System Chattering Research Articles

Design of ABS fuzzy sliding mode control system based on pavement recognition

A fuzzy sliding mode variable structure control method based on road surface recognition was proposed to solve the problem that the Anti-lock Braking System (ABS) effect of current ABS algorithm was not ideal on complex road surface. In the road recognition module, real-time estimation of five typical road surfaces using fuzzy logic control. Dynamic calculation of optimal slip ratio for different road surfaces based on identified road conditions. Design of ABS sliding mode variable structure controller with optimal slip ratio and actual slip ratio as input. Aiming at the chattering problem of sliding mode control, a fuzzy controller is designed to reduce chattering. An 8-DOF dynamic simulation model of a four-wheel hub motor is established. The effectiveness of the controller is verified by braking simulation experiments on medium and low adhesion road. By comparing the simulation test with the traditional sliding mode controller under the condition of high adhesion road, the suppression effect of the system chattering is verified, and its excellent control performance is proved.

PMSM non-singular fast terminal sliding mode control with disturbance compensation

A non-singular fast terminal sliding mode control (NFTSMC) strategy is proposed for a permanent magnet synchronous motor control system susceptible to load disturbance. First, an NFTSM surface with fast convergence during the finite time is designed to circumvent the singular point in the TSM surface. Then, a novel reaching law (NRL) is presented to resolve the inconsistency between the system chattering and convergence rate in the traditional reaching law (TRL). Meanwhile, a non-singular fast terminal sliding mode disturbance observer (NFTSMDO) is developed to estimate the disturbance value and compensate the speed controller, further enhancing the system's anti-disturbance performance. Finally, the experiments are conducted jointly with MATLAB/Simulink and the dSPACE platform; accordingly, the experimental results indicate that when the system adds load disturbances, the PI overshoot is 38.7 rpm and the adjustment time is the longest. In addition, when the NFTSMC-TRL and NFTSMC-NRL-NFTSMDO overshoots are 37.4 and 22.1 rpm, respectively, the adjustment time is the shortest and the overall anti-disturbance is the best. Compared to SMDO, NFTSMDO improves the observer's response speed and estimation accuracy while suppressing sliding-mode chattering. It can be inferred that the control strategy proposed in this study can effectively suppress the chattering of the sliding mode control system and improve the anti-disturbance ability of the control system.

Finite-Time Disturbance Observer of Active Power Filter With Dynamic Terminal Sliding Mode Controller

This article proposes an adaptive dynamic terminal sliding mode control (ADTSMC) based on a finite-time disturbance observer (FTDO) for a single-phase active power filter (APF). Aiming at the internal parameter fluctuations and external unknown disturbances in the APF system, an FTDO is designed to compensate for the unknown uncertainties. Then, the proposed dynamic terminal sliding mode control (DTSMC) method combines the dynamic sliding mode control and the terminal sliding mode control to achieve finite-time convergence and weaken system chattering. In order to ensure the organic combination of FTDO and DTSMC, a dual-hidden-layer recurrent neural network (DHLRNN) is used to estimate the gain of sliding mode switching term adaptively so that FTDO can achieve the maximum disturbance estimation. Hardware experiments verify that the designed ADTSMC method has satisfactory robustness and harmonic compensation property under different nonlinear loads.

An optimized sliding‐mode observer control algorithm for vehicle sensor‐less PMSM

AbstractAn optimized sliding‐mode observer control algorithm for permanent magnet synchronous motor (PMSM) is proposed to solve the problems in the conventional sliding‐mode observer control algorithms (e.g., system chattering and phase delay). The proposed algorithm adopts a new piecewise function as a switching function to reduce system chattering. The low pass filter in the conventional sliding‐mode observer is substituted with a complex coefficient filter in the proposed algorithm to solve the phase delay caused by the low pass filter. Moreover, the counter emf back obtained using the filtering of the complex coefficient filter is reintroduced into the sliding‐mode observer to decrease the sliding‐mode gain coefficient and reduce chattering in the system. the simulation results suggest that the proposed algorithm outperforms the conventional sliding‐mode observer control algorithm in reducing chattering, increasing the convergence speed, reducing torque pulsation, increasing speed estimation accuracy and coping with speed and load mutation.

