Landing of Aircraft Using Integral State Feedback Sliding Mode Control

Integral Discrete-time Sliding Mode Control of Homogeneous Charge Compression Ignition (HCCI) Engine Load and Combustion Timing

This paper proposes a Decentralized Integral Single-phase Sliding Mode Control (DISSMC) for Load Frequency Control (LFC) in Complex Power Systems with Multi-Source generation (CPSMS), integrating reheat, hydro, gas, and wind turbines. A generalized structure is employed to model Multi-Area Linked Power Systems (MALPS), providing a realistic representation of diverse power plants. The proposed method formulates an integral Sliding Surface (SS) to mitigate the chattering phenomena and ensures finite-time stability through a continuous control law. Additionally, a single-phase technique eliminates the reaching phase, ensuring immediate trajectory control. The MATLAB/Simulink simulations validate the DISSMC's effectiveness in stabilizing frequency fluctuations and managing load variations across three interconnected regions, each hosting different power plant types. The results highlight the proposed controller's robustness and adaptability to dynamic load and renewable energy source fluctuations.

Precise and robust position tracking control of surgical robots is essential to perform efficient surgery. Even though a variety of control algorithm has been developed for robust trajectory tracking, but most of them are dependent on the exact modeling of the system to guarantee their accuracy and robustness. Unlike the industry manipulator, surgical robot has inevitable uncertainties from surgical environment such as trocar and wire-cable friction. In this paper, we propose a model-free controller that combines simplicity of PD control and robustness of sliding mode control. The PD-ISMC (Integral Sliding Mode Control) is designed by adding the integral part of the error to sliding surface of the previously proposed PD-SMC and the robust trajectory tracking performance was verified by using the actual surgeon's surgical motion data and implementing master-slave system.

This paper reports a new technique of control combining the concepts of sliding mode control and the multimodel approach. Baptized Integral Pseudo Sliding Mode Control, this control strategy, reduces the library of models whose number can block the establishment of the multi model control strategy in real time. It also allows, on the one hand, having a robust behavior compared to certain classes of uncertainties, and, on the other hand eliminating completely the chattering phenomenon.

In order to improve the robustness and increase the fast response, a novel current controller with the integral sliding mode control and quasi-PR control is proposed for the quasi-Z source inverter (qZSI). Firstly, the state space equations of the qZSI are established. Secondly, the sliding surface of the proposed controller is built. In the same time, the stable, existence and arrival conditions of the sliding surface are derived. Thirdly, a compound control strategy has been analysis analyzed. Finally, a MATLAB model is built. The simulation results verify the proposed controller can achieve a faster dynamic response and realize stable compared to the traditional PI controller.

Integral Sliding Mode Control with Exponential Reaching law for PMSM in Electric Vehicles

The hemodialysis is a medical application dedicated to the patient who suffers from a renal insufficiency, with the help of an extracorporeal circuit and an artificial kidney, the device replaces the functioning of the kidney, thanks to a peristaltic pump, the blood is taken, purified and then reinjected into the body of the patient. The application of the stepper motors is widely used, due to its multiple advantages, such as the price, the control with an open loop, etc… the aim of this paper to study the control of the stepper motor in order to apply it to motorize the blood pump of the hemodialysis. We start with a modeling of the motor, development of the equations necessary to calculate the gains of the digital corrector by state control and the parameters of the variable structure controller by integral sliding mode. The simulation of the correctors is done in order to find the appropriate control, two situations are targeted, the simulation with and without load torque. The state space representation is applied to model the regulated system, thus the vector control in the d-q axes is implemented to facilitate the control. Due to the non-linearity of the stepper motor, the speed and position control requires a robust and efficient control, the simulation presents important results in order to interpret them and deduce the main factors to control the motor in a convenient way.

This article presents a novel reinforcement learning (RL)-based control scheme for trajectory tracking of robot manipulators, incorporating an uncertainty estimator and an optimal tracking controller. A momentum observer (MO) is implemented in conjunction with an integral sliding mode control (ISMC) to facilitate uncertainty estimation for compensation. A proportional-derivative-like (PD-like) control plus an actor-critic neural network (NN)-based feedforward control is utilized for trajectory tracking. An NN parameter selection scheme is adopted to circumvent the time-consuming adjustments of its activation functions and initial weights, thereby ensuring the admissibility of the initial control policy and improving its efficiency. Lyapunov function analysis demonstrates stability of the closed-loop system, in which all error signals are shown to remain bounded and eventually settle into a small residual set. The proposed control scheme is compared with a conventional PD approach consisting of a feedforward controller and an NN controller with adaptive radial basis functions (RBFs). Comparison is also made with a recent approach featuring a feedforward super-twisting sliding mode control (FSTSMC). Simulation and experimental results show superior tracking performance of the presented control scheme against the comparative counterparts, validating the new approach and further supporting its effectiveness and feasibility.

This paper establishes a novel approach of robust active compliance control for a robot hand via an Integral Sliding Mode Controller (ISMC). The ISMC allows us to introduce a model reference approach where a virtual mass-spring damper system can be used to design a compliant control. In order to allow for practical grasping, we consider the shape of the object to be grasped. Hence, the work exploits a grasping technique via Cylindrical and Spherical coordinate systems due to their simplicity and geometric suitability. The control uses the operational space approach. Thus, the control is split into a task control and a particular optimizing posture control. The experimental results show that target trajectories can be easily followed by the task control despite the presence of friction and stiction while the posture controller maintains a desired finger posture. When the object is grasped, the compliant control will automatically adjust to a specific compliance level. Once a specific compliance model has been achieved, the fixed compliance controller can be tested for a specific scenario. The experimental results prove that the BERUL hand can automatically and successfully attain different compliancy levels for a particular object via the ISMC.

