Sliding Mode Control Scheme Research Articles

An adaptive integral sliding mode control strategy for medical linear accelerator vacuum system

Medical linear accelerators (MLAs) are critical components for radiation therapy, providing a state-of-the-art treatment platform for cancer therapy. The vacuum system is one of the most important MLA subsystems and its stable operation is necessary to generate high-quality beams. For vacuum system pressure control, traditional proportional-integral-derivative (PID) strategies have disadvantages such as inaccurate and imprecise control response due to its simple calculation. This paper presents an innovative adaptive integral sliding mode control (AISMC) strategy aimed at enhancing the response time, precision of control, and capability to reduce disturbances within the MLA vacuum system. In addition, a nonlinear MLA vacuum system mathematical model is established based on mechanism method. Stability of the developed vacuum control system is validated using Lyapunov stability theory. Simulation results illustrate that the proposed AISMC strategy has better response speed and accuracy than traditional PID-based systems, achieving better pressure tracking performance than traditional sliding mode control strategy with PID control. Most important for the proposed controller, system chattering is effectively mitigated.

Robust design of a two-stage composite sliding mode controller for enhanced performance in large-scale systems

This paper introduces an innovative composite sliding mode control strategy tailored for large-scale system, specifically tackling the intricate task of formulating a sliding mode control law for singularly perturbed systems. This paper delineates the development of a composite controller by dissecting it into subsystem controllers for both ‘slow’ and ‘fast’ subsystems, exploring its effectiveness in managing matched bounded external disturbances within the context of large-scale system. While sliding mode control proves to be a robust solution for handling uncertainty and disturbances, its inherent complexity and discontinuous characteristics pose significant challenges in crafting designs suitable for singularly perturbed systems.

Trajectory tracking control of the pushing ore truck manipulator based on adaptive sliding mode control with interference observer

An improved sliding mode controller was designed to solve the problem of low tracking accuracy caused by various disturbances and errors existing in the hydraulic-driven manipulator for pushing ore truck. The state space equation of the hydraulic system of the pushing ore truck manipulator was modeled and derived, and a sliding mode function was designed. For interference signals, use interference observers for observation. For the unobserved parts, adaptive laws are used for compensation to reduce system chattering, and system’s stability is verified using Lyapunov functions. The simulation results show that, compared with the traditional Sliding mode control and adaptive sliding mode control, the adaptive sliding mode control strategy based on interference observer proposed in this paper can effectively weaken the system chattering, reduce the uncertainty caused by external interference and modeling error, and improve the trajectory tracking accuracy of the pushing ore truck manipulator.

A model-based sliding mode control with intelligent distribution for a proportional valve driven by digital valve arrays

Parallel-connected digital valve arrays are commonly utilized in the pilot stage of the proportional directional valve to enhance dynamic performance and reliability. However, when the digital valve array is driven by a digital signal, it is difficult to optimally assign the signal pulses to each valve. If the assignment is not well executed, it can significantly reduce the switching uniformity of the digital valves or lead to performance degradation of the system. In this paper, a model-based sliding mode control strategy based on the intelligent distribution of control law is proposed and successfully applied to a proportional valve driven by digital valve arrays. The intelligent distribution strategy encompasses a logic distribution algorithm and a circular sliding distribution algorithm that automatically assigns control laws to different valves based on the rolling of the PWM signal cycle. Experimental results confirm that the proposed strategy not only simultaneously reduces the total number of valve switches and enhances the switching uniformity among the valves, but also adapts to the variation in the number of valves. The proposed strategy is not limited to the application of digital valve arrays, it is also applicable in other fields of multi-actuators driven by digital signals, and can simultaneously improve the control accuracy, lifetime, and maintenance friendliness.

Identification and Control of Flexible Joint Robots Based on a Composite-Learning Optimal Bounded Ellipsoid Algorithm and Prescribe Performance Control Technique

This paper presents an indirect adaptive neural network (NN) control algorithm tailored for flexible joint robots (FJRs), aimed at achieving desired transient and steady-state performance. To simplify the controller design process, the original higher-order system is decomposed into two lower-order subsystems using the singular perturbation technique (SPT). NNs are then employed to reconstruct the aggregated uncertainties. An adaptive prescribed performance control (PPC) strategy and a continuous terminal sliding mode control strategy are introduced for the reduced slow subsystem and fast subsystem, respectively, to guarantee a specified convergence speed and steady-state accuracy for the closed-loop system. Additionally, a composite-learning optimal bounded ellipsoid algorithm (OBE)-based identification scheme is proposed to update the NN weights, where the tracking errors of the reduced slow and fast subsystems are integrated into the learning algorithm to enhance the identification and tracking performance. The stability of the closed-loop system is rigorously established using the Lyapunov approach. Simulations demonstrate the effectiveness of the proposed identification and control schemes.

