Sliding Mode Control Method Research Articles

Adaptive terminal sliding combined super twisting control design and flight tests for automatic carrier landing system

Considering the challenges posed by external disturbances on carrier-based aircraft landing control, higher demands are required for the precision and convergence of the carrier landing control system. First, this paper proposes an Adaptive Terminal Sliding Combined Super Twisting Control (ATS-STC) method to address the issues of low precision, slow convergence, and poor disturbance rejection capability resulting from external disturbances, such as carrier air-wake and deck motion. By introducing a nonlinear term into the sliding surface and employing an integral approach, the proposed ATS-STC method can ensure finite-time convergence and mitigate the chattering problem. An adaptive law is also utilized to estimate the external disturbances, thereby enhancing the anti-disturbance performance. Then, the stability and convergence time analysis of the designed controller are conducted. Based on the proposed method, an Automatic Carrier Landing System (ACLS) is developed to perform the carrier landing control task. Furthermore, a multi-dimensional validation is carried out. For the numerical simulation test, the Terminal Sliding Mode Control (TSMC) method and Proportion Integration Differentiation (PID) method are introduced as comparison, the quantitative assessment results show that the tracking error of TSMC and PID can reach 1.5 times and 2 times that of the proposed method. Finally, the Hardware-in-the-Loop (HIL) test and real flight test are conducted. All the experimental results demonstrate that the proposed control method is more effective and precise.

Robust control of charged particles position in a homogeneous isotropic turbulence using an electric field

This research investigates the position control of spherical charged particles suspended in a directly simulated homogeneous isotropic turbulence, which has the potential to improve the efficiency of the electrostatic precipitators (ESPs) in removing gaseous pollutants. To do this, the electric field used in ESPs is controlled by the sliding mode control method to steer the particles toward their desired positions. The particles are charged using the field charging method, which leads to electrical interactions between them. Employing the linked-list method reduces the computational cost related to these interaction forces. The dynamics of particles is simulated using the Maxey–Riley equation including the control force. Coupling the direct numerical simulation solver with the proposed control method and the linked-list scheme, along with solving the particle dynamics, complicates the problem from a control theory point of view. The robustness of the proposed model-free control method leads to overcoming disturbances and uncertainties in the simulation due to turbulence and repulsive electric forces. Hence, steering a large number of charged particles to places with more pollution concentration or increasing the duration of exposure of the particles to gaseous pollutants becomes possible. The findings of the present research are pertinent to improving the performance of air purification equipment.

Neural Network-Based Fixed-Time Tracking and Containment Control of Second-Order Heterogeneous Nonlinear Multiagent Systems.

This study concentrates on the fixed-time tracking consensus and containment control of second-order heterogeneous nonlinear multiagent systems (MASs) with and without measurable velocity under directed topology. By defining a time-varying scaling function and approximating the unknown nonlinear dynamics with radial basis function neural networks (RBFNNs), a novel distributed protocol for solving the fixed-time tracking consensus and containment control problems of second-order heterogeneous nonlinear MASs with full states available is proposed based on a nonsingular sliding-mode control method constructed by designing a prescribed-time convergent sliding surface. For the scenario of immeasurable velocity, a fixed-time convergent states' observer is designed to reveal the velocity information when the unknown linearity is bounded. Subsequently, a distributed fixed-time consensus protocol based on observed velocity information is proposed for the extended results. Ultimately, the acquired results are verified by three simulation examples.

End jitter suppression using FONFTSMC for rigid-flexible coupling systems of PMSpM based on NDO

A permanent magnet spherical motor (PMSpM) with three degrees of freedom rotation characteristics in the rigid rotor has broad application prospects. But the adding flexible material will inevitably produce end jitter issue in the process of the rigid-flexible coupling system (RFCs) movement. To solve the above problem, a fractional order non-singular fast terminal sliding mode control method with a disturbance observer was proposed for the rigid-flexible coupling system of a permanent magnet spherical motor (RFCs-PMSpM). Firstly, a dynamic model of RFCs-PMSpM was established by using the Hamilton principle and Euler–Bernoulli beam theory. Secondly, the influences on the end jitter were discussed from the perspectives of load mass, material parameters, and driving torque of the flexible shaft. The sensitivity analysis is carried out, and the key factors affecting the jitter are obtained. Then, a fractional order non-singular fast terminal sliding mode controller based on a nonlinear disturbance observer (NDO-FONFTSMC) is proposed. The stability of the closed-loop control system was proved by the Lyapunov method. Finally, the effectiveness of the proposed jitter suppression strategy was validated and compared with existing approaches, which also provides an important reference for the future application of RFCs-PMSpM in high-precision industry.

