Variable Structure Control Method Research Articles

Depth control of an unmanned underwater vehicle based on robust inversion and sliding mode variable structure control

This paper addresses the depth control problem of an underactuated Unmanned Underwater Vehicle (UUV) subject to model uncertainties and ocean current interference. A robust inversion sliding mode variable structure control method is proposed. First, a vertical-plane UUV depth control model is established. Then, the inversion control method is combined with the sliding mode variable structure control method to devise an inversion sliding mode control algorithm. In order to further improve the control system’s robustness against external environmental interference, a robust control methodology is introduced for the design of the depth controller. Simulation results demonstrate that the designed controller effectively addresses the issues of model uncertainties and ocean current interference, thereby enhancing the UUV’s depth control accuracy.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road recognition

Aiming at the problem that the current ABS control algorithm cann’t make full use of the ground braking force to complete the braking when the complex road surface is in emergency braking, the ABS sliding mode variable structure control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor hydraulic composite is designed. Based on the fuzzy logic control method, the road adhesion coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip rate of different roads. The ABS sliding mode variable structure controller is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the sign function in the traditional sliding mode variable structure control to weaken the ’ chattering ’ phenomenon in the sliding mode variable structure control, and then the ABS controller is designed. Taking the experimental prototype vehicle driven by four-wheel hub motor as the research object, an eight-degree-of-freedom dynamic simulation model of the whole vehicle is established. Compared with the traditional PID controller, the braking time is shortened by 0.2 s and the braking distance is shortened by 2.3 m, which shows the feasibility of the designed controller. Through the simulation braking experiment of the docking road, the adaptability and real-time performance of the ABS sliding mode controller are verified, and the importance of the road adhesion coefficient identification to the ABS controller is verified.

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.

Self-Organizing Interval Type-2 Fuzzy Neural Network Compensation Control Based on Real-Time Data Information Entropy and Its Application in n-DOF Manipulator.

In order to solve the high-precision motion control problem of the n-degree-of-freedom (n-DOF) manipulator driven by large amount of real-time data, a motion control algorithm based on self-organizing interval type-2 fuzzy neural network error compensation (SOT2-FNNEC) is proposed. The proposed control framework can effectively suppress various types of interference such as base jitter, signal interference, time delay, etc., during the movement of the manipulator. The fuzzy neural network structure and self-organization method are used to realize the online self-organization of fuzzy rules based on control data. The stability of the closed-loop control systems are proved by Lyapunov stability theory. Simulations show that the algorithm is superior to a self-organizing fuzzy error compensation network and conventional sliding mode variable structure control methods in control performance.

Adaptive neural network finite-time control for nonlinear cyber-physical systems with external disturbances under malicious attacks

This paper is concerned with the finite-time tracking control problem for a class of high-order nonlinear cyber-physical systems (CPSs) with external disturbances, which are subject to malicious attacks occurring in controller-actuator (C-A) channel. Combining the variable structure (VS) control method and the artificial neural network (NN) technique, a novel adaptive neural network finite-time control strategy is developed. In particular, a Gaussian radial basis function neural network (RBFNN) is designed as an adaptive neural estimator working in an online manner to achieve the estimation and reconstruction of malicious attacks and external disturbances. Furthermore, rigorous proofs have been presented to show that the proposed control scheme can guarantee that the output tracking error converges to the origin in finite time. Finally, the proposed control scheme is applied to heavy duty vehicle system (HDVS) as a testbed, and a representative simulation is provided to demonstrate the validity and effectiveness of the proposed method.

A comparative study of FNN‐based dynamic sliding mode control for DC‐DC converters

SummaryIn this paper, a dynamic sliding‐mode variable‐structure control (VSC) is proposed for the voltage tracking control for DC‐DC boost converters, combining with a type of fuzzy neural networks (FNNs) based on different membership functions. In terms of the uncertainties from parameter perturbations and unmodeled dynamics in the DC‐DC converter, the FNNs including, respectively, Gaussian membership functions and ellipsoidal‐type membership functions are employed to approximate the uncertainties. Based on an average model for the present converter, a novel dynamic VSC that is induced by an auxiliary dynamics of the duty cycle is designed, by exploring an ideal line sliding surface based on the reference inputs and the duty cycle for the converter. Under the basis of the adaptive FNN dynamic VSC law, the tracking error system of the DC‐DC boost converter is analyzed to be boundedly stable. Eventually, the validation and the superiority of the proposed dynamic VSC method are shown in some comparative simulations.