To advance the efficiency and dynamic responsiveness of electric vehicles (EVs), this study introduces a comprehensive intelligent control and energy-management framework that couples a superconducting magnetic energy storage (SMES) assisted hybrid energy storage system (HESS) with a synchronous reluctance motor (SynRM) drive. The proposed configuration exploits the high power density and instantaneous response of SMES to enhance performance during transient load changes. To mitigate nonlinear behaviors, parameter deviations, and external disturbances within both HESS and SynRM subsystems, two resilient nonlinear controllers are designed: an Adaptive Barrier Function based Super-Twisting Sliding Mode Controller (ABC-STSMC) and a Synergetic Controller. The adaptive gains of the ABC-STSMC are tuned automatically through the Whale Optimization Algorithm (WOA) to ensure optimal robustness. Moreover, a deep reinforcement learning–driven energy management system (RL-EMS) governs real-time power allocation among the SMES, supercapacitor, and fuel cell, thereby maximizing overall efficiency and component longevity across variable driving conditions. The framework is validated through MATLAB/Simulink simulations and Hardware-in-the-Loop (HIL) experimentation. Quantitative comparisons with conventional Sliding Mode Control (SMC) and Integral Sliding Mode Control (ISMC) demonstrate that theWOA-optimized ABC-STSMC improves transient response by 28%, enhances tracking accuracy by 35%, and strengthens disturbance rejection. Simultaneously, the RL-EMS lowers switching losses and ensures balanced energy utilization. Collectively, the integrated control and management scheme offers higher reliability, robustness, and adaptability, positioning it as a promising solution for future high-performance electric mobility systems.

This paper proposes an integral sliding mode control with a novel model-based iterative feedforward compensating the hysteresis to finish high-precision positioning control of the piezoactuated stage. The Bouc-Wen model is established to design a novel iterative feedforward control (IFC) method. The IFC reduces the effects of inherent hysteresis on the positioning precision of the piezo-actuated stage. The positioning error of the IFC is inevitable because of the model uncertainty. Subsequently, an integral sliding mode control algorithm is implemented to further decrease the tracking error and enhance the anti-disturbance capability of the IFC. To reduce the chattering of the proposed controller, a boundary layer method based on Fal-function is designed. The stability of the integral sliding mode control is analyzed via Lyapunov stability theory. The feasibility of the proposed controller is certified by a series of simulation results. Compared with the IFC and conventional sliding mode control (CSMC) method, the proposed controller has higher performance in terms of the positioning precision of piezo-actuated stages.

Comparative study of PD and Integral Sliding mode control (ISMC) is designed for a flexible 5-link planar robot manipulator. This comparative study enables us to observe the performance characteristics of the two controllers. The controller for the flexible body motion is designed to enforce the state trajectory onto a desired sliding surface and then guides it into the state space origin. The integral sliding mode control is used to reject the disturbance in the system and later helps the system to remain in a continuous control with the implementation of Super-twisting algorithm thereafter. These control techniques suppresses the uncertainties due to parametric variations and external disturbances. The efficacy and robustness of the proposed integral and super-twisting controllers are confirmed via computer simulations.

In this paper, high order observer (HOO) and integral sliding mode controller (ISMC) are studied in the system of permanent magnet synchronous motor (PMSM) with the uncertainty disturbance. The system is divided into two loops: current loop and speed loop for ISMC and HOO. HOO can get the estimated value of external interference and the uncertain parameters’ disturbance. The estimated value got from HOO will also be accurate because of the high-order characteristic of HOO. ISMC with the estimated disturbance has better robust and performance. The simulations prove the effectiveness of the ISMC and HOO.

In order to guarantee that grasping with robot fingers are safe when interacting with a human or a touched object, the robot fingers have to be compliant. In this study, a novel active and robust compliant control technique is proposed by employing an Integral Sliding Mode Control (ISMC). The ISMC allows us to use a model reference approach for which a virtual mass-spring damper can be introduced to enable compliant control. The performance of the ISMC is validated for the constrained underactuated BERUL (Bristol Elumotion Robot fingers) fingers. The results show that the approach is feasible for compliance interaction with objects of different softness. Moreover, the compliance results show that the ISMC is robust towards nonlinearities and uncertainties in the robot fingers in particular friction and stiction.KeywordsIntegral Sliding Mode ControllerActive Compliance ControlUnderactuated Robot FingersRobust Control

This paper develops a novel integral sliding mode controller (ISMC) for a general type of underwater robots based on multiple-input and multiple-output extended-state-observer (MIMO-ESO). The difficulties associated with the unmeasured velocities, unknown disturbances, and uncertain hydrodynamics of the robot have been successfully solved in the control design. An adaptive MIMO-ESO is designed not only to estimate the unmeasurable linear and angular velocities, but also to estimate the unknown external disturbances. An ISMC is then designed using Lyapunov synthesis, and an adaptive gain update algorithm is introduced to estimate the upper bound of the uncertainties. Rigorous theoretical analysis is performed to show that the proposed control method is able to achieve asymptotical tracking performance for the underwater robot. Experimental studies are also carried out to validate the effectiveness of the proposed control, and to show that the proposed approach performs better than a conventional potential difference (PD) control approach.