Complementary Sliding Mode Control Research Articles

Self-Constructing Chebyshev Fuzzy Neural Complementary Sliding Mode Control and Its Application.

In this article, a complementary sliding mode (CSM) controller using a self-constructing Chebyshev fuzzy recurrent neural network (SCCFRNN) is proposed for harmonic suppression control of an active power filter (APF). The SCCFRNN whose structure can be automatically learned through the designed structure self-learning algorithm is introduced to approximate the unknown nonlinear term in the APF dynamic model, so as to improve modeling accuracy and reduce the burden of CSM control (CSMC). The SCCFRNN combines the advantages of a fuzzy neural network (FNN), recurrent neural network (RNN), and Chebyshev neural network (CNN), and all parameters can be adjusted according to the designed adaptive laws. Eventually, through detailed simulation, hardware experiments, and fair comparison, the feasibility and superiority of the proposed control algorithm were verified.

Fast and High Accuracy CSM Control Under Manipulator Actuator Fault Conditions

The dynamic performance metrics of manipulators are decreased when actuator faults happen. To ensure the response speed and improve the tracking accuracy under actuator fault, the complementary sliding mode (CSM) controller is designed in this article. Different from the general sliding mode control (SMC), there are two sliding surfaces in the CSM controller design process, and the mathematical complexity of the controller is simplified through the relationship of the two complementary sliding surfaces, which helps to reduce the response time. Also, the structural parameter changes and disturbance existed in the real manipulator system are also considered in this paper by introducing uncertainty item during modeling, thus the robustness of the controller is improved. In the experimental part, the control effect of the CSM proposed is compared with that of the conventional sliding mode method. Normal conditions and actuator constant deviation fault of the manipulator are studied. The results show that the CSM has superiority in control accuracy and response speed. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In recent years, the control problem of manipulators under complex conditions has attracted particular attention. The key to the design of the controller lies in its stability while keeping the tracking performance. Many complex auxiliary methods are proposed to guarantee this, but a few can achieve acceptable performance. This article proposed the complementary sliding mode controller design method, in which two sliding surfaces are used to simplify the proof in the controller design. We choose the error variables to construct the sliding surface, so the CSM could handle several actuator faults very well, which enhances the adaptive ability of the algorithm.

Controlled synchronization of a vibrating screen driven by two motors based on improved sliding mode controlling method.

With a requirement of miniaturization in modern vibrating screens, the vibration synchronization method can no longer meet the process demand, so the controlled synchronization method is introduced in the vibrating screen to achieve zero phase error state and realize the purpose of increasing the amplitude. In this article, the controlled synchronization of a vibrating screen driven by two motors based on improved sliding mode controlling method is investigated. Firstly, according to the theory of mechanical dynamics, the motion state of the vibrating screen is simplified as the electromechanical coupling dynamical model of a vibrating system driven by two inductor motors. And then the synchronization conditions and stability criterion of the vibrating system are derived and numerically analyzed. Based on a master-slave controlling strategy, the controllers of two motors are respectively designed with Super-Twisting sliding mode control (ST-SMC) and backstepping second-order complementary sliding mode control (BSOCSMC), while the uncertainty is estimated by an adaptive radial basis function neural network (ARBFNN). In addition, Lyapunov stability analysis is performed on the two controllers to prove their stability theoretically. Finally, simulation analysis is conducted based on the dynamics model in this paper.

Wavelet Fuzzy Neural Supertwisting Sliding Mode Control of an Active Power Filter

This paper presents a new intelligent sliding mode control approach to effectively achieve harmonic suppression of an active power filter (APF). An intelligent complementary terminal sliding mode controller (CTSMC) is proposed to improve the control accuracy of current loop and deal with the lumped disturbances in the system. Complementary terminal sliding mode control combines the features of complementary sliding mode control (CSMC) and terminal sliding mode control (TSMC) and does not depend on an accurate dynamic model. In addition, in order to reduce chattering, a multi-loop neural network (MLNN) whose parameter learning laws of MLNN are derived based on the Lyapunov laws are proposed to approximate the unknown nonlinear function term in the APF dynamic model, thus reducing the burden of sliding mode control. Finally, within the computing power of control board, detailed simulation and hardware experiments are carried out to demonstrate it has better harmonic suppression, steady-state and dynamic performance compared with the existing methods.

