Sliding Mode Control Approach Research Articles

State of Change-Related Hybrid Energy Storage System Integration in Fuzzy Sliding Mode Load Frequency Control Power System with Electric Vehicles

In the context of the integration of hybrid energy storage systems (HESSs) and electric vehicles (EVs), this paper investigates the load frequency control (LFC) issue of the power system. Weighting coefficients are set for the generators, HESSs and EVs, respectively, to show their different abilities to regulate the power system. A fuzzy logic-based sliding mode control approach is designed to ensure the stable performance of the LFC power system integrated with HESSs and EVs. The improvement of the proposed method is the application of the linear matrix inequality (LMI) toolbox in fuzzy controller design, which solves the limitations and uncertainties caused by trial-error or experience in common fuzzy controllers. There is no general form for the membership function of the fuzzy control. This paper presents a design approach for the membership function based on the calculation results of LMI. Simulations are tested on an IEEE 39-bus system integrated with HESSs and EVs. The simulation results prove that the proposed method reduces the time required for the power system frequency to reach stability by approximately 8.8%, demonstrating the superiority and usability of the proposed approach.

A novel fuzzy assisted sliding mode control approach for frequency regulation of wind-supported autonomous microgrid

Autonomous microgrids (ATMG), with green power sources, like solar and wind, require an efficient control scheme to secure frequency stability. The weather and locationally dependent behavior of the green power sources impact the system frequency imperfectly. This paper develops an intelligent, i.e., fuzzy logic-based sliding mode control (F-SMC) utilizing a proportional-integral-derivative (PID) type sliding surface to regulate the frequency of a wind-diesel generator-based ATMG system. A dynamic structure of the wind generator is designed to participate in the frequency support of the considered plant. The mastery of the F-SMC is analyzed over the conventional SMC (C-SMC) under load perturbation. This study used the artificial gorilla troop optimization (GTO) technique to tune the F-SMC parameters. The effectiveness of the GTO-tuned F-SMC frequency regulation (FR) scheme is compared with well-established particle swarm optimization (PSO) and grey wolf optimization (GWO) approaches under various scenarios such as load perturbations, governor dead band (GDB), generation rate constraint (GRC), higher/lower dimensions of ATMG, and wind speed variations. Finally, the proposed GTO-based F-SMC approach has been validated upon a standard IEEE-14 bus system and compared with recent techniques.

Sliding Mode Control Approach for Vision-Based High-Precision Unmanned Aerial Vehicle Landing System Under Disturbances

Unmanned aerial vehicles (UAVs) face significant challenges when landing on moving targets due to disturbances, such as wind, that affect landing precision. This study develops a system that leverages global navigation satellite system (GNSS) signals and UAV visual data to enable real-time precision landings, and incorporates a sliding mode controller (SMC) to mitigate external disturbances throughout the landing process. To this end, a reference-model-based SMC is proposed, which defines reference values for each state to enhance the steadiness and safety of the velocity control system, thereby improving velocity state tracking and accuracy. The stability of the proposed controller is demonstrated using the Lyapunov method and comparing its performance against other controllers, including backstepping, linear-quadratic regulator (LQR), and proportional–integral–derivative (PID). The experimental results reveal a 75% reduction in maximum velocity tracking error and an 80% reduction in maximum landing error with the proposed controller. Finally, extensive real-flight tests confirm the stability and feasibility of the system.

Theory and experiment for autonomous quadrotor flight via bounded robust finite-time homogeneous sliding mode control: A roadmap to search and rescue