Rollover Control of AGV Combined with Differential Drive, Active Steering, and Centroid Adjustment under Slope Driving Condition

The centroid of the Automated Guided Vehicle (AGV) equipped with the load platform is high, and it is prone to rollover when driving sideways on a slope. To solve this problem, this study proposes an anti-rollover cooperative control strategy combining differential drive, active steering, and load platform. According to the characteristics of AGV, the dynamic coupling of each subsystem is analyzed. The expected yaw stability control torque is calculated based on optimal control. The active steering controller is designed based on the model predictive control. The expected roll control torque is solved by the proposed sliding mode variable structure control method to dynamically adjust the centroid. Evaluation of the overall control system is accomplished by simulations and experiments under different load conditions of the AGV in the lateral driving condition on a slope. Compared with the PI controller, the sideslip angle decreases by 14.62% and 18.24%, and the roll angle decreases by 12.38% and 14.93% under high and low load conditions, respectively. The error between the experimental and simulation results is within 7.8%. It shows that the proposed cooperative control strategy can improve the stability of AGV under different load conditions and reduce the rollover probability when the AGV is driving sideways on a slope. This research provides a theoretical and experimental basis for active safety control of AGVs.

Trajectory Control Algorithm of Flexible Joint Manipulator Based on Random Matrix and Screw Theory

Flexible articulated manipulators are often used for the task of tracking reference trajectories in space and have attracted much attention. Aiming at the uncertainty of the robot system, based on random matrix and screw theory, this paper constructs a trajectory control model of a flexible joint manipulator. In order to reduce the steady-state tracking error, a random matrix variable structure control method is introduced into the model, and a nonlinear spinor-like random matrix function is designed to improve the traditional random matrix surface. In the simulation process, the dynamic model of the series robot is firstly obtained according to the screw and random matrix equation, and the dynamic characteristics are analyzed. Combined with dynamic surface control technology, a neural network controller is designed to solve the problem of dimensional explosion and ensure that the tracking error converges to a small neighborhood of zero. The experimental results show that by using the observation value to replace the unmeasurable state of the system, combining it with the random matrix network to identify the unknown dynamics of the system, and designing the random matrix network controller, the tracking control of the system can be realized, and the tracking error can be ensured to converge to a small neighborhood of zero. The control system has a better control effect than traditional PID, the peak time is shortened by 45.83%, the adjustment time is shortened by 46.91%, the maximum overshoot is reduced by 51.35%, and the steady-state error after filtering is only 0.049, which is reduced by 47.31%. Effective interference signal and measurement noise are suppressed, and the quantitative observation performance of the flexible joint manipulator system is improved.

Active Lane-Changing Control of Intelligent Vehicle on Curved Section of Expressway

In order to improve the intelligent vehicle lane-changing performance, an active lane-changing control algorithm is proposed considering the changes of road curvature and vehicle speed. Firstly, the vehicle dynamics model considering vehicle speed variation and lane-changing safety distance is established, and the expected lane-changing trajectory model under the curved road is designed simultaneously. Then, taking the yaw rate and longitudinal speed as the control objectives of lateral and longitudinal motions, respectively, the sliding-mode variable structure control method based on Lyapunov stability condition is adopted, and the trajectory tracking controller is designed by combining the inverted method to track the desired lane-changing trajectory. Finally, the lane-changing trajectory model and trajectory tracking controller are verified in simulation platform of CarSim/Simulink and hardware-in-the-loop (HIL) test bench. The results show that the proposed trajectory tracking control method can perform the lane-changing behavior well under different road curvatures and vehicle speeds while maintaining high trajectory tracking control accuracy.

Soft variable structure control of linear fractional-order systems with actuators saturation

In this paper, a new method of soft variable structure control for Fractional-Order System (FOS) is proposed to achieve faster response while the control signal is continuous and satisfies actuators’ constraints. Our proposed method, by describing a desired commensurate FOS, with the help of a pole placement algorithm and applying an optimization routine, in the form of a procedure, leads the system to the desired character. The routine is done by solving an optimization problem subject to a control signal constraint qua we obtain the fastest response possible in the sense of stability region. The sufficient condition of stability of the control system is developed based on the stability theory of Fractional Order (FO) linear differential equations, and attributes of the Mittag-Leffler function. Finally, an example and corresponding numerical simulations are presented to show the efficiency of the proposed method. In the proposed method, a new control strategy for the FOS is presented, a complex problem is solved in a simple way, and it can exploit the benefits of using FOS in the modeling and control of complex physical phenomena.

