimations from the SRCKF algorithm closely align with the output results from Carsim, with an error margin of less than 15%. The braking force distribution strategy, based on the direct yaw moment control using the terminal sliding mode algorithm, effectively tracks the desired yaw rate and sideslip angle.

Fault-tolerant controller design with connectivity maintenance in fractional-order multi-agent systems using a super-twisting sliding mode algorithm

This article explores fault analysis in distributed fractional multi-agent systems, specifically addressing fault detection in nonlinear fractional-order multi-agent systems by introducing a sliding surface. To achieve fault detection, we employ a super-twisting sliding mode observer designed for accurate fault estimation within individual agents. Building on this, we present a new fractional-order sliding surface accompanied by a potential function, strategically designed to ensure connectivity maintenance. Drawing on the estimated fault and the fractional-order sliding surface, we propose a fault-tolerant controller. This controller operates within a finite time frame, simultaneously guaranteeing fault tolerance and connectivity maintenance. To demonstrate the effectiveness of our approach, we conduct simulations on three numerical examples. These examples represent heterogeneous systems with both directed and undirected graph topologies, showcasing the versatility and applicability of our proposed methodology.

Adaptive super-twisted sliding mode trajectory tracking control for quadrotor UAV with prescribed performance based on finite-time disturbance observer

This study proposes a finite-time disturbed observer-based prescribed performance adaptive super-twisted sliding mode trajectory tracking control scheme for quadrotor UAV. Based on the super-twisted sliding mode algorithm, adaptive control, finite-time theory, and prescribed performance control, this scheme aims to achieve stable tracking of a quadrotor UAV along a defined trajectory. This is achieved even when faced with challenges such as modeling uncertainty, external uncertainty, and complex interference environments. Firstly, the coupling between the channels and the disturbance effects are unified as the aggregate disturbance. To address the issue of the adverse impact of aggregate disturbance on system performance, a new finite-time disturbance observer is developed to estimate the overall disturbance. The observer can effectively eliminate the negative effects of the aggregate disturbance without considering the disturbed boundary conditions during the design process. Secondly, the disturbance estimation information and the adaptive super-twisted algorithm are used to construct the adaptive super-twisted sliding mode controllers for the position and attitude loops, respectively. Then, a prescribed performance control is designed to predefined the time for the position loop to effectively suppress the deleterious effects of interference. This ensures that the position system can quickly meet the prescribed tracking requirements. Finally, the stability of the designed trajectory tracking control system is demonstrated using the Lyapunov theorem. Numerical simulation results verify the effectiveness and superiority of the proposed controller.

Adaptive Attitude Roll Control of Guided Projectile Based on a Novel Unidirectional Global Sliding Mode Algorithm

Adaptive Attitude Roll Control of Guided Projectile Based on a Novel Unidirectional Global Sliding Mode Algorithm

Multi-wing chaotic system based on smooth function and its predefined time synchronization

In this paper, the construction of multi-wing chaotic system and predefined time synchronization are investigated. First, a new 4D chaotic system is constructed, and the existence of chaotic attractors is proved by dissipativity, boundedness, and Lyapunov exponents. Then the existence of a saddle focus of index-2 is proved by equilibrium point analysis, and a multi-winged hyperchaotic system is generated by extending the saddle focus with the constructed smooth function, which is found to be more complex and more conducive to synchronization applications by complexity analysis. Then the simulation of the circuit also proves the chaotic properties of the system in a physical sense. Finally, a new robust controller is designed using the fast terminal sliding mode algorithm to achieve predefined time synchronization between heterogeneous chaotic systems, and the numerical simulation results indicate that this synchronization method has a rapid time of convergence and achieves the predefined time effect.