This paper introduces a new saturated robust control technique for quadrotor aircraft modeled by second-order Ordinary Differential Equations (ODEs), considering disturbances in the control channel (matched disturbances). The control design employs a Sliding Mode Control (SMC) approach, featuring in: (i) a novel saturated homogeneous sliding manifold, (ii) a novel tracking controller, namely, Bounded Robust Finite-Time Homogeneous Sliding Mode Control (BRFTHSMC). An Improved Fixed-time Convergent Extended State Observer (IFCESO) is incorporated into the control scheme to handle disturbances. Together the BRFTHSMC and the IFCESO establish a reliable Active Disturbance Rejection Control (ADRC) framework. The latter ensures finite-time convergence of the errors quantities to the origin along with effective disturbance rejection. Rigorous stability analysis is conducted based on Lyapunov theory. Beside control design, another distinguishing theoretical outcome of this paper in the form of Corollary is the extension of the present results to integrator-type systems (higher-order systems). The study is substantiated through MATLAB®/Simulink simulations and Robot Operating System (ROS)/Gazebo implementation, validating the theoretical foundation. Extensive experimental tests on real hardware, including attitude and Cartesian trajectory tracking under various disturbances, further affirm the theoretical findings. The synthesized control system surpasses alternative methods in terms of control signal’s boundedness, finite-time tracking stability, transient response performance, and steady-state precision. Notably, the control input circumvents singularity challenges observed in conventional SMC approaches. In addition to trajectory tracking experiments, the controller’s effectiveness is demonstrated in real-world search and rescue scenarios. Therefore, a Deep Neural Network (DNN) algorithm, based on a MS COCO-pretrained Single Shot Detector (SSD-Mobilenet-v2), is employed for a person detection mission in an unknown search area.

Anti-Sway Adaptive Fast Terminal Sliding Mode Control Based on the Finite-Time State Observer for the Overhead Crane System

This work proposes an adaptive rapid terminal SMC (sliding mode control) approach based on the FFTSO (fast finite-time state observer) for overhead crane trajectory tracking and anti-swing control in the presence of external disturbances and parameter uncertainty. First, the system state observation under the constraint of unknown system parameters is accomplished by designing the FFTSO based on finite-time theory. Next, a parameter-adaptive fast terminal SMC is created for an overhead crane based on the model transformation. This technique can still monitor the intended trajectory and reduce payload swing even in cases when the payload mass and wire rope length are uncertain. Next, the Lyapunov theorem is used to demonstrate the stability of the overhead crane system’s positioning and anti-swing angle control mechanism. Lastly, the platform experiments confirm that the suggested closed-loop system control technique is successful.

Intelligent Driving Vehicle Trajectory Tracking Control Based on an Improved Fractional‐Order Super‐Twisting Sliding Mode Control Strategy

ABSTRACTAiming at resolving trajectory tracking control challenges during high‐speed lane changes in intelligent driving vehicles, an innovative fractional‐order sliding mode control approach is introduced in the present study. The control strategy comprises upper and lower‐level controls. First, the upper‐level control designs the vehicle trajectory tracking controller, integrating a non‐singular terminal sliding mode (NTSM) surface with a fractional‐order fast super‐twisted sliding mode control (FOF‐STSMC) algorithm. The NTSM surface properties ensure rapid convergence of the system tracking error to zero within a finite time, while the fractional‐order control extends the control system's regulation range and enhances algorithm flexibility. Additionally, the integration with the super‐twisting algorithm effectively mitigates oscillation issues in the control input, achieving a smooth input. Second, the lower‐level control aims to enhance vehicle driving stability. Utilizing the reference yaw rate, and sideslip angle and accounting for tire force saturation, a fractional‐order sliding mode control (FOSMC) algorithm is developed to compute the external yaw moment. Through dynamic load allocation, considering the vertical load for each tire, intelligent external yaw moment distribution significantly improves vehicle stability. Finally, the results of the Carsim–Simulink co‐simulation demonstrate that, compared to the STSMC strategy, the FOSMC strategy with front‐wheel‐only steering, and the linear quadratic regulator (LQR) control strategy, the proposed control strategy in this paper reduces the tracking error by 77%, 61%, and 58%, respectively, achieving more precise and stable trajectory tracking under high‐speed conditions.