Design of a Fixed-Wing UAV Controller Combined Fuzzy Adaptive Method and Sliding Mode Control

To overcome the complexity of the coupled nonlinear model of a fixed-wing UAV system and the uncertainty caused by a large number of interference factors, a control algorithm combining fuzzy adaptive control and sliding mode variable structure control was proposed. The controller algorithm mainly relies on the sliding mode variable structure control method to solve the control problem of the strongly coupled complex nonlinear system. Based on sliding mode control, a fuzzy adaptive method is introduced to reduce the chattering problem of the traditional sliding mode control, and the uncertain parameters and unknown functions caused by external disturbances are approximated by this method. In this study, two types of fuzzy adaptive sliding mode controller were designed according to the different object ranges of the fuzzy adaptive algorithm. In addition, the stability of the controllers was verified using the Lyapunov method. Finally, numerical simulations are performed to demonstrate the effectiveness of the proposed controllers by comparing with the traditional sliding mode controller.

Vibration pile driving system based on Sliding Mode Control

The sliding mode variable structure synchronous control of vibration pile driving system driven by double DC motors is studied. Firstly, the model of double machine driven vibratory pile driving system is established, and the theoretical derivation of system synchronization and stability is carried out. Secondly, the sliding mode variable structure control method is used to realize the phase speed synchronous control of two motors in the vibration system. Finally, Simulink is used to verify the correctness of the theoretical derivation, and the vibration displacement of the pile driving system is simulated and analyzed. The research shows that the sliding mode variable structure control can realize the synchronous control of the double machine driven vibratory pile driving system, which provides a theoretical and practical engineering basis for the design of this type of vibratory pile driving system.

Adaptive Fault Tolerant Attitude Control of a Nano-Satellite with Three Magnetorquers and One Reaction Wheel

In this paper, a passive fault tolerant attitude control is investigated for a nano-satellite with three magnetorquers and one reaction wheel in the presence of actuator constraints, external disturbances, and partial loss of actuator effectiveness as unknown actuator faults. For this purpose, a variable structure control approach is employed due to its ability to deal with the partial loss of actuator effectiveness and adjusting the maximum amplitude of the control signal by a control gain. A modified sliding variable is designed based on angular velocity and attitude errors with an adaptive parameter coefficient. The dynamics equation of the adaptive parameter is extracted during the stability proof of the closed-loop system. Changing the value of this parameter changes the effect intensity of the quaternion errors on the sliding variable and causes the attitude errors to maintain within a limited range. Applying this parameter to the modified sliding variable makes the controller perform well even if the adaptive parameter is significantly reduced. Furthermore, directly using the adaptive parameter in the structure of control law makes the controller generate a chattering-free torque. Comparing the simulation results with the results of two variable structure control methods designed in previous articles shows that its performance in attitude tracking commands has improved. In addition, Monte Carlo simulations with random actuator faults are performed to show the robustness of the proposed controller in the presence of actuator constraints and external disturbances.

Robust control of a space robot based on an optimized adaptive variable structure control method

Space robot has been playing an increasingly important role in on-orbit service missions. Dynamic coupling exists between the space robot arm and the floating base, and an inaccurate dynamic model will deteriorate the control accuracy of space robot motion. This paper proposed an optimized adaptive variable structure control method to realize coordinate motion control of space robot base and its arm. The controller can adapt its gain to match system uncertainties and external disturbances so that the error dynamics converge to the origin following a parabola-like path which is close to the natural behavior of a second-order system. Therefore, the controller will eliminate the chattering phenomenon and reduce the settling time. Further, taking the motion error as the objective function, the gain parameter is optimized by adopting the modified Gaussian barebones differential evolution method. Numerical simulations aimed at verifying the space robot dynamic model and the effectiveness of the controller are carried out based on Simscape Multibody. The results prove that the theoretical dynamic model of the space robot is accurate. In addition, the controller is demonstrated to present reduced settling time and higher control accuracy in comparison with the boundary layer sliding mode control method.

Fixed-Time Formation Control for Second-Order Disturbed Multi-Agent Systems under Directed Graph

This paper investigates the fixed-time formation (FixF) control problem for second-order multi-agent systems (MASs), where each agent is subject to disturbance and the communication network is general directed. First, a FixF protocol is presented based on the backstepping technique, where the distributed cooperative variable structure control method is utilized to handle the bounded disturbances. Then, to remove the dependence of control gains on the global information, a practical adaptive FixF control is presented, where the MASs can achieve formation with a bounded error within fixed time. Finally, a numerical example is presented to validate the theoretical result.