Disturbance-Observer-Based Sliding-Mode Speed Control for Synchronous Reluctance Motor Drives via Generalized Super-Twisting Algorithm

In this study, a novel composite speed controller combining a sliding-mode speed controller with a disturbance observer is proposed for the vector-controlled synchronous reluctance motor (SynRM) drive system. The proposed composite speed controller employs the generalized super-twisting sliding-mode (GSTSM) algorithm to construct both the speed controller and the disturbance observer. The GSTSM speed controller is utilized to stabilize the speed tracking error dynamics in finite time, while the GSTSM disturbance observer compensates for the total disturbance in the speed tracking error dynamics, which includes external disturbances and parametric uncertainties. Under the framework of the constant direct-axis current component vector control strategy for the SynRM drive system, comparative simulation studies are conducted among the standard STSM speed controller, the GSTSM speed controller, the composite speed controller using a GSTSM speed controller and a standard STSM disturbance observer, and the proposed composite speed controller. The effectiveness and superiority of the proposed composite speed controller are verified through simulation results.

New Adaptive Super-Twisting Extended-State Observer-Based Sliding Mode Scheme with Application to FOWT Pitch Control

This paper details the transformation of the velocity or position-tracking problem of a class of uncertain systems using finite time stability control for first-order uncertain systems. A new composite extended-state observer sliding mode (ESOSM) scheme is proposed, which includes an adaptive super-twisting-like ESO and an adaptive super-twisting controller. The adaptive super-twisting controller is implemented through a barrier function-based second-order sliding mode algorithm. To further reduce control chattering and improve control performance, the adaptive super-twisting-like ESO, which employs high-order terms in the super-twisting algorithm to accelerate convergence, is designed to observe the lumped uncertainty in real time. The advantages of the proposed scheme are verified by a numerical example and application with regard to floating offshore wind turbine (FOWT) pitch control. Compared with proportional integral (PI) and adaptive super-twisting sliding mode (ASTSM) schemes, better results are obtained in velocity tracking and fatigue load suppression. For the FOWT pitch control application, the platform roll, pitch, and yaw are decreased by 3%, 2%, and 4%, respectively, compared to the PI scheme at an average turbulent wind speed of 17 m/s and turbulence intensity of 17.27%.

Backstepping and Novel Sliding Mode Trajectory Tracking Controller for Wheeled Mobile Robots

A novel variable structure controller based on sliding mode is developed for addressing the trajectory tracking challenge encountered by wheeled mobile robots. Firstly, the trajectory tracking error model under the global coordinate system is established according to the kinematic model of the wheeled mobile robot. Secondly, the novel sliding mode algorithm and backstepping method are introduced to design the motion controller of the system, respectively. Different sliding mode surfaces are formulated to guarantee rapid and stable convergence of the system’s trajectory tracking error to zero. Ultimately, comparative simulation trials validate the controller’s ability to swiftly and consistently follow the reference trajectory. In contrast to traditional controllers, this controller shows rapid convergence, minimal error, and robustness.

Optimal Observer-Based Power Imbalance Allocation for Frequency Regulation in Shipboard Microgrids

This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage.

Robust Control of Golf Swing Robot Using Backstepping Based on Fuzzy Sliding-Mode and Super-Twisting Backstepping Sliding-Mode Algorithms

This paper focuses on trajectory tracking, robustness and stabilization of a golf swing robot which has been recently developed to simulate the ultra-high-speed swing motions of a golfer. The proposed control strategies are based on the Lyapunov stability theory and include Backstepping and Sliding-Mode Control based techniques. To attenuate the chattering phenomena caused by a discontinuous switching function and improve the dynamic response of the manipulator, a fuzzy system is used in this research; a Backstepping Sliding-Mode Controller (BSMC), a Backstepping Fuzzy Sliding-Mode Controller (BFSMC) and a Super-twisting Backstepping Sliding-Mode Controller (STBSMC) are used to evaluate the proposed hybrid controller’s BFSMC performance. The Lyapunov stability theory is used to guarantee the stability of the proposed closed-loop robot technique. Numerical simulations show the effectiveness of the proposed strategy based on the fuzzy logic mechanism under different disturbances and uncertainties.