An Anti‐Attack Neural Sliding Mode Framework Based on a Novel Non‐Fragile Observer

ABSTRACTThis article investigates anti‐attack stabilization with passivity problem of uncertain singular semi‐Markov jump systems (singular S‐MJSs) with exogenous disturbance and delay. An ingenious non‐fragile observer‐based neural sliding mode control (SMC) scheme is put forward to solve the problem. First, considering unmeasured states, a distinctive non‐fragile and decoupled observer, which does not contain the control input or any auxiliary sliding mode compensator design as in existing observer‐based SMC approaches, is established such that the disadvantages of sliding mode switching in observers in existing literature can be avoided. Then, “only one sliding surface” design and a new system analysis route are presented, and the derived sliding surface is accessibly designed. Next, a new version of stochastic admissibility and passivity sufficient condition is given, and a related algorithm via an optimization problem is proposed to determine the controller gain and the observer gain by linear matrix inequalities (LMIs). Further, a novel observer‐based anti‐attack neural SMC law, which utilizes a neural network‐based approach to approximate actuator attack, is proposed to stabilize the singular S‐MJSs against actuator attack. Finally, simulation and comparison results are presented, which demonstrate the effectiveness and superiority of our method.

Linear Disturbance Observer-Enhanced Continuous-Time Predictive Control for Straight-Line Path-Following Control of Small Unmanned Aerial Vehicles

This paper studies the straight-line path-following problem on the lateral plane for fixed-wing unmanned aerial vehicles (FWUAVs) which are susceptible to uncertainties. Firstly, based on the natural frame’s location on the prescribed reference paths, the command yaw angle (which is the basis for yaw angle control system design) is solved analytically by combining it with the errors of path following, attack angle, sideslip angle, attitude angles, and geometric parameters of the prescribed reference paths. Secondly, by considering complicated dynamic characteristics, a linear extended state observer is designed to estimate uncertainties such as nonlinearities, couplings, and unmodeled dynamics whose estimated values are incorporated into the continuous-time predictive controllers for feedback compensation. Finally, numerical simulations are conducted to demonstrate the advantages of the proposed method, including reduced tracking errors and enhanced robustness in the closed-loop system, as compared to the conventional nonlinear dynamic inversion and sliding mode control approaches.

Transportation for 4-DOF Tower Cranes: A Periodic Sliding Mode Control Approach

Transportation for 4-DOF Tower Cranes: A Periodic Sliding Mode Control Approach

An Improved Adaptive Sliding Mode Control Approach for Anti-Slip Regulation of Electric Vehicles Based on Optimal Slip Ratio

To optimize the acceleration performance of independently driven electric vehicles with four in-wheel motors, this paper proposes an anti-slip regulation (ASR) strategy based on dynamic road surface observer for more efficient tracking of the optimal slip ratio and enhanced vehicle acceleration. The method uses the Unscented Kalman Filter (UKF) observer to estimate vehicle speed and calculate the actual slip ratio, while a fuzzy controller based on the Burckhardt tire model identifies road surfaces. The road’s peak adhesion coefficient and optimal slip ratio curve are fitted using a Back Propagation Neural Network (BPNN) optimized by Particle Swarm Optimization (PSO). The control strategy further refines torque management through an adaptive sliding mode control (ASMC) that integrates adaptive laws and a super-twisting sliding mode approach to track the optimal slip ratio. Joint simulations with MATLAB/Simulink and Carsim on low-adhesion, joint, and split road surfaces demonstrate that the strategy quickly and accurately identifies the optimal slip ratio across various road surfaces. This enables the tire slip ratio to approach the optimal value in minimal time, significantly improving vehicle dynamic performance. Compared to conventional sliding mode controllers, the optimized ASMC reduces chattering and improves control precision.

Distributed finite-time sliding mode containment control for multi-unmanned surface vehicles with input and output quantization

To solve the containment control problem of multi-unmanned surface vehicles (USVs) with input and output quantization communication, we propose a distributed containment method using sliding mode control (SMC) technology. First, with only the quantized value of position information being available, a super-twisting algorithm (STA)-based observer is used to recover the unmeasured velocities of the follower USVs in a finite time. Second, based on the STA-based observer, a distributed SMC strategy is developed to guide the follower USVs closely into the convex hull formed by the leader USVs under quantized communication. Furthermore, the stability analysis is given to guarantee that sliding variables and containment position errors can converge to specified ranges related to the quantization parameters and the parameters of the STA-based observer. Finally, simulation results demonstrate the feasibility of the designed SMC approach.