Intelligent Complementary Terminal Sliding Mode Using Multiloop Neural Network for Active Power Filter

This paper presents a new intelligent sliding mode control approach to effectively achieve harmonic suppression of an active power filter (APF). An intelligent complementary terminal sliding mode controller (CTSMC) is proposed to improve the control accuracy of current loop and deal with the lumped disturbances in the system. Complementary terminal sliding mode control combines the features of complementary sliding mode control (CSMC) and terminal sliding mode control (TSMC) and does not depend on an accurate dynamic model. In addition, in order to reduce chattering, a multi-loop neural network (MLNN) whose parameter learning laws of MLNN are derived based on the Lyapunov laws are proposed to approximate the unknown nonlinear function term in the APF dynamic model, thus reducing the burden of sliding mode control. Finally, within the computing power of control board, detailed simulation and hardware experiments are carried out to demonstrate it has better harmonic suppression, steady-state and dynamic performance compared with the existing methods.

Self-Evolving Chebyshev Radial Basis Function Neural Complementary Sliding Mode Control

A novel intelligent complementary sliding mode control (ICSMC) method is proposed for nonlinear systems with unknown uncertainties in this paper. A self-evolving Chebyshev radial basis function neural network (RBFNN) (SECRBFNN) with self-learning parameters and structure is proposed and combined with complementary sliding mode control (CSMC). CSMC not only has the advantages of the strong robustness of traditional SMC but also has certain advantages in reducing chattering and control accuracy. The SECRBFNN, which combines the advantages of the Chebyshev network (CN) and an RBFNN, is used to estimate unknown uncertainties in nonlinear systems. Meanwhile, a node self-evolution mechanism is proposed to avoid redundancy in the number of neurons. Eventually, the detailed simulation results demonstrate the feasibility and superiority of the proposed method.

Compound robust control of permanent magnet synchronous motor based on quasi‐Z source inverter

AbstractIn this study, a compound control strategy for motor side and quasi‐Z source side is proposed to improve the robustness of the quasi‐Z source permanent magnet synchronous motor drive system subjected to external disturbance. In this method, the complementary sliding mode control and sliding mode control as feedback controllers are combined with the disturbance observer technology as a feed‐forward compensator to achieve fast tracking and disturbance suppression for the PMSM drive system. Firstly, the signal models of quasi‐Z source inverters and motors are established. Secondly, by introducing state variables, the composite sliding mode controller is designed with strong robustness based on matched disturbances. Then, in order to further improve the disturbance suppression performance, a disturbance observer based on a feed‐forward compensator is designed to estimate the mismatched external disturbances in the motor drive system. Finally, the global asymptotic stability based on Lyapunov criterion is proved. The simulation and experimental results show that the proposed compound control strategy has the advantages of fast convergence, small motor speed pulsation and strong robustness to external disturbances.

Design of an NSMCR Based Controller for All-Electric Aircraft Anti-Skid Braking System

In this paper, a relative threshold event-triggered based novel complementary sliding mode control (NSMCR) algorithm of all-electric aircraft (AEA) anti-skid braking system (ABS) is proposed to guarantee the braking stability and tracking precision of reference wheel slip control. First, a model of the braking system is established in strict-feedback form. Then a virtual controller with a nonlinear control algorithm is proposed to address the problem of constraint control regarding wheel slip rate with asymptotical stability. Next, a novel approaching law-based complementary sliding mode controller is developed to keep track of braking pressure. Moreover, the robust adaptive law is designed to estimate the uncertainties of the braking systems online to alleviate the chattering problem of the braking pressure controller. Additionally, to reduce the network communication and actuator wear of AEA-ABS, a relative threshold event trigger mechanism is proposed to transmit the output of NSMC in demand. The simulation results under various algorithms regarding three types of runway indicate that the proposed algorithms can improve the performance of braking control. In addition, the hardware-in-the-loop (HIL) experimental results prove that the proposed methods are practical for real-time applications.

Novel Load Disturbance Observer-based Global Complementary Sliding Mode Control for a Precision Motion Stage Driven by PMLSM

Novel Load Disturbance Observer-based Global Complementary Sliding Mode Control for a Precision Motion Stage Driven by PMLSM

Adaptive Complementary Sliding Mode Control for Synchronous Reluctance Motor With Direct-Axis Current Control

In order to design a high-performance synchronous reluctance motor (SynRM) drive system, a novel adaptive complementary sliding mode (ACSM) speed control and an effective <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current control (EDCC) are proposed in this article. First, a classical proportional-integral based field-oriented control of the SynRM drive with a constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is introduced. However, the constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is obtained by trial and error method or satisfying the minimum excitation current of the SynRM. More importantly, the constant value of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is not suitable for the highly nonlinear and time-varying SynRM drive at the varied load torque conditions. Therefore, an ACSM speed control with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current control (ACSMSC-DCC) system is designed for the speed regulation of the SynRM. The ACSM speed control is proposed to generate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current commands, and an EDCC by using the stator flux estimator is proposed to produce the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current commands. Finally, the proposed ACSMSC-DCC system is implemented in a 32-bit floating-point digital signal processor TMS320F28075 and its effectiveness are verified by some experimental results.

