Sliding Mode Control Research Articles (Page 1)

The power quality of the electrical supply system has been impacted by the increase in non-linear loads and renewable energy sources such as the solar and the wind power integrated into the grid. The poor power quality results in equipment damage, system shutdown, and data loss, leading to lower operational efficiency and higher maintenance costs. The voltage sag, voltage swell, voltage flicker and voltage harmonic distortions are the most common and severe issues. The dynamic voltage restorer is the most effective solution for these voltage quality problems, which injects necessary voltage levels at the time of faults in order to maintain the load side voltage within specified boundaries. The appropriate control technique should be adopted for the generation of firing pulses for power electronic switches used to construct this device. The classical sliding mode control has the disadvantage of taking a long time to minimize errors. The main objective of this paper is to improve the accuracy and durability the conventional algorithm by adding nonlinear quantity, resulting in the fast terminal sliding mode controller. Furthermore, the artificial neural network is combined with proposed methodology to improve performance of double feeder power system for nonlinear load conditions. The system is modeled and simulated in a MATLAB/Simulink environment with a proportional integral controller optimized by particle swarm optimization, genetic algorithm and mind blast algorithm followed by non-linear controllers. The faults are simulated to mimic voltage sags A, E and B with different load conditions like linear, dynamic and non-linear. The power quality indices like total harmonic distortion, harmonic compensation ratio, sag score and voltage sag lost energy index are considered for assessment of compensation percentage. It is observed that Sag Score is improved by 80% thus increasing voltage sag lost energy index to more than 95%. Therefore, quantitative data demonstrate the efficacy of the proposed method in mitigating voltage sag while simultaneously reducing grid voltage imbalance and distortion, irrespective of the fault type.

Adaptive sliding mode controller design for islanded microgrid

Hybrid Adaptive Sliding Mode Controller for Path Tracking of Wheeled Mobile Robot in Uncertainty

Adaptive fuzzy fractional-order terminal sliding mode control using adaptive neural network observation architecture with application to ultra-precision stages

Integration of linear extended state observer within proxy-based sliding mode control for a cable-driven aerial manipulator

Tilt Integral Derivative-Based Sliding Mode Control for Nonlinear Two Interacting Tanks

Adaptive super-twisting sliding mode control for trajectory tracking of underactuated ship

A novel sliding mode control based on qubit rotation angle for efficient manipulation of robotic arms

Abstract A control strategy is proposed for a trapezoidal back-EMF permanent magnet synchronous motor (commonly referred to as a brushless DC motor) driven by a four-switch, three-leg inverter. The motor is regulated using field-oriented control (FOC) with an outer speed loop governed by a Dung-Beetle Optimization (DBO) algorithm–based Artificial Neural Network tuned Proportional–Integral–Derivative (D-BAP) controller. The PID gains are optimized at discrete reference speeds ranging from 50 rpm to 3000 rpm under three load conditions (low, medium, and high) using the Integral of Time-weighted Absolute Error (ITAE) criterion. The optimized gain sets, along with the corresponding reference speed, actual speed, battery current, and battery voltage, are compiled into an extensive dataset used to train the ANN for adaptive online tuning. The trained network continuously updates the controller gains in real time, enabling robust adaptation to variations in mechanical load and DC-link voltage. The proposed D-BAP controller is benchmarked against conventional PI, fuzzy–PI, Model Predictive Control (MPC), and Sliding Mode Control (SMC), with both simulation and experimental results demonstrating superior speed tracking, minimal steady-state error, and enhanced robustness under nonlinear operating conditions.

In response to the demands for high reliability, excellent dynamic response, and high-precision control of advanced aircraft actuation systems, this study focuses on the control technology for the master-master operating mode of dual-redundancy electro-hydrostatic actuation (EHA) systems. A multi-domain coupling model integrating motor magnetic circuit saturation, hydraulic viscosity-temperature characteristics, and mechanical clearances was established, based on which a current-loop decoupling technique using vector control was developed. Furthermore, the study combined adaptive sliding mode control (ASMC) and an improved active disturbance rejection control (ADRC) to enhance the robustness of the speed loop and the disturbance rejection capability of the position loop, respectively. To address the key challenges of synchronous error accumulation and uneven load distribution in the master-master mode, a dual-redundancy dynamic model accounting for hydraulic coupling effects was developed, and a two-level cooperative control strategy of "position synchronization-dynamic load balancing" was proposed based on the cross-coupling control (CCC) framework. Experimental results demonstrate that the position loop control error is less than ±0.02 mm, and the load distribution accuracy is improved to over 97%, fully meeting the design requirements of advanced aircraft. These findings provide key technical support for the engineering application of power-by-wire flight control systems in advanced aircraft.