Dynamic Sliding Mode Control of Spherical Bubble for Cavitation Suppression

Cavitation is a disadvantageous phenomenon that occurs when fluid pressure drops below its vapor pressure. Under these conditions, bubbles form in the fluid. When these bubbles flow into a high-pressure area or tube, they erupt, causing harm to mechanical parts such as centrifugal pumps. The difference in pressure in a fluid is the result of varying temperatures. One way to eliminate cavitation is to reduce the radius of the bubbles to zero before they reach high-pressure areas, using a robust approach. In this paper, sliding mode control is used for this purpose due to its invariance property. To force the radius of the bubbles toward zero and prevent chattering, a new dynamic sliding mode control approach is used. In dynamic sliding mode control, chattering is removed by passing the input control through a low-pass filter, such as an integrator. A general model of the spherical bubble is used, transferred to the state space, and then a state proportional-integral feedback is applied to obtain a linear system with a new input control signal. A comparison is also made with traditional sliding mode control using state feedback, providing a trusted comparison.

Compensation Function Observer-Based Backstepping Sliding-Mode Control of Uncertain Electro-Hydraulic Servo System

Observer-based control is the most commonly used method in the control of electro-hydraulic servo system (EHSS) with uncertainties, but it suffers from the drawback of low accuracy under the influence of large external load forces and disturbances. To address this problem, this paper proposes a novel compensation function observer-based backstepping sliding-mode control (BSMC) approach to achieve high-accuracy tracking control. In particular, the model uncertainties, including nonlinearities, parameter perturbations and external disturbances are analyzed and treated together as a lumped disturbance. Then, a fourth-order compensation function observer (CFO) is constructed, which fully utilizes the system state information to accurately estimate the lumped disturbance. On this basis, the estimate of the lumped disturbance is incorporated into the design of a backstepping sliding-mode controller, allowing the control system to compensate for the disturbance effect. The stability of the closed-loop control system under the CFO and BSMC is rigorously proven through the use of the Lyapunov theory, which guarantees that all the tracking error signals converge exponentially to the origin. Comparative simulations are carried out to show the effectiveness and efficiency of the proposed approach, i.e., compared with PID and ESO-based BSMC methods, the tracking accuracy is respectively improved by 94.86% and 88.19% under the influence of large external load forces and disturbances.

Disturbance observer based adaptive predefined‐time sliding mode control for robot manipulators with uncertainties and disturbances

AbstractThis article develops a predefined‐time sliding mode control approach for systems with external disturbances and uncertainties through a nonlinear disturbance observer (DO). For addressing predefined‐time stabilization problem of robotic manipulator system, a predefined‐time sliding mode surface is proposed, ensuring system states converge to origin within a predefined‐time once sliding mode surface is attained. Compared to conventional fixed‐time and finite‐time control strategies, a distinctive advantage of this scheme is that system settling time can be explicitly chosen in advance and independent of system states. To achieve predefined‐time performance, a disturbance observer is introduced to generate the disturbance estimate, which can be incorporated into controller to counteract disturbance. To address the systems uncertainty, an adaptive law is employed to estimate the unknown upper boundary of system uncertainties. Finally, the effectiveness and performance of the proposed scheme are illustrated by simulation and experiment.