Modified complementary sliding mode control with disturbance compensation for permanent magnet linear synchronous motor servo system

In this study, a modified complementary sliding mode control (MCSMC) method based on a disturbance force observer with mass identification (DFOB-MI) applicable to the permanent magnet linear synchronous motor is proposed to achieve high-performance servo control fields. MCSMC is an improvement on the complementary sliding mode control (CSMC) method, which incorporates an approach angle into the saturation function. MCSMC allows for asymptotic convergence of the position tracking errors and guarantees the global robustness of the system. In addition, compared to hybrid control strategies combining neural networks with CSMC, the MCSMC method has a simpler structure and faster response. However, in practical applications, the mass variation of the mover has a significant impact on system performance. To achieve better dynamic and static characteristics, a disturbance force observer capable of identifying the mass variation based on model reference adaptive identification theory is proposed. DFOB-MI can identify the mass of the mover and provide information on the disturbance caused by the change of the load. Thus, the compensation current is calculated to reduce the disturbance and realise compensation. The more accurate tracking performance and stronger robustness of the proposed control scheme compared to conventional approaches have been confirmed through comparative experimental studies.

Load Disturbance Observer-Based Complementary Sliding Mode Control for PMSM of the Mine Traction Electric Locomotive

For the permanent magnet synchronous motor (PMSM) control system of the mine traction electric locomotive (MTEL), the fluctuation of the load will lead to the resonance of the velocity of the MTEL and result in mechanical damage. To solve this problem, a disturbance observer-based complementary sliding mode controller (DOB-CSMC) design method is proposed in this paper. A mathematical model of PMSM is first established. Then, a disturbance observer is designed to reconstruct the load disturbances. In order to realize the static and dynamic tracking performance of the PMSM system, a saturation function-based complementary sliding mode controller is designed and the reconstructed disturbance is introduced into the controller to counteract the influence of external disturbance. Finally, the simulation and experimental results show that the DOB-CSMC method has a smaller overshoot and a shorter settling time compared with the traditional SMC method.

Complementary sliding mode control with adaptive switching gain for PMSM

Since the control system in a permanent magnet synchronous motor (PMSM) has uncertainties and disturbances, the switching gain is a key factor in effecting chattering in sliding mode control. An ad...

Complementary Sliding Mode Control via Elman Neural Network for Permanent Magnet Linear Servo System

The permanent magnet linear servo system is usually susceptible to uncertainties, such as parameter variations, external disturbances, and friction forces. To address this problem, a complementary sliding mode control (CSMC) via Elman neural network (ENN) was presented in this paper. First, the mathematical model of the permanent magnet linear synchronous motor (PMLSM) with a lumped uncertainty was established. Second, on the basis of the traditional sliding mode control (SMC), CSMC was designed by combining the integral sliding surface with the complementary sliding surface. CSMC is generally used to reduce the chattering phenomenon and, consequently, to improve the tracking performance. However, the values of the switching gain and the boundary layer thickness are difficult to select in CSMC. To deal with this problem, ENN was adopted in the proposed CSMC system to replace the switching control law. Due to its strong learning ability, ENN can estimate the value of the lumped uncertainty and adjust the parameters online, thus further improving the robustness of the system. In addition, to verify the control performance of the proposed method, a digital signal processor (DSP) was implemented as the experimental platform to control the mover of the PMLSM for the tracking of different reference trajectories. The experimental results show that the proposed control strategy not only improves tracking accuracy but also guarantees the robustness of the system.

DC-Link Voltage Regulation for Wind Power System by Complementary Sliding Mode Control

Considering the non-rigid transmission connection between the wind turbine and the generator, their angular velocity is inconsistent. A DC-link voltage control model with uncertainties is established by a two-mass inertial model. The system uncertainties increase greatly compared with the single-mass inertial model, which aggravates a DC-link voltage accuracy. To suppress the uncertainties, the complementary sliding mode control (CSMC) is proposed to regulate the DC-link voltage since it has strong robustness. The equivalent controller for the voltage loop is obtained by the conservation principle of AC and DC side power, and the compensation controller for the uncertainties is designed by the saturation function. The CSMC system is analyzed to be asymptotic stability. The simulation and experiment results show that the CSMC system can suppress the system uncertainties, and obtain a more little steady-state error of the DC-link voltage, compared with PI control system.