This research presents the design of a robust nonlinear controller for the lateral dynamics of a self-driving car. It is based on the block control and super-twisting sliding mode control techniques in order to effectively mitigate the uncertainties and disturbances of the vehicle. The dynamic model of the system is composed of the standard bicycle dynamic model (not kinematic) for the vehicle and the dynamics of a BLDC motor connected to a steering rack system as the steering actuator. Moreover, the control scheme considers an inner loop for controlling the actuator position based on the field-oriented control (FOC) and PID control approaches. The controller’s overall performance is validated through its application to a mathematical model of a brushless direct current (BLDC) motor, acting as the actuator, plus the steering rack dynamics and the lateral dynamic model of the vehicle. Measurements of voltages and currents are taken in both the abc and dq reference frames, the latter being commonly used in the field-oriented control (FOC) technique. Additionally, the system’s performance is evaluated in terms of trajectory tracking, orientation, and lateral deviation from the lane center.

A straightforward and effective nonlinear control strategy for quadcopters is presented, designed to prevent collisions using a Proportional–fractional order-integral–derivative sliding surface sliding mode control with backstepping controller. This controller enables the quadcopter to evade both single and multiple obstacles. When an obstacle with a high collision risk is identified, a virtual spherical boundary around the obstacle is created to define the collision zone. The controller then calculates the angular tracking errors between the quadcopter’s current trajectory and the tangential lines extending from its position to the boundary sphere, using these to adjust the quadcopter’s path for collision avoidance. A method is proposed to guide the quadcopter to its intended destination after successfully avoiding obstacles. The performance of this collision-avoidance algorithm is validated through simulation results.

The development of robust and efficient wireless charging systems is essential for the widespread adoption of electrification in the transport sector, e.g., Electric Vehicles (EVs). Capacitive Wireless Power Transfer (CWPT) has emerged as a promising alternative to inductive methods, offering advantages such as lower cost, lighter structure, and reduced electromagnetic interference. However, the performance of practical CWPT systems, particularly systems employing simple L-type compensation networks, is severely affected by coupling plate misalignment, which causes variations in coupling capacitance. These variations give rise to a pseudo-resonance phenomenon, wherein conventional controllers, such as traditional Sliding Mode Control, mistakenly regulate reactive power to zero at an off-resonant frequency, leading to a drastic collapse in active power transfer. To overcome this limitation, this paper introduces a novel Adaptive Sliding Mode Control (ASMC) framework augmented with an online Recursive Least Squares (RLS) observer for real-time estimation of the time-varying coupling capacitance. The proposed dual-loop control structure integrates an inner adaptive loop that accurately tracks capacitance changes and an outer sliding mode loop that dynamically adjusts the inverter switching frequency to sustain true resonant operation. A rigorous Lyapunov-based stability analysis confirms global convergence and robustness of the closed-loop system. Comprehensive MATLAB/Simulink R2025a simulations validate the proposed approach, demonstrating its capability to maintain zero reactive power and stable 35 kW power transfer with over 95% efficiency under dynamic misalignment conditions of up to 30%. In contrast, a conventional SMC approach experiences severe pseudo-resonant collapse, with output power degrading below 1 kW. These results conclusively highlight the effectiveness and necessity of the proposed ASMC-RLS strategy for achieving robust, misalignment-tolerant CWPT in high-power EV charging applications.

To enhance the precision, load capacity, disturbance rejection, and reliability of shipborne parallel stabilization platforms under complex sea conditions, this paper proposes a redundant, actuated, parasitic-motion-free 3-DOF 3RRS-RUS parallel stabilization platform. Based on the proposed 3RRS-RUS shipborne parallel stabilization platform, a Linear Active Disturbance Rejection Control (LADRC) approach, integrated with a Sliding Mode Disturbance Observer (SMDO), is developed. First, the mechanism is synthesized using screw theory, and its 2R1T 3-DOF characteristics are verified through parasitic motion analysis. Second, the inverse kinematics model is established. Third, the conventional LADRC is decoupled, and a new Linear Extended State Observer (LESO) together with its corresponding control law is designed. Moreover, an SMDO is incorporated into the motor’s three-loop control scheme to alleviate the estimation burden on the LESO and enhance the system’s disturbance rejection capability. Finally, experimental validations were carried out on both the CSPACE and SimMechanics platforms. The results demonstrate that the proposed SMDO–LADRC achieves superior tracking performance, high robustness, and strong disturbance rejection capability, The tracking errors along the RX, RY, and Z axes were reduced by 6.5%, 1.1%, and 16.6%, respectively, compared with the conventional LADRC, while also confirming the feasibility of the newly designed 3-DOF 3RRS-RUS shipborne parallel stabilization platform.