Adaptive Interval Type-2 Fuzzy Neural Network Sliding Mode Control of Nonlinear Systems Using Improved Extended State Observer

An adaptive sliding mode control (ASMC) based on improved linear extended state observer (LESO) is proposed for nonlinear systems with unknown and uncertain dynamics. An improved LESO is designed to estimate total disturbance of the uncertain nonlinear system, and an interval type-2 fuzzy neural network (IT2FNN) is used to optimize and approximate the observe bandwidth of LESO, and the adaptive parameter tuning is realized based on the gradient descent (GD) method. Based on the total disturbance estimated by LESO, an ASMC strategy is designed to ensure the system stability. By adapting the sliding mode gain, the observation performance of LESO compared to the total disturbance can be better utilized, and system chattering is reduced. Finally, some simulation results are given which show that the proposed control strategy has a good control effect, strong practicability, and wide versatility.

Design of single neuron super-twisting sliding mode controller for permanent magnet synchronous servo motor

Aiming at the control system of permanent magnet synchronous servo motor which is easily affected by external disturbance and parameter uncertainty, a single neuron sliding mode combining single neuron adaptive algorithm and super-twisting sliding mode (STSM) control is proposed. The STSM control is used to overcome the chattering problem in the traditional sliding mode control, and the proportional control and the STSM control are combined to enhance the robustness of the control system. In order to improve the dynamic performance of the system and enhance the anti-disturbance ability of the system, the single neuron adaptive control adopted can adjust the relevant parameters of the designed sliding mode controller online. The simulation and experimental results show that the designed improved sliding mode controller can effectively suppress the chattering of the control system, realize the fast following and no overshoot of the control system, and enhance the robustness of the system.

Handling and Stability Integrated Control of AFS and DYC for Distributed Drive Electric Vehicles Based on Risk Assessment and Prediction

How to improve the trajectory following ability and lateral stability under extreme conditions is an important research problem for distributed drive electric vehicles (DDEVs). This paper proposes a novel integrated control architecture of active front steering control (AFS) system and direct yaw moment control (DYC) system for DDEVs. First, to deal with the future instability problem caused by driver’s misoperation or delayed control, online risk assessment and prediction models, including self-regulating phase plane stability judgment and future driving state prediction of vehicles, is designed to provide decision commands for actuators in advance under extreme conditions. Then, on the basis of comprehensive consideration of system chattering, robustness and control constraint index requirements, an integrated control method based on robust sliding mode predictive control (SMPC) to put forward to solve the multi-objective and multi-constraint optimization problem for multi-subsystem integration. Finally, the simulation and experimental results show that the proposed control architecture can effectively assist drivers improve the trajectory following ability and handling stability of DDEVs, as to ensure the maneuverability and safety of emergency obstacle avoidance under extreme conditions.

A Bi-Sliding Mode PI Control of DC-Link Voltage of Three-Phase Three-Wire Shunt Active Power Filter

A novel bi-sliding mode PI control (bi-SMPIC) of the dc-link voltage of a three-phase three-wire shunt active power filter (APF) is proposed in this article. One SMPIC having an improved reaching law function in the reaching phase can make the speed of the state variables reaching the sliding surface approach zero. The other SMPIC possessing an improved reaching law function with a boundary layer in the sliding phase can render the state variables asymptotically stable at the origin of the sliding surface. Thus, the proposed bi-SMPIC can effectively reduce system chattering. Moreover, it is proven that the system has reachability and asymptotic stability. Further, a formula for determining the PI control parameters is obtained. From the formula, the proposed bi-SMPIC can have ideal control effects in both the reaching phase and the sliding phase. Finally, the high control performance of the bi-SMPIC is confirmed by both experimental and simulation results.