Research on the motor control system of electric driven air suction seed dispenser

In order to improve the characteristics of the motor control system of the electric drive type pneumatic PLANTING device, some pneumatic PLANTING devices made by American PrecisionPlanting Company were used to design the motor control system and the drive gear of the motor. On the basis of analyzing the dynamics of brushless DC motor, hysteresis control and sliding mode control strategy are used to control the speed of the motor, and the control system simulation model of the drive motor is established on MATLAB/Simulink software. The simulation results show that the waveform is consistent with the theoretical analysis. When the load is suddenly applied, the speed can respond quickly and become stable quickly. The torque response can follow the change of current well, and the system can run smoothly.

Trajectory tracking of a wheeled mobile robot based on the predefined‐time sliding mode control scheme

AbstractIn this paper, a double‐loop control method is proposed to improve the trajectory tracking performance of a wheeled mobile robot (WMR) with slippage properties and external disturbances. Considering the strong robustness and the ability to enable the system to converge in a short time, the predefined‐time sliding mode control (PTSMC) strategy is applied to the design of a double‐loop controller. Furthermore, a nonlinear disturbance observer (NDO) is adopted to comply with the feedforward compensation of the external disturbances. In turn, the controller only needs to deal with the internal disturbance of the system under the premise of using the NDO, thereby reducing the burden of the sliding mode controller. Based on Lyapunov methods, the stability of the double‐loop controller and the NDO is analyzed. Finally, the feasibility of the double‐loop control strategy is proven by simulations of the WMR operating along circular, sin‐shaped, and eight‐shaped roads.

Performance improvement of predictive voltage control for interlinking converters of integrated microgrid

Voltage quality in Renewable Energy System may be harmed by varying power demand and fluctuating energy source outputs. The model predictive voltage (MPV) control approach is suggested in this study. The proposed control strategy enables appropriate power interactions between the AC and DC subgrids while sharing power fluctuations in a coordinated way. Both the AC and DC subgrids support each other in accordance with their normalized relative changes in AC frequency and DC voltage, respectively. A typical photovoltaic (PV) wind-battery-based hybrid AC/DC microgrid is modelled and investigated, and the usefulness of the proposed scheme is validated under the renewable energy variations and load perturbations. MATLAB/Simulink has validated the efficacy of the suggested strategy. A set of comparative tests was conducted between conventional Proportional-Integral (PI) control, Sliding Mode Control (SMC) strategies, and a novel Model Predictive Voltage Control (MPV) approach under diverse conditions. The aim was to comprehensively assess the advantages of the proposed MPV method. Results demonstrate that, in contrast to traditional PI and SMC control strategies, the MPV technique exhibits distinct benefits in terms of superior control performance and achieves exceptionally low Total Harmonic Distortion (THD) values. Ultimately, the proposed solution not only raises the performance standard but also ensures the stable operation of the Renewable Energy System (RES).

Asymptotic consensus tracking control of robotic manipulators with disturbance and dead-zone via adaptive sliding mode control

This article aims at solving the difficulties of robotic manipulator systems with unknown disturbance and dead-zone in consensus trajectory tracking. For the purpose of accelerating the tracking process of leader and follower manipulators, a novel sliding mode control strategy is proposed. For compensating the influence of unknown lumped disturbance and control dead-zone, a novel adaptive law is designed for the construction of controller. With the help of adaptive sliding mode controller, based on the Lyapunov stability theory, the over-estimation is alleviated and the tracking errors converge to zero asymptotically. The simulations demonstrate the validity of the proposed strategy for consensus asymptotic trajectory tracking.

Adaptive neural network-based practical predefined-time nonsingular terminal sliding mode control for upper limb rehabilitation robots

This article investigates the predefined time trajectory tracking control problem of upper limb rehabilitation robots in the presence of the model uncertainty and external disturbances. An adaptive neural network-based practical predefined-time fast nonsingular terminal sliding-mode control (PPT-FNTSMC) strategy is proposed, in which a novel sliding mode surface is constructed to achieve predefined-time convergence and avoid the singularity problem as well. Additionally, a neural network is employed to approximate the lumped disturbances, and the estimated values are utilized in the controller for compensation, thereby reducing the required switching gain and mitigating chattering phenomenon. A rigorous theoretical analysis is provided to illustrate that the tracking errors can converge to a vicinity of the origin in a predefined time. Finally, simulations on a two-joint single-arm robot and a 5-DOF upper-limb exoskeleton are conducted and compared with an existing control method to demonstrate the effectiveness and superiority of the proposed control strategy.