Enhanced three-dimensional trajectory tracking control for AUVs in variable operating conditions using FMPC-FTTSMC

In addressing the variable operating conditions encountered in complex underwater tasks, an enhanced three-dimensional tracking control method is proposed for autonomous underwater vehicle (AUV) based on fuzzy model predictive control-finite time terminal sliding mode control (FMPC-FTTSMC). Firstly, to enhance adaptability to tasks and environments, fuzzy model predictive control method is designed to achieve precise three-dimensional trajectory tracking. Additionally, a fuzzy weight allocator is employed to enable AUV to autonomously adjust optimization strategies based on real-time states such as task type, speed, and distance from the seabed, thus better coping with changing conditions and improving the universality of the control method. Secondly, a dynamic controller is designed using the finite-time terminal sliding mode control method, combined with a finite-time radial basis function neural network (FTRBFNN) disturbance observer to accurately estimate disturbances. Finally, simulation results demonstrate that the proposed method effectively reduces optimization solving time compared to traditional model predictive control, achieves trajectory tracking control under various conditions, meets preset state constraints, and demonstrates excellent tracking accuracy and robustness.

Adaptive sliding mode anti-swing control of 4-DOF tower crane based on a nonlinear disturbance observer

Tower cranes are widely applied in outdoor environments with inevitable external disturbances, which can reduce transportation efficiency and safety. To improve the transient control performance of the tower crane when transporting goods and to guarantee good robustness, this paper designs an adaptive sliding mode Anti-swing control method based on a nonlinear disturbance observer. Firstly, a 4-DOF tower crane error dynamics model considering external disturbances and air friction is established, and then, a nonlinear disturbance observer is designed to estimate the aggregate disturbance. Further, a disturbance effect indicator (DEI) is set to judge the advantages and disadvantages of the disturbance effect on the tower crane system from a new perspective. Finally, beneficial disturbance effects are organically combined with a sliding mode control method possessing an adaptive mechanism to eliminate payload swing by introducing favorable interference. Using Lyapunov stability analysis in conjunction with the LaSalle invariance principle, the closed-loop system is shown to be asymptotically stable. Simulation results show that the controller proposed in this paper achieves accurate positioning by driving the trolley and the jib, and at the same time, can keep the payload swing angle slight during the working process and eliminate the payload swing angle after accurate positioning. Moreover, it is also robust in the face of external disturbances and system parameter variations.

A novel disturbance observer–based integral sliding mode control method for frequency regulation in power systems

A novel disturbance observer–based integral sliding mode control method for frequency regulation in power systems

Adaptive Fast Integral Terminal Sliding Mode Control Strategy Based on Four-Switch Buck–Boost Converters

With the rapid development of electronic power systems, DC-DC converters are widely used, including the Four-Switch Buck–Boost (FSBB) converter, which has a unique advantage in scenarios with a wide range of voltage inputs. To improve the response speed and anti-interference capability of the FSBB converter, this paper proposes an adaptive global fast integral terminal sliding mode control method. Through an in-depth analysis of the fundamental characteristics of the FSBB converter, this study employed a global fast integral terminal sliding mode controller combined with an adaptive algorithm to significantly improve the dynamic performance and robustness of the FSBB converter. The simulation and experimental results show that the proposed method could track the reference voltage quickly and accurately in different modes, exhibiting excellent system robustness compared to conventional sliding mode control, terminal sliding mode control, and PID control methods.

Research on multi-vehicle formation control based on improved artificial potential field method

Multi-vehicle formation can perform various special tasks in unstructured environment. How to take into account the safety of vehicles in avoiding obstacles and the ability to maintain formation has a certain research value. In this paper, the four-circle model of vehicle is established first, and the circle radius is adjusted according to the state of vehicle, so as to describe the safety boundary of vehicle. The improved RRT algorithm is used for the whole route planning, and the discrete path points are used as vehicle guidance. Then the artificial potential field is constructed, and the formation coordination potential field is proposed, so that the vehicles can cooperate with other vehicles to keep the preset formation as far as possible when avoiding obstacles. Then the control quantity of the vehicle is calculated according to the force condition of the vehicle in the potential field by the double exponential sliding mode control method. Finally, the effectiveness of the method is verified by the simulation experiments of triangle formation and circular formation under different working conditions, and the formation error is reduced by about 20%.