A novel adaptive backstepping sliding mode control for a lightweight autonomous underwater vehicle with input saturation

Accurate depth and heading control play an essential role for autonomous underwater vehicles (AUVs) in near-seabed exploration and ocean surveys. This paper proposed a novel adaptive backstepping sliding mode control (ABSMC) algorithm for a lightweight autonomous underwater helicopter (AUH) subject to highly coupled nonlinearities, unknown system parameters, disturbances uncertainties, and input saturation. This algorithm adopted a conditional adaptation algorithm to govern adaptation so that gains only adapt when necessary to improve stability. Different reaching laws were selected for heading and depth control to reduce system chattering. For thruster saturation, we proposed an anti-windup compensator for auxiliary dynamic compensation based on system states; it can make the controller output change smoothly in the event of input saturation to better meet the response characteristics of the actual physical actuator. The mathematical proofs of the proposed algorithms are presented. Simulation results are presented to illustrate the effectiveness of the proposed control method. Moreover, extensive experimental results show that the proposed algorithm has better control performance than PID and sliding mode controllers and demonstrate its adaptive capability to system state changes.

Finite-Time Disturbance Observer of Nonlinear Systems

In practical applications, for highly nonlinear systems, how to implement control tasks for dynamic systems with uncertain parameters is still a hot research issue. Aiming at the internal parameter fluctuations and external unknown disturbances in nonlinear system, this paper proposes an adaptive dynamic terminal sliding mode control (ADTSMC) based on a finite-time disturbance observer (FTDO) for nonlinear systems. A finite-time disturbance observer is designed to compensate for the unknown uncertainties and a dynamic terminal sliding mode control (DTSMC) method is developed to achieve finite time convergence and weaken system chattering. Moreover, a dual hidden layer recurrent neural network (DHLRNN) estimator is proposed to approximate the sliding mode gain, so that the switching item gain is not overestimated and optimal value is obtained. Finally, simulation experiments of an active power filter model verify the designed ADTSMC method has better steady-state and dynamic-steady compensation effects with at least 1% THD reduction in the presence of nonlinear load and disturbances compared with the simple adaptive DTSMC law.

Autonomous vehicle trajectory tracking lateral control based on the terminal sliding mode control with radial basis function neural network and fuzzy logic algorithm

Abstract. This paper will study a trajectory tracking control algorithm for electric vehicles based on a terminal sliding mode controller. First, a 3 degrees of freedom nonlinear vehicle model and a controller-oriented 2 degrees of freedom vehicle model are established. The preview time is adaptively adjusted based on the preview model. Then, the vehicle trajectory tracking controller, which uses the terminal sliding mode algorithm, is designed. The radial basis function (RBF) neural network algorithm is used to approximate the system variable parameters in the control model online. At the same time, fuzzy logic is used to control the gain parameters of the controller to reduce the chattering of the control system. Finally, the designed controller is verified by simulation. The maximum deviation of path tracking under different speeds is 0.6 m, and the target path can also be well followed under different road friction coefficients. The simulation results show that the controller designed in this paper can effectively carry out the vehicle trajectory tracking and lateral control and reduce the chattering to a certain extent.

A composite sliding-mode observer with PLL structure for a sensorless SPMSM system

To achieve high-precision speed and position control for the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes a sensorless vector control strategy based on a composite sliding-mode observer (SMO) and an improved phase-locked loop (PLL) structure. Different from the existing sensorless methods, the proposed control strategy can further improve the accuracy of observation position and speed. First, a new sliding-mode function and the equivalent control are introduced to weaken the chattering and accelerate the reaching rate. Then, a sliding-mode current observer based on an adaptive law control is designed to observe the back electromotive force (back EMF). Meanwhile, the adaptive law can ensure the stability of the system in different states and reduce the system chattering. Second, an adaptive back EMF observer is presented to accurately observe the estimated back EMF. Furthermore, the stability of the two observers is proved by employing the Lyapunov second method. Next, the variable gain PLL with the signal suppressor is used to obtain an accurate rotor position and speed. Finally, the simulations and experiments are implemented to validate the performance of the proposed control strategy, in terms of speed and position tracking as well as anti-disturbance ability.