Performance-optimisation-based repetitive trajectory tracking control for autonomous farming vehicle

The high precision trajectory tracking for the autonomous farming vehicle (AFV) is closely related to work quality and crop yield. Farmland operations are usually repetitive tillages, and the farmland soil is relatively soft, slippery, and uneven, which can easily lead to uncertain problems such as slippage, parameter perturbation, and external disturbance. This paper proposes a finite-time repetitive trajectory tracking control strategy integrated with particle swarm optimisation (PSO) and equivalent input disturbance (EID) for the AFV to achieve performance optimisation. The repetitive control framework with finite-time convergence technique can effectively realise the iterative convergence performance of the repetitive trajectory tracking. The PSO algorithm is integrated into determining the control gains to optimise the dynamic and steady-state performances of the trajectory tracking control system. The EID method enhances the tracking precision and robustness to internal and external disturbances. Under MATLAB/Simulink and CarSim co-simulation environment, the effectiveness and advantages of the designed control strategy are illustrated by comparing it with the traditional repetitive control, the EID-based PI control, the active-disturbance-rejection-control-based nonsingular terminal sliding mode control, as well as the sliding-mode-observer-based integral sliding mode control strategies for a farming vehicle.

Sub-synchronous oscillation suppression strategy for virtual synchronous generators based on dual-loop sliding mode control

The virtual synchronous generator (VSG) has synchronous voltage source characteristics that can effectively improve the stability of high-penetration renewable energy power systems. However, the output impedance of VSG using traditional voltage–current inner-loop control has lower damping in the sub-synchronous frequency range. Therefore, when the VSG is connected to a grid with series compensation for long-distance transmission of renewable energy, in the sub-synchronous frequency range, there is a potential interaction between the inductive output impedance of VSG and the capacitive impedance of the line, leading to the occurrence of sub-synchronous resonance (SSR). To address this challenge, the stability of a series-compensated grid-connected system employing voltage–current inner-loop control was analyzed using VSG sequence impedance modeling. A dual-loop sliding mode control strategy (SMC-DL) was proposed to suppress SSR occurrence. This control strategy can significantly enhance the damping of VSG’s output impedance in the sub-synchronous frequency range, and effectively suppress SSR. Compared to traditional control strategies, this control strategy does not require the addition of virtual impedance, avoids voltage offset issues, adapts to grids with different series compensation levels. Finally, the effectiveness of this approach was verified through simulations and experiments.

Adaptive Super-Twisting Sliding Mode Control for Robot Manipulators with Input Saturation.

The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC is developed for robot manipulators, which not only achieves strong robustness but also ensures finite-time convergence. The boundary of lumped uncertainties cannot be easily obtained. A modified adaptive law is developed such that the boundaries of time-varying disturbance and its derivative are not required. Considering input saturation in practical cases, an ASTSMC with saturation compensation is proposed to reduce the effect of input saturation on tracking performances of robot manipulators. The finite-time convergence of the proposed scheme is analyzed. Through comparative simulations against two other sliding mode control schemes, the proposed method has been validated to possess strong adaptability, effectively adjusting control gains; simultaneously, it demonstrates robustness against disturbances and uncertainties.

Trajectory Tracking Control of Mobile Manipulator Based on Improved Sliding Mode Control Algorithm

Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior.

Active and passive heave compensation system based on feedback linearization sliding mode variable structure control

This study presents a novel electric-hydraulic servo system with an active–passive lift compensation feature designed for a lifting crane used in offshore operations. Additionally, the study explores the control methodology of this system. Firstly, the principle of the combined active–passive lift-compensated system is explained, and the mathematical model of the response is established. To eliminate the strong nonlinearities inherent and mismatched term, the method of exact input-state linearization is employed. For observing the uncertain disturbance terms in the model, a new type of expanded state sliding mode observer(ESSMO) is designed. Subsequently, a control strategy of sliding mode with variable structure is designed using the method of hyperbolic convergence law. The stability of the controller is proved based on Lyapunov’s stability theorem. Finally, the control method is simulated and analyzed under different working conditions and compared with traditional PID control and sliding mode control strategies directly designed by the nonlinear model. The simulation results demonstrate that the feedback linearized hyperbolic convergence law sliding mode control strategy not only reduces dependence on exact parameters of the original system but also exhibits strong robustness and suppression of model nonlinearities and parameter uncertainty.