Inductor current estimation based sensorless control of boost type DC-DC converter

This paper presents a nonlinear fast terminal sliding mode control approach for a two-phase interleaved boost converter (2PIBC), emphasizing the utilization of inductor current estimation for achieving current sensorless control. The proposed approach introduces a state and disturbance estimation algorithm (SDEA) to effectively estimate the inductor current, external disturbances, system parameter uncertainties, and unmodeled dynamics within a 2PIBC. The combination of the proposed controller and SDEA enhances the robustness of 2PIBC, enabling it to track the desired reference voltage accurately. The stability of the proposed scheme is rigorously demonstrated through the application of Kharitono’s stability criteria. Furthermore, extensive simulations have been conducted to compare the response of the proposed controller with other state-of-the-art sensorless controllers. Finally, the hardware results are shown to validate and ensure the feasibility of the proposed work.

Formation Control of Multi-agent Systems Over Directed Topologies: A Sliding Mode Control Approach With Prescribed-time Convergence

Formation Control of Multi-agent Systems Over Directed Topologies: A Sliding Mode Control Approach With Prescribed-time Convergence

SMC for discrete singular stochastic jump systems under semi-Markov kernel

In this study, the sliding mode control (SMC) is investigated for discrete singular stochastic semi-Markov jump systems under a semi-Markov kernel. Based on the remarkable application background and advantages in modeling complex dynamic systems, singular semi-Markov jump systems are utilized to address discrete SMC issues. A mode-dependent sliding function with a singular matrix is considered to reduce the effects of the numerical problems. The main aim is to use an improved approach to eliminate the matrix power terms so that the underlying augmented system can realize mean-square admissibility. An appropriate SMC law is constructed to achieve the reachability of the quasi-sliding mode, overcoming the difficulty caused by parameter uncertainty. Finally, the effectiveness of the SMC approach is verified using a DC motor model.

Control of a building system with sudden nonlinearity using the sliding mode technique

In civil engineering application such as the seismic resistant structural design, a building system often enters into its nonlinear range to minimize the force transfer to the superstructure. An ideal control design should enhance the usefulness of the nonlinear behavior by diminishing its adverse effects at a minimal control input. This study developed a unified feedback mechanism based on the sliding mode control approach that fostered the multiple selected modal control of a structural system undergoing linear and nonlinear stages of hysteretic deformations. The ideal sliding surface for controlling a specific mode was designed based on the interaction characteristics between two modes at two different stages of deformation. An ′ S′ type functional form of the control force was developed on either side of the sliding surface based on the velocity feedback of the system by ensuring reachability to the ideal sliding surface. To demonstrate the effectiveness of the adopted control, a five-story shear building with uniform mass and initial stiffness distribution with concentrated nonlinearity at the base column was considered under 10 earthquake excitations. The system was studied under the proposed control along with the uncontrolled system. In addition to the adopted control, a popular and existing LQG control technique was also implemented based on the equivalent linearized structural system for comparison. The adopted control provided the desired performance of the structural system while keeping the effectiveness of the system’s nonlinearity under earthquake excitations. Considering the system’s responses and the input control force, the efficiency of the adopted mechanism outperformed the LQG control, which was found to amplify the unfavorable effects of the system’s nonlinearity.

Adaptive sliding mode control for quadrotor transport systems with uncertain parameters and disturbances

SummaryQuadrotor transportation systems have been widely utilized in both commercial and civilian fields. However, challenges arise due to the variable payload mass and unpredictable wind disturbances during cargo transport, potentially leading to excessive payload swinging and system instability. To tackle this issue, this article proposes an adaptive sliding mode control approach that concurrently achieves trajectory tracking for the quadrotor and mitigates payload swinging. In the outer loop subsystem, the quadrotor dynamics model is partitioned into two components that is, actuated and underactuated components. Sliding surfaces are designed based on this divided system model, and two adaptive laws are designed to compensate for payload mass uncertainty and unknown wind disturbances. The system's asymptotic stability is assured through the application of the Lyapunov theorem. In the inner loop subsystem, a disturbance rejection controller is formulated. Comparative simulation results conclusively demonstrate the outstanding performance of the proposed method in terms of trajectory tracking and robustness.

Performance of Robust Type-2 Fuzzy Sliding Mode Control Compared to Various Conventional Controls of Doubly-Fed Induction Generator for Wind Power Conversion Systems

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.