Parameter fuzzy rectification for sliding mode control of five-phase permanent magnet synchronous motor speed control system

Introduction: Nowadays, five-phase permanent magnet synchronous motors have been widely used in the industrial and transportation fields, and the existing sliding mode control methods for speed control systems can no longer meet the requirements such as fast response and good stability.Methods: In light of the aforementioned considerations, the study initially employs mathematical modeling to elucidate the five-phase permanent magnet synchronous motor. Secondly, on the basis of proportional-integral-derivative sliding mode control, radial basis function and Takagi-Sugeno-Kang fuzzy model are introduced for parameter identification and optimization and regulation. Finally, a new neural network regulation algorithm and speed control strategy are proposed.Results and Discussion: The experimental results demonstrated that the expected parameter optimization rate of the regulation algorithm can reach 90%, and the overshooting amount under small inertia working condition is only 3%, and the adjustment time is 0.02 s. The new control algorithm can be used to control the motor speed with the lowest speed fluctuation and the fastest recovery time. In addition, when affected by the load torque, the motor speed controlled by the new strategy fluctuated the least, with a speed drop of only 1% and the fastest recovery time of 0.02 s. It exhibited the lowest control error of 3.7% and the lowest overshooting amount of 5.9%.Conclusion: In summary, the suggested approach has the potential to significantly enhance the speed control system’s control performance while maintaining strong resilience and anti-interference capabilities. The method has certain guiding significance for the practical application of five-phase permanent magnet synchronous motor speed control system.

Prescribed-time leader-follower consensus and containment control for nonlinear multi-agent systems with event-triggered control protocols

This paper discusses the prescribed-time leader-follower consensus and containment control problems for a class of nonlinear multi-agent systems with external disturbances. First, an event-triggered control protocol with sign function is proposed, which can ensure that all agents achieve consensus within a prescribed time. Second, as the sliding mode control has the advantage of good robustness to external disturbances, an improved event-triggered control protocol is designed by using the integral sliding mode control method and some sufficient conditions are derived for achieving the prescribed-time leader-follower consensus. Moreover, the prescribed-time containment control problem for multi-agent systems with multiple leaders is investigated by using the event-triggered control strategy. It is shown that Zeno behavior can be excluded in the above consensus issues by choosing parameters appropriately. Finally, several numerical examples are given to demonstrate the effectiveness and reliability of the proposed approaches.

Adaptive backstepping control using a novel dual-differentiator for multi-degree-of-freedom manipulator uncertain systems with unknown multi-disturbances

In this article, the adaptive sliding mode backstepping controller (ASMBC) using a novel dual-differentiator is proposed for multi-degree-of-freedom (MDOF) manipulator systems with uncertain states and multi-disturbances. The dual-differentiator comprises a tracking differentiator (TD) and a disturbance observer (DOB) based on the proposed TD. A novel tracking differentiator based on the inverse hyperbolic sine function and terminal attractor function (IHSTD) is introduced to reconstruct unknown states like velocity responses of the manipulator systems. Furthermore, the other differentiator, DOB based on aforementioned IHSTD (IHSTD-DOB), is involved in estimating the uncertain and stochastic multi-disturbances affecting the manipulator systems. Then, an ASMBC scheme, combining proposed dual-differentiator, is developed for achieving accurate tracking control of manipulator. Additionally, to handle the “explosion of term” issue in backstepping control, the designed IHSTD is also utilized to estimate the derivative of the virtual control law. The stability of the controller is rigorously analyzed using the Lyapunov method. Finally, numerical simulation results are presented to validate the effectiveness of the proposed scheme. Comparison experiments with the traditional DOB, the scheme except IHSTD, and the classical sliding mode control method are carried out by Simulink. The results illustrate that the present control method not only has an excellent tracking performance but also accurately estimates the unpredictable multi-disturbance and reconstructs the unknown states of the manipulator systems.