Passive Super-Twisting Second-Order Sliding Mode Control Strategy for Input Stage of MMC-PET

When the operating state of the power system changes, a modular multilevel converter power electronic transformer (MMC-PET) based on modular multilevel converters cannot perform efficient energy transfer and power conversion under conventional control strategies. To address the above problems, this paper proposes a passive, second-order super-helical sliding mode control strategy for MMC-PET by combining passive control and second-order super-helical sliding mode control with a stronger anti-interference capability. First, a Euler–Lagrange model based on positive and negative sequence separation is established according to the mathematical model of the MMC; second, the model of the system is passively analyzed, and a passive controller is designed according to its passivity, and the passive controller is further optimized by using the super-helical second-order sliding mode control, which improves the overall robustness and interference immunity; finally, the effectiveness and superiority of the super-twisting second-order sliding mode passive control strategy is demonstrated by verifying it through the construction of the MMC-PET simulation model and testing it under various non-ideal working conditions.

Fast finite-time time-varying formation tracking control of multi-agent systems with external disturbance and region constraints

In this paper, fast finite-time time-varying formation tracking control for second-order multi-agent systems with external disturbance and region constraints is investigated. The ubiquitous control input response delay is considered. A predictor-based state transformation is employed to obtain the ideal equivalent systems without control input response delay. Considering the difficulty of measuring external disturbance, a fast finite-time observer with the sliding mode technique is proposed to estimate the disturbance, which positively compensates the system. By adopting the sliding mode control strategy, a novel fast finite-time formation tracking controller is proposed. Sufficient conditions for the formation tracking control with region constraints are obtained. Numerical simulations are employed to validate the feasibility and effectiveness of the theoretical results.

Dynamic-matching adaptive sliding mode control for hypersonic vehicles

Hypersonic vehicles exhibit significantly varied dynamic characteristics across different flight regimes. These characteristics, such as model uncertainties and actuator saturation levels, have strong time-varying properties, necessitating a control strategy capable of adaptively matching robustness and responsiveness to such variability. This paper introduces an adaptive sliding mode control strategy tailored for hypersonic vehicles, which dynamically aligns controller performance with the vehicle's varying dynamic properties. Initially, a quantitative model to characterize the dynamic uncertainty of the hypersonic vehicle is constructed, and an online adaptive method to estimate the bounds of model uncertainty is proposed. This method enables real-time adaptation of controller robustness. Furthermore, the study employs artificial potential functions for online estimating control saturation and actuation rates. It adaptively modulates the control response rate coefficients based on these estimations, effectively mitigating saturation while ensuring the rapid convergence of tracking errors. Additionally, the stability of the system is scrutinized through Lyapunov theory, which verifies that the tracking error remains uniformly ultimately bounded. The simulation results corroborate the efficacy of the proposed approach, illustrating advancements in robustness, responsiveness, chattering suppression, and saturation prevention.

Differential graphical games of multiagent systems with nonzero leader's control input and external disturbances

AbstractIn this article, we investigate the problem of differential graphical games for multiagent systems (MASs) with external disturbances. In particular, the system considered in this article allows the leader to have an unknown bounded control input, and the communication topology between agents is allowed to be a weakly restricted structure with only containing a directed spanning tree. We propose a novel dynamic sliding mode control strategy to dispose the presence of leader's nonzero control input and external disturbances. Furthermore, a nominal controller based on the worst‐case control strategies of neighbors is designed to provide a distributed solution for differential graphics games of MASs. Finally, our algorithms are applied to solve multiple unmanned surface vessels games. Simulation studies are provided to test the effectiveness of the proposed algorithms.

Suppression of Torque Ripple in Switched Reluctance Motors Which is Based on Synchronization Technology

The double salient pole structure of Switched Reluctance Motor (SRM) makes its electromagnetic field exist nonlinear saturation characteristics, resulting in its large torque pulsation in operation, so it is difficult to achieve speed regulation smoothly by traditional control methods. In view of this problem, a sliding mode control strategy which is based on synchronous transmission technology was proposed.Firstly, the basic structure of switched reluctance motor was analyzed, and the mathematical model of mechanical motion of switched reluctance motor was established. Secondly, an improved sliding mode controller which is based on synchronous signal transmission technology was designed by analyzing the reason of large torque ripple of switched reluctance motor, and the stability of the system was proved. Finally, simulation is used to verify the effectiveness of the control strategy.Compared with the traditional PID (Proportional Integral Differential) control algorithm, this control technology not only suppresses the SRM torque ripple effectively , but also makes the sliding mode controller output the precise target electromagnetic torque quickly by increasing the control variables. The results of research indicate that this design can not only restrain the torque ripple effectively, but also adjust the convergence speed and overshoot of the controller by adjusting the design parameters.