An Integral Sliding Mode Stator Current Control for Industrial Induction Motor

An integral sliding mode control (ISMC) for stator currents of the induction motor (IM) is developed in this work. The proposed controller is developed in the d-q synchronous reference frame, by using the indirect field-oriented control (FOC) method. Robust asymptotic tracking of stator current components in the presence of model uncertainties and current coupling disturbance terms has been guaranteed by using an enhanced ISMC surface. More precisely, the stationary error of stator currents has been eliminated, and the accuracy of the regulators has been enhanced. According to the Lyapunov approach, it has been proven that the stator currents tracking happens asymptotically, and consequently, the stability of each loop has been demonstrated. Simulation and experimental results show the capability of the new controller in diminishing system chattering and increasing the robustness of the designed scheme, considering the variation of the plant parameters and current disturbance terms. It has been illustrated that compared with the conventional ISMC and PI regulators, the proposed current controllers provide smoother control actions and excellent dynamics. In addition, because of the precise control over the rotor flux, the rotor flux weakening method is employed to run the motor at a higher speed than the rated value.

PMSM sliding mode control based on novel reaching law and extended state observer

To improve the dynamic quality and control performance of the permanent magnet synchronous motor speed control system, a novel sliding mode control method with improved reaching law for PMSM was proposed, which has a shorter reaching time and small system chattering. An extended state observer (ESO) based on the hyperbolic tangent function for the sliding mode controller is designed to realize the real-time tracking of the mechanical angular velocity and load disturbance of the motor, which can weaken the influence of the internal parameter perturbation and external load disturbance. The performance of the novel sliding mode controller for PMSM was simulated based on MATLAB/Simulink. An experimental platform based on dSPACE is built. The simulation and experimental results show that this novel PMSM controller can effectively suppress the system chattering and improve the dynamic performance and robustness of the system.

An Improved Permanent Magnet Synchronous Motor Rotor Position Observer Design Based on Error Harmonic Elimination

An improved rotor position observer based on sliding mode control was proposed to eliminate estimation error and harmonic ripples for PMSM sensorless control. A multi-proportional resonant filter was designed instead of a low-pass filter to filter out the specific harmonics of back EMF. The improved filter can solve the phase delay problem caused by a low-pass filter, eliminate the rotor angle compensator, simplify the system structure, and effectively suppress the system chattering. Then, a fractional normalized phase-locked loop was adopted to calculate the speed and rotor position, further eliminating the influence of noise. Compared with the traditional sliding mode control and the improved sliding mode control, the improved sliding mode observer can effectively suppress the back EMF chattering and reduce the speed estimation error. The correctness and effectiveness of the proposed improved sliding mode observer were verified through the simulation model and experimental platform of PMSM sensorless control.

Research on an Improved Sliding Mode Observer for Speed Estimation in Permanent Magnet Synchronous Motor

Aimed at the problems of system chattering and large observation errors in the sensorless control of a permanent magnet synchronous motor (PMSM) based on a traditional sliding mode observer (SMO), a combined reaching law algorithm based on the exponential reaching law and arcsine saturation function reaching law is proposed to improve the sliding mode observer. An appropriate positive real number is taken and compared with the product of controller gain and stator current observation error to judge the system position in sliding mode motion. In the early stage of sliding mode motion, the exponential reaching law is utilized, and then, in the latter and stable stages of sliding mode motion, the arcsine saturation function reaching law is used. The stability of the observer is proved by Lyapunov theory. The simulation and experimental data show that the speed error of the sliding mode observer based on the combined reaching law is reduced by 80% compared with the traditional sliding mode observer, and the chattering problem is also improved.