Vibration control and robustness analysis of tensegrity structures via fuzzy dynamic sliding mode control method

This study addresses the problem of mitigating vibration responses in tensegrity structures subjected to complex dynamic loading conditions. The overall purpose is to develop an effective control method to enhance the stability and performance of these structures. To achieve this, a fuzzy dynamic sliding mode control (FDSMC) method is proposed. The methodology involves deriving the state space expression of the controlled system based on the tensegrity structure's dynamic model, followed by designing a dynamic sliding mode controller using the reaching law. Fuzzy rules are incorporated to adaptively adjust the dynamic sliding mode parameters, accounting for uncertainties in controller parameters, thereby ensuring high efficiency and smooth controller output. A comparative analysis scheme, focusing on identical energy input on actuators, is utilized to evaluate the performance of various active vibration control methods. Two illustrative examples, a spatial double-layer tensegrity beam and a complex tensegrity spiral tower, are investigated in detail. The findings demonstrate that the FDSMC method significantly reduces structural dynamic responses and improves algorithm robustness compared to the conventional linear quadratic regulator (LQR) method, indicating its promising potential for relevant engineering applications.

Dynamic event-triggered dual-channel quantized sliding mode control for uncertain networked control systems under DoS attacks

This paper introduces a dynamic event-triggered sliding mode control method to address the issue of quantized stability in uncertain networked control systems (NCSs) subjected to random Denial-of-Service (DoS) attacks. Firstly, a dynamic event-triggered mechanism is utilized to compensate for the damage caused by DoS attacks while effectively reducing network bandwidth pressure. Subsequently, a sliding mode controller is designed to ensure the robustness of uncertain NCSs with external disturbances. Additionally, we construct a novel control framework that considers network delays and incorporates quantizers for state and control signals, respectively. Based on this framework, both a sufficient condition for exponential stabilization of NCSs and a co-design method for dynamic event trigger and controller are given. Finally, the effectiveness of the proposed method is verified with two generalized simulation examples.

Comprehensive Chassis Control Strategy Based on Coordination of Traction/Braking Distribution and Active Roll Control

A coordinated control of front/rear traction, four-wheel independent braking, and an active roll control system is proposed in this paper to improve overall vehicle cornering performance. The control algorithm is structured in a hierarchical form: the supervisory controller is used to calculate the desired yaw rate and roll angle based on the driver input and vehicle states; the upper-level controller is utilized to decide the target longitudinal tire forces, yaw moment, and anti-roll moment based on the sliding mode control method; and the control allocator is used to optimally map the virtual control input to the control commands of specific actuators. Co-simulations of MATLAB/Simulink and CarSim were conducted to verify the performance enhancement of the proposed controller. The results suggest that the proposed controller can effectively enhance the driving performance in limit cornering while maintaining lateral stability, and it reduces tire usage, as indicated by the index of tire dissipation energy when compared to control methods such as AWD, AWD-ESC, and ICC.

Improved Sliding Mode Control for Tracking Global Maximum Power of Triple Series Parallel Ladder Photovoltaic Array under Uneven Shadowing

Abstract This paper presents an innovative way for enhancing the performance of photovoltaic arrays under uneven shadowing conditions. The study focuses on a triple series parallel ladder configuration to exploit the benefits of increased power generation while addressing the challenges associated with uneven shadowing. The proposed methodology focuses on the implementation of improved sliding mode Control technique for the global maximum power point tracking efficiently. Sliding mode control is known for its robustness in the presence of uncertainties and disturbances, making it suitable for dynamic and complex systems such as photovoltaic arrays. This work employs a comprehensive simulation framework to comment the performance of the suggested improved sliding mode control strategy at uneven shadowing scenarios. Comparative analysis has been done to show the effectiveness of the suggested method than the traditional control strategies. The results demonstrate a remarkable enhancement in the tracking accuracy of the global maximum power point, leading to enhanced energy harvesting capabilities under challenging environmental conditions. Furthermore, the proposed approach exhibits robustness and adaptability in mitigating the effect of shading on the photovoltaic array, thereby increasing overall system efficiency. This research contributes valuable insights into the development of advanced control strategies for photovoltaic arrays, particularly in the context of triple series parallel ladder configurations operating under uneven shadowing conditions. Under short narrow shading condition, the improved sliding mode control method tracking the maximum power more compared to perturb & observe is 20.68%, incremental conductance is 68.78%, fuzzy incremental conductance is 19.8%, and constant velocity sliding mode control is 1.25%. The improved sliding mode control method has 60% less chattering than constant velocity sliding mode control under shading conditions.