Approach Angle-Based Saturation Function of Modified Complementary Sliding Mode Control for PMLSM

In this paper, an approach angle-based saturation function of modified complementary sliding mode control (MCMSC) method was proposed to overcome the influence of uncertainties such as parameter variations and external disturbances on permanent magnet linear synchronous motor (PMLSM) servo system. On the foundation of the mathematical model considering uncertainties of PMLSM and the theory of sliding mode control (SMC), complementary sliding mode control (CSMC) method was designed by combining the integral sliding surface with the complementary sliding surface. By using the continuous saturation function, CSMC can efficiently eliminate the system chattering phenomenon caused by the discontinuous function in SMC and further improve the position tracking accuracy. However, the saturation function makes the boundary layer in CSMC constant, so the asymptotic stability of the system cannot be guaranteed. Hence, an approach angle-based saturation function of MCSMC was designed to realize the dynamic change of the boundary layer, which can diminish the boundary layer with the change of state trajectory until it converges to the sliding surface, thereby further improving the robustness of the system. Additionally, the hybrid SMC methods, such as fuzzy-SMC and neural network-SMC (NN-SMC), are avoided. A precise test platform based on digital signal processor (DSP) was implemented, and experimental results are shown to demonstrate the effectiveness and correctness of the proposed method.

Modified adaptive complementary sliding mode control for the longitudinal motion stabilization of the fully-submerged hydrofoil craft

This paper presents a Modified Adaptive Complementary Sliding Mode Control (MACSMC) system for the longitudinal motion control of the Fully-Submerged Hydrofoil Craft (FSHC) in the presence of time varying disturbance and uncertain perturbations. The nonlinear disturbance observer is designed with less conservatism that only boundedness of the derivative of the disturbance is required. Then, a complementary sliding mode control system combined with adaptive law is designed to reduce the bound of stabilization error with fast convergence. In particularly, the modified complementary sliding mode surface which contains the estimation of the disturbance can reduce the switching gain and retain the normal performance of the system. Moreover, a hyperbolic tangent function contained in the control law is utilized to attenuate the chattering of the actuator. The global asymptotic stability of the closed-loop system is demonstrated utilizing the Lyapunov stability theory. Ultimately, the simulation results show the effectiveness of the proposed approach.

Hybrid-loop servo control system of double toggle mechanical press for flexible forming process based on sliding mode control and neural network techniques

A hybrid-loop servo control system based on sliding-mode control and neural network control is proposed in this article to realize flexible forming process on a double toggle mechanical press. First, kinematics and dynamic analysis of the drive system are conducted to derive the control objective behavior. Then, the structure of the hybrid-loop system is introduced; sliding-mode control is applied to compensate the punch position errors. In the inner loop of the servo motor, complementary sliding-mode control is used to track the motor rotation angle, and a radial basis function neural network estimator is applied to eliminate the considerable load disturbances in the stamping stage. Finally, experimental hardware is constructed and a compound blanking and drawing process is carried out to validate the proposed servo control system in practice. With different materials and drawing depth, high tracking accuracy and robustness are exhibited to realize favorable forming performance.

Precision Sinusoidal Local Scan for Large-Range Atomic Force Microscopy With Auxiliary Optical Microscopy

Atomic force microscopy (AFM) is a powerful measurement instrument which can build 3-D topography image of conductive and nonconductive samples at nanoscale resolution. However, due to the scan method of conventional AFM, the induced mechanical resonance of the scanner and the scan in area of uninterest would strictly limit the scan speed. In this study, we improve these problems with our designed AFM system from three aspects. First, the sinusoidal trajectory is applied to lateral scanning of the AFM rather than the traditional raster trajectory, so the scan rate can be increased without inducing vibration of the lateral scanner. Second, with this promising scan trajectory, the internal model principle-based neural network complementary sliding-mode controller and adaptive complementary sliding-mode controller are designed to achieve high precision scanning and to cope with the system parameter uncertainties and external disturbance. Finally, with the aid of an auxiliary optical microscopy and the scanned information during the scanning process, scan path planning can be adopted to focus the scanning on samples such that the total scan time is further shortened. Extensive experimental results are provided to show the appealing performance of the proposed method.

Intelligent complementary sliding-mode control with dead-zone parameter modification

This paper proposes an intelligent complementary sliding-mode control (ICSMC) system which is composed of a computed controller and a robust controller. The computed controller includes a neural dynamics estimator and the robust compensator is designed to prove a finite L2-gain property. The neural dynamics estimator uses a recurrent neural fuzzy inference network (RNFIN) to approximate the unknown system term in the sense of the Lyapunov function. In traditional neural network learning process, an over-trained neural network would force the parameters to drift and the system may become unstable eventually. To resolve this problem, a dead-zone parameter modification is proposed for the parameter tuning process to stop when tracking performance index is smaller than performance threshold. To investigate the capabilities of the proposed ICSMC approach, the ICSMC system is applied to a one-link robotic manipulator and a DC motor driver. The simulation and experimental results show that favorable control performance can be achieved in the sense of the L2-gain robust control approach by the proposed ICSMC scheme.