Sliding Mode Control of Manipulator Based on Improved Reaching Law and Sliding Surface

Aiming at the problem of convergence speed and chattering in sliding mode variable structure control of manipulator, an improved exponential reaching law and nonlinear sliding surface are proposed, and the Lyapunov function is used to analyze its stability. According to the dynamic model of the 6-DOF UR5 manipulator and the proposed reaching law and sliding surface, the corresponding control scheme is designed. The control performance of the proposed control scheme is verified by tracking the end trajectory of the manipulator on the MATLAB and CoppeliaSim robot simulation platform. The experimental results show that the proposed control scheme can not only significantly improve the convergence speed and make the system converge quickly, but also can effectively reduce the chattering of the system. Even in the presence of disturbance signals, fast and stable tracking can be achieved while ensuring the robustness of the system, and the chattering of the robotic arm system can be weakened to a certain extent. Compared with the classical control method based on the computational torque method and the traditional sliding mode control scheme based on the exponential reaching law, the proposed scheme has certain advantages in terms of tracking accuracy, convergence speed, and reducing system chattering, and effectively improves the overall control performance of the system.

Nonsingular Fast Terminal Sliding Mode Control for Permanent Magnet Linear Synchronous Motor via High-Order Super-Twisting Observer

In this article, a nonsingular fast terminal sliding mode (NFTSM) control strategy is proposed based on the high-order super-twisting observer (HOSTO) to acquire a fast and precise tracking performance for position regulation of permanent magnet linear synchronous motor. First, the NFTSM control is introduced to achieve fast convergence of the position tracking error. However, the lumped disturbances result in incompleteness of the system state information, and the robustness of the system is guaranteed through a large switching gain for the NFTSM, which causes system chattering. Therefore, the HOSTO is utilized to estimate the state information. Then, the NFTSM controller is designed based on the estimated state variables. The system’s stability under the proposed control is demonstrated using Lyapunov stability theory. Finally, real-time experiments are carried out to illustrate the efficiency and superiority of the proposed control strategy.

Predefined-time bipartite tracking consensus for second-order multi-agent systems with cooperative and antagonistic networks

This paper addresses the predefined-time bipartite tracking problem for second-order Multi-Agent Systems (MASs) with undirected signed topologies. A group of observers, which can estimate the state tracking errors for each follower in a pre-specified time, is proposed based on the time-varying function. In order to deal with the uncertainties caused by the unknown disturbances and the unknown input signal of the leader, we propose a predefined-time distributed control protocol based on the sliding mode control method. In addition, an auxiliary dynamic sliding variable is designed to reduce system chattering. We theoretically prove that the two control protocols can drive the state trajectories of each follower to reach the corresponding sliding surface within a specified time, and finally ensure that the prescribed-time bipartite tracking consensus is achieved for the MASs. Simulations are provided to verify the proposed schemes, and the simulation results further confirm the superiority of the adaptive control protocol.

SMO-Based Sensorless Control of a Permanent Magnet Synchronous Motor

In order to reduce the chattering caused by the discontinuity of the control function in the traditional sliding mode observer (SMO), this article proposes a sliding mode observer with phase-locked loop (PLL) to estimate the speed and position of the rotor. The back electromotive force (EMF) of a permanent magnet synchronous motor (PMSM) in a static coordinate system is accurately estimated by SMO, and then, PLL is constructed to combine the observed rotor position angle and back EMF to compensate the phase lag in angle estimation so as to obtain a more accurate speed. It solves the problems of poor robustness and complex algorithms in the traditional SMO prediction algorithm. The simulation results show that the SMO with PLL can effectively reduce the system chattering and effectively improve the accuracy of rotor speed and position estimation.