Research on a Path Tracking Control Strategy for Autonomous Vehicles Based on State Parameter Identification

With the rapid development of autonomous driving technology, estimating and controlling key vehicle state parameters under complex road conditions have become critical challenges. This study combines Unscented Kalman Filtering (UKF) and Sliding Mode Control (SMC) methods to propose an integrated control model for achieving more efficient control. First, a three-degrees-of-freedom vehicle dynamics model based on the Dugoff tire model is constructed to accurately estimate key vehicle state parameters. Next, UKF is used to estimate road friction coefficients and key vehicle state parameters, and its performance is compared with Extended Kalman Filtering (EKF) under various conditions. The results show the superiority of UKF in identifying road friction coefficients. Based on SMC theory, a sliding surface is designed, and the functional relationship between state variables and control variables is derived to establish the corresponding control model. Joint simulations using Carsim and Simulink under different conditions validate the real-time performance and effectiveness of the designed UKF-SMC integrated control strategy in the presence of external disturbances and system uncertainties. Simulation results indicate that this strategy effectively enhances the overall performance and safety of autonomous vehicles, providing an accurate real-time solution capable of handling complex and variable road conditions. The proposed UKF-SMC integrated control strategy not only proves its theoretical superiority but also demonstrates promising practical applications in simulation experiments. This study provides reliable technical support for the development of autonomous driving technology under complex road conditions.

Squirrel Cage Induction Motor (SCIM) Rotor Flux Estimation and Observer Using Multivariable Sliding Mode Control (MSMC)

This paper proposes a multivariable sliding mode control (MSMC) based in rotor flux estimation and observer methods for squirrel cage induction motor (SCIM). The principle of sliding mode control (SMC) adjustment can also be applied to multivariable systems. In this case, for each control quantity, there is a control member who switches the latter quickly between a maximum value and a minimum value, thus causing the sliding mode to appear. This article will discuss sliding mode tuning of multivariable systems, highlighting issues that arise in relation to mono-variable systems studied so far. In this paper, we will establish the general relationships, where we introduce the regulators of multivariable systems. To describe the behavior in sliding mode, we will call or equivalent control vector, at the end of this article we will introduce a rotor flux observer to improve the results obtained. The work is developed with a 2-level voltage source inverter. The simulation results are carried out to verify and validate the multivariable sliding mode control method proposed based rotor flux estimation and observer scheme

An improved dynamic Prandtl–Ishlinskii hysteresis model and a PID-type adaptive sliding mode controller for piezoelectric micro-motion platform

Piezoelectric actuators are widely used in the field of micro-nano driving due to their advantages of fast frequency response, high displacement resolution, large stiffness, small size, and low heat generation. However, the hysteresis non-linearity of piezoelectric actuators severely affects their positioning accuracy during operation. Therefore, the study of hysteresis model and compensation control for piezoelectric actuators has always been a hot topic in the field of micro-nano driving. However, existing hysteresis models and control methods cannot well describe the dynamic hysteresis curve of piezoelectric actuators and track the desired trajectory. To address this issue, this paper proposes an improved dynamic Prandtl–Ishlinskii (IDPI) model and a finite-time trajectory tracking adaptive sliding mode control method based on PID-type. Firstly, this paper introduces the construction and parameter identification method of the IDPI model. Secondly, the accuracy of the IDPI model in describing hysteresis curves under different input signals is verified through experiments, and the effectiveness of the feedforward controller based on the IDPI model is validated experimentally. Then, considering the modeling uncertainty, unmodeled internal dynamics, and external environmental disturbances of the piezoelectric micro-motion platform, a finite-time trajectory tracking adaptive sliding mode controller based on PID-type is designed to suppress the non-linear characteristics of the piezoelectric micro-motion platform. Finally, the performance of the compensator is verified through simulation experiments.

Finite‐time control of DC–AC boost converter: The limit cycle approach

AbstractThis paper proposes a novel finite‐time limit cycle controller for DC to AC conversion in power boost converters. The stable limit cycle is categorized as a positive limit set. Achieving the control law, based on the concepts of set stability and finite‐time stability, is a challenging problem. To fulfill the control objective, a novel sliding manifold is suggested concerning the structure of the wanted limit cycle which facilitates conditions for the development of finite‐time stability for the limit cycle. By utilizing the sliding mode control method, a control strategy is proposed that guarantees the desired stable limit cycle is created in the phase plane of the closed‐loop system and the phase trajectories reach it in a finite time and remain on it for all future times. This ensures the finite‐time generation of the biased sinusoidal oscillations in the output of the power boost converter from a DC input source. The simulation results of a practical boost converter have validated the effectiveness and feasibility of the presented algorithm.