基于滑模控制的大型喷雾机底盘自动调平方法研究

When a sprayer travels on a ramp or a rough road, the load exerted on each wheel changes. If an unbalanced wheel load is maintained for long periods of time, the wheels may slip, the sprayer’s manoeuvrability is affected, and a rollover accident may occur. In this study, the air suspension of a self-propelled sprayer chassis was investigated, and the potential load imbalance conditions of the sprayer suspension were analysed. A mathematical model of the inflation/deflation of the suspension was established based on air nonlinear thermodynamics and vertical dynamics theory and a ¼-scale vertical dynamics model of the sprayer chassis was developed. A control strategy to balance the sprayer’s wheel load was developed. Considering the nonlinear characteristics of the air suspension, a sliding mode variable structure control method was used to balance the wheel load. Simulation experiments were conducted under different working conditions. The simulation results showed that the sliding mode variable structure control provided good control response and precision. The proposed auto load-levelling controller was tested under different working conditions, including different roll and pitch angles and navigating a rough road; the controller successfully changed the load on each spring to ensure that the sprung mass of the suspension was equal and the wheel load was balanced. The results of this study provide reference information for auto load-levelling control of large sprayers.

Bivariate grid-connection speed control of hydraulic wind turbines

The requirement for An electrical grid-connected wind turbine is that the synchronous generator speed is stable within a required speed range for the electrical grid. In this paper, a hydraulic wind turbine (HWT) system is considered, and the working principle and working conditions of the HWT are introduced. A novel speed control method is proposed in this paper, using both a proportional flow control valve and a variable displacement motor, which are adjusted in combination to control the speed of the HWT. By establishing a state space model of the HWT and solving the nonlinear system with a feedback linearization method, a bivariate tracking controller is constructed to realize accurate speed control under fluctuating wind speed and the load disturbance conditions. The effectiveness of the control method is verified by simulation, but experimental results highlight problems with the method. The theoretical controller is simplified to reduce sensitivity to measurement noise and modeling error. The control effect has been improved to some extent, but it is limited. Based on these results, combined with the sliding mode variable structure control method and the feedback linearization method to solve the problem of measurement noise and modeling error, and the effectiveness of the control law is finally verified experimentally. It lays a theoretical foundation for the practical application of HWT.

Study on Fuzzy Neural Sliding Mode Guidance Law with Terminal Angle Constraint for Maneuvering Target

Aiming at the requirement that the guidance law should meet the minimum miss distance and the desired terminal angle at the same time, a sliding mode variable structure control method is introduced. In order to improve the fuzzy variable structure guidance law for maneuvering target attack effect, a neural network to the optimization design is carried out on the guidance law. The neural network is trained by the samples, which is under the condition of different error coefficient of angle, the coefficient of reaching law, and the coefficient of on-off item about target. Fuzzy neural sliding mode guidance law with terminal angle constraint can increase the performance of the large maneuvering target. In addition, on the basis of the traditional PC platform visual simulation system, a new guidance law simulation platform based on embedded system and virtual reality technology is formed. The platform can verify the validity of the guidance law.

Human-autonomous devices for weak signal detection method based on multimedia chaos theory

The detection of weak signals has been widely used in communication, radar and other fields. The detection of weak signals in the background of strong noise is an important research hotspot of modern information theory, and prompts people to explore and study new theories and new methods of weak signal detection. The device takes Holmes-type Duffing mapping as the research object, and uses the Lyapunov exponent as the criterion for chaos identification. The chaotic critical value of the equation is changed from chaotic state to periodic state. Whether it contains the detection algorithm of the target signal, the signal detection for the unknown frequency and the Holmes-type Duffing system is improved by the sliding mode variable structure control method in the control theory. The simulation results show that the improved chaotic Duffing system can effectively suppress the noise and detect the frequency of the weak signal through the power spectrum of the system.

Modeling and Dynamics Analysis of Marine Planktonic Ecosystem Based on Adaptive Fuzzy Variable Structure Control Approach

Yao, H., 2020. Modeling and dynamics analysis of marine planktonic ecosystem based on adaptive fuzzy variable structure control approach. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 436–441. Coconut Creek (Florida), ISSN 0749-0208.Based on the logistic model, a new nonlinear dynamic model of marine plankton ecosystem is established considering the fishing behavior and the weakening effect of pollution on plankton and the self purification ability of plankton ecosystem. The dynamic characteristics of the model are analyzed by using the adaptive fuzzy variable structure control method, and the stability conditions of the marine planktonic ecosystem are obtained. On this basis, the adaptive fuzzy variable structure control of the system is designed. Finally, the feasibility and validity of this method for the study of marine planktonic ecological model are verified by numerical simulation.