Sliding Mode Control Approach Research Articles

High-performance induction motor drive based on adaptive super-twisting sliding mode control approach

High-performance induction motor drive based on adaptive super-twisting sliding mode control approach

Secure Path Following Control of Autonomous Vehicles Under Actuator Attacks Using Fuzzy Terminal Sliding Mode Control Approach

Secure Path Following Control of Autonomous Vehicles Under Actuator Attacks Using Fuzzy Terminal Sliding Mode Control Approach

Modeling dynamics and stability analysis of pneumonia disease infection with parameters uncertainties control

In this work, a mathematical model of six compartments is formulated, showing the dynamic flow of pneumonia disease in the human population with treatment and vaccination interventions. Equilibria points and stability analyses were carried out using the Lyapunov function approach. Analytically, it is found that at the disease-free equilibrium state, local and global asymptotic stability behaviors are achieved when [Formula: see text] with instability if [Formula: see text]. However, at the endemic equilibrium point, asymptotic stability is attainable if [Formula: see text] and instability otherwise. The study indicates that pneumonia disease infection is successfully reduced when treatment and vaccination interventions are administered to the patients. The work also proposes an adaptive sliding mode control approach with a closed-loop control system to manage pneumonia epidemic model uncertainties. This approach intends to reduce disease transmission and infection through successful tracking of defined trajectories and managing uncertainties. For the control rates [Formula: see text], the technique managed to track the disease carriers and infectious agents accurately even in the presence of parameter uncertainties. In conclusion, an increase in the control rates [Formula: see text] in the existence of parameter uncertainty control systems significantly reduces the number of disease transmitters and infectious agents quicker than in their absence. Hence, this study signifies the pivotal role of treatment and vaccination in the control of pneumonia infection as well as the control of parameter uncertainties by the proposed method.

Sliding Mode Control Approach for H2 Purity Regulation in High-Pressure Alkaline Electrolyzers

This paper presents the design of a Sliding Mode Control (SMC) for H2 purity regulation in high pressure alkaline electrolyzers. The control scheme is based on mixing the concepts of sliding-mode control with a PID sliding surface and Bristol matrix design. A 25-state dynamic model of the high-pressure alkaline electrolyzer is considered from the literature. The results show that the proposed control scheme design is simple, and the results obtained motivate more studies to be used in more realistic applications.

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

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

Chattering-Free Second Order Robustness Sliding Mode Controller for Complex Interconnected Systems: A Moore-Penrose Inverse Technique

In this paper, a novel second order sliding mode control approach is extended toa class of complex interconnected systems with mismatched interconnections and unknown perturbations. The key contribution of this paper is to cancel two common restrictions clogging the application of the variable structure control to complex interconnected systems: 1) all of state variables must be accessible; 2) the control input is affected by chattering problems. First, a novel reduced-order sliding mode estimator (ROSME) is proposed to estimate the unmeasurable variables. Second, based on Moore-Penrose inverse technique and ROSME tool, a new decentralized chattering-free second order robustness sliding mode controller (CSORSMC) is developed to force the system states to stay in a sliding surface from the initial period instance and attenuate the chattering phenomenon in the control signal. Besides, a novel appropriate linear matrix inequality (LMI) requirement is proved such that the plant in sliding mode is asymptotically stable. Lastly, a mathematical model including two subsystems is simulated which confirms the usefulness and advantages of proposed technique.

Terminal sliding mode control based on recursive stochastic configuration network for ball mill lining replacement process

The precise control of multi-joint manipulators presents significant challenges in the context of replacing internal liners of large grinding machines. These challenges arise due to the uncertainty of system parameters and external disturbance. A terminal sliding mode control based on a recursive stochastic configuration network is proposed to ensure that the system is stable, and it reduces system oscillations in this article. In addition, a disturbance observer based on recursive stochastic configuration network is designed to estimate and compensate for the uncertainties in the system, thereby improving the robustness of the system. To enhance the realism of the simulations, the simulation modeling process incorporated uncertainty parameters and external disturbance information. The simulation results demonstrated the effectiveness of the proposed terminal sliding mode control approach in meeting the practical control requirements. This accomplishment presents a valuable new method for controlling mechanical arms. The method is applicable under conditions of system uncertainty and external disturbance.

Fully Distributed Event-Triggered Formation Control for Multiple Quadrotors

This paper studies fully distributed formation control problems for multi-quadrotor systems with external disturbances via an event-triggered approach. For leader-follower multi-quadrotor systems, a fully distributed event-triggered formation control (DETFC) framework is proposed by utilizing an adaptive sliding-mode control approach, which does not rely on any global information of the network topology. The finite-time reachability of the sliding-mode surface can be guaranteed for the states of the nonlinear, coupled and underactuated system subject to external disturbances. Meanwhile, the zeno behavior of the proposed event-triggered protocol is proved to be excluded. A novel dynamic sliding-mode surface is designed to guarantee the formation performance as the quadrotor state trajectories move on the constructed sliding manifold. Via Lyapunov stability theory, sufficient conditions to ensure the formation results are derived for multi-quadrotor systems. Simulations and experiments are conducted to validate the effectiveness of the proposed control scheme.

A Sliding Mode Control-Based Guidance Law for a Two-Dimensional Orbit Transfer with Bounded Disturbances

The aim of this paper is to analyze the performance of a state-feedback guidance law, which is obtained through a classical sliding mode control approach, in a two-dimensional circle-to-circle orbit transfer of a spacecraft equipped with a continuous-thrust propulsion system. The paper shows that such an inherently robust control technique can be effectively used to obtain possible transfer trajectories even when the spacecraft equations of motion are affected by perturbations. The problem of the guidance law design is first addressed in the simplified case of an unperturbed system, where it is shown how the state-feedback control may be effectively used to obtain simple mathematical relationships and graphs that allow the designer to determine possible transfer trajectories that depend on a few control parameters. It is also shown that a suitable combination of the controller parameters may be exploited to obtain trade-off solutions between the flight time and the transfer velocity change. The simplified control strategy is then used to investigate a typical heliocentric orbit raising/lowering in the presence of bounded disturbances and measurement errors.

Cognitive-Radio-Based Resource Management for Smart Transportation: A Sliding Mode Control Approach

Smart transportation is one of the key components of the smart city. A significant amount of data is produced by the numerous vehicles connected via wireless networks. This demands smart spectrum management for efficient data communication. The optimal bandwidth usage can be obtained by opportunistically sharing the spectrum among high-priority class primary and low-priority class secondary users’ vehicles. In this study, we develop a mathematical model to ensure effective resource allocation in Cognitive Radio based Smart Transportation Networks (CR-STN) considering the mobility, bandwidth constraint and interference models. Robust sliding mode control is synthesized using an exponential reaching law to avoid data packet congestion in CR-STN to ensure smart spectrum management. In addition, a dynamic event-triggered mechanism is incorporated with the sliding mode controller to reduce computational complexity and energy expenses. The effectiveness of the suggested controller has been validated by simulation results.

Wavelet Fuzzy Neural Supertwisting Sliding Mode Control of an Active Power Filter

This paper presents a new intelligent sliding mode control approach to effectively achieve harmonic suppression of an active power filter (APF). An intelligent complementary terminal sliding mode controller (CTSMC) is proposed to improve the control accuracy of current loop and deal with the lumped disturbances in the system. Complementary terminal sliding mode control combines the features of complementary sliding mode control (CSMC) and terminal sliding mode control (TSMC) and does not depend on an accurate dynamic model. In addition, in order to reduce chattering, a multi-loop neural network (MLNN) whose parameter learning laws of MLNN are derived based on the Lyapunov laws are proposed to approximate the unknown nonlinear function term in the APF dynamic model, thus reducing the burden of sliding mode control. Finally, within the computing power of control board, detailed simulation and hardware experiments are carried out to demonstrate it has better harmonic suppression, steady-state and dynamic performance compared with the existing methods.

An Advanced Physiological Control Algorithm for Left Ventricular Assist Devices

Left ventricular assist devices (LVADs) technology requires developing and implementing intelligent control systems to optimize pump speed to achieve physiological metabolic demands for heart failure (HF) patients. This work aimed to design an advanced tracking control algorithm to drive an LVAD under different physiological conditions. The pole placement method, in conjunction with the sliding mode control approach (PP-SMC), was utilized to construct the proposed control method. In this design, the method was adopted to use neural networks to eliminate system uncertainties of disturbances. An elastance function was also developed and used as an input signal to mimic the physiological perfusion of HF patients. Two scenarios, ranging from rest to exercise, were introduced to evaluate the proposed technique. This technique used a lumped parameter model of the cardiovascular system (CVS) for this evaluation. The results demonstrated that the designed controller was robustly tracking the input signal in the presence of the system parameter variations of CVS. In both scenarios, the proposed method shows that the controller automatically drives the LVAD with a minimum flow of 1.7 L/min to prevent suction and 5.7 L/min to prevent over-perfusion.

Event-triggered formation-containment control for multi-agent systems based on sliding mode control approaches

In this article, event-triggered (ET) formation-containment control is profoundly investigated for discrete-time multi-agent systems (DT-MASs) in the framework of sliding mode control (SMC). The ET mechanism is utilized to effectively relieve the communication burden and SMC is employed to reliably handle the matching disturbances to enhance the control performance. According to this task, a novel ET controller based on SMC is constructed to ensure that a desired formation shape (i.e. a convex hull) is definitely formed by all leaders, and involves the trajectories of all followers. Then, sufficient conditions to solve the desired controller settings are deduced with the aid of the feature of Laplacian matrices as well as some essential inequality techniques. Furthermore, the reachability of constructed sliding surfaces is systematically revealed and the predetermined manifold is reachable in finite time. Finally, the efficiency of the designed control rule is verified with simulation examples.

Event-Triggered SMC for Networked Markov Jumping Systems With Channel Fading and Applications: Genetic Algorithm.

The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jumping systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order to reduce resource consumption in the transmission process, an event-triggered protocol is adopted for networked MJSs. A key feature is that the signal transmission is inevitably affected by fading phenomenon due to delay, random noise, and amplitude attenuation in a networked environment. With the aid of a common sliding surface, an event-triggered SMC law is designed by adjusting the system network mode. Under the framework of stochastic Lyapunov stability, sufficient conditions are constructed to ensure the mean-square stability of the