A Rotor Position Detection Method for Permanent Magnet Synchronous Motors Based on Variable Gain Discrete Sliding Mode Observer

The purpose of this paper is to study the sensor-less rotor position estimation method for permanent magnet synchronous motors, and to achieve accurate estimation of rotor position in different conditions. Firstly, the traditional super-twisting observer algorithm is analyzed, and a new discrete variable gain sliding mode observer is designed to solve the buffeting problem in discrete systems, taking the reaction force as the disturbance signal. By estimating the back potential of the observer, the buffeting problem in the sliding mode algorithm can be effectively improved as shown by the simulation results. Then, to solve the problem of phase delay in rotor position estimation, an adaptive orthogonal phase-locked loop method is used to compensate the estimation error caused by the change in motor speed and increase the estimation accuracy of rotor position. The stability of the method can be proven by Lyapunov’s second method. Simulation experiments verify the accuracy of the proposed PMSM rotor position estimation method.

Backup Pattern for traction system of FWIA electric vehicle to guarantee maneuverability and stability in presence of motor faults and failures

Faults and failures in driving motors of four-wheel-independently-actuated (FWIA) electric vehicles can lead to hazardous accidents. To address this challenge, this paper introduces a novel “Backup Pattern” by grouping the driving motors into front and rear traction subsystems. This “Backup Pattern” ensures the optimal allocation of driving torque between functional motors, providing a reliable and effective mechanism to mitigate the impact of faulty motors on the vehicle’s overall performance. Based on the torque distribution strategy, a composite controller structure is presented, utilizing the second-order sliding mode algorithm to design both the traction controllers for longitudinal and differential torques and an active-front-steering (AFS) controller for additional steering angle. The composite controller not only enhances the vehicle’s maneuverability and stability but also copes with uncertainties and disturbances in the vehicle system. Hardware-in-loop (HiL) tests validate the superior effectiveness and robustness of the designed controller, showcasing its ability to enhance FWIA electric vehicle performance compared to the conventional first-order sliding mode control-based method.

Adjacent Cross-coupling Control for Magnetic Levitation System with Ultra-local Sliding Mode Algorithm

Adjacent Cross-coupling Control for Magnetic Levitation System with Ultra-local Sliding Mode Algorithm

Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer.

Aiming at the problems of poor adjustment effect, weak anti-disturbance ability, and low robustness of the traditional sliding mode algorithm for permanent magnet synchronous motor speed sensorless, a permanent magnet synchronous motor speed observation method combining super-twisting sliding mode control algorithm and fuzzy control is proposed to accelerate the convergence speed of the system and improve the anti-disturbance ability. Fuzzy rules are used to solve the problem of obtaining the upper bound of the boundary function in the super-twisting algorithm. Moreover, the fuzzy algorithm is used to output the variable sliding mode gain instead of the fixed sliding mode coefficient to improve the system robustness and suppress the jitter. The simulation results show that the overshoot of the control system is 4%, the lag time is not more than 0.003 ms, the speed error is not more than 1%, and the response and adjustment time is not more than 0.02 s. The proposed control strategy improves the tracking accuracy and response speed of the system, suppresses the sliding mode chattering, and enhances the anti-interference ability of the system.

Improve methanol efficiency for direct methanol fuel cell system via investigation and control of optimal operating methanol concentration

This study investigates and controls the optimal operating methanol concentration for direct methanol fuel cell (DMFC) system, which effectively improves the efficiency of DMFC system. Firstly, a DMFC output characteristic model and a nonlinear stack methanol concentration model were established. Moreover, an adaptive observer was developed to reconstruct unmeasurable stack methanol concentration to estimate methanol concentration. Then, in order to achieve the minimum methanol consumption under required power, the reference methanol concentration was determined by analyzing DMFC system with its maximum energy conversion efficiency. Finally, the sliding mode algorithm was adopted to track reference optimal methanol concentration. The estimated performance of adaptive observer and non-adaptive observer for methanol concentration was compared through experimental bench data. Furthermore, the methanol consumption and energy conversion efficiency under proposed optimal methanol concentration strategy and fixed methanol concentration were compared. The comprehensive result demonstrates that the adaptive observer has better performance than non-adaptive observer in terms of estimated performance. Moreover, the proposed strategy for optimal methanol concentration was compared with fixed methanol concentration of 0.3 mol/L and 0.4 mol/L, and the fuel consumption of DMFC system was reduced by 7.9% and 30.9% respectively.