This study evaluates the performance and robustness of a port-Hamiltonian controller for the links of a liquid mirror telescope and a PI controller for the rotation of its liquid mirror, using ROS2 and Gazebo. The telescope links track a star’s apparent daily motion, while the liquid mirror achieves the required angular speed for a desired focal length. These references are computed based on the star’s name and focal length input. The telescope’s physical properties, including dimensions, masses, inertia, and 3D models, are stored in a Unified Robot Description Format (URDF) file, enabling Gazebo to initialize accurate simulations. Joint information—state interfaces (angular position and speed) and command interfaces (effort)—is also defined in the URDF. Controller configurations, including gains, bounds, and control parameters, are stored in a YAML file, ensuring seamless integration with Gazebo. The evaluation encompasses key performance metrics. For the two-link telescope, tracking accuracy, settling time, control effort, and energy efficiency are analyzed. For the liquid mirror, the primary focus is on tracking precision. The port-Hamiltonian controller’s performance is compared to inverse dynamics and super-twisting sliding mode controllers. Results show that the port-Hamiltonian controller achieves a favorable balance between accuracy and energy efficiency, exhibiting smoother control actions that reduce energy consumption and actuator wear. Its stability under varying conditions ensures high precision for astronomical observations. Furthermore, ROS2 and Gazebo provide a risk-free environment for extensive testing, facilitating a smooth transition to real-world implementation.

In this study, we introduce a novel adaptive fault-tolerant sliding mode control strategy for the finite-time control of symmetric robotic manipulators subjected to uncertainties, disturbances and actuator failures. Firstly, we design a novel type of sliding mode manifold termed Practical Fast Terminal Sliding Mode (P-FTSM). P-FTSM exhibits the capability to accelerate convergence speed while ensuring the finite-time convergence of the system. Subsequently, the P-FTSM is integrated with the super-twisting algorithm (STA) to mitigate the chattering of control input. Additionally, a novel K∞ function is introduced to serve as the gain of the STA. This strategy, which does not require knowledge of the upper bound of the disturbance and fault information, ensures that the gain is tuned according to the disturbance and fault variations, mitigating the adverse effects of high gain and further weakening of the chattering. Simulation results on a two-link symmetric manipulator verify that the proposed method achieves outstanding quantitative performance. The proposed method achieves convergence times of 0.22 and 0.12 s for the joint errors, with root mean square errors (RMSE) of 0.036 and 0.095. The integral absolute errors (IAE) are 0.049 and 0.086, and the total control energy is 943.46. The total variations (TV) of the control signals are 2.86×103 and 1.64×103, indicating effectively suppressed chattering. Overall, the proposed strategy ensures high precision, rapid convergence, and strong fault-tolerant capability.

ABSTRACT The spacecraft attitude tracking problem with prescribed performance in the presence of environmental disturbance, model uncertainty, actuator faults, and saturation presents a significant challenge. Under these tough conditions, this paper proposes an adaptive model predictive control (MPC) with a novel appointed‐time performance function (APF) constraint to achieve high‐performance attitude tracking trajectories with appointed‐time convergence. Firstly, within the proposed MPC framework, an optimal attitude trajectory is obtained, respecting the performance boundary and actuator limitations. Next, by introducing a contraction constraint via prescribed performance auxiliary sliding mode control (SMC), the recursive feasibility and closed‐loop stability of MPC are rigorously demonstrated. Additionally, the function‐adaptive law is employed to estimate and compensate the total disturbances. Finally, simulations are conducted to demonstrate the effectiveness and validity of the proposed adaptive appointed‐time prescribed performance MPC algorithm.

Reduced chattering target-tracking sliding mode control for intraprocedural propofol control.

Adaptive sliding mode control of gap-like manipulators based on an improved hybrid algorithm-optimized neural network

ABSTRACT This work investigates the robust sliding mode control (SMC) law design for uncertain T‐S fuzzy singular semi‐Markovian jump systems (S‐SMJSs) with time‐varying delays and one‐sided Lipschitz (OSL) nonlinearities. A fuzzy integral sliding mode surface (SMS) is designed. Then, given that the modeling of general fuzzy systems struggles to approximate the complex nonlinearities in practical systems, this work addresses more general nonlinearities considering the T‐S fuzzy strategy, the OSL condition, and the quadratically inner‐bounded (QIB) condition. A mode‐dependent Lyapunov function is designed, and sufficient conditions of stochastic admissibility are derived for the sliding motion with performance by using a novel matrix constraint condition and a scaling approach, which have lower conservatism. Moreover, an appropriate SMC law is proposed, which can satisfy the reachability condition and keep the sliding motion admissible under the disturbances and nonlinearities. Finally, the effectiveness of the results is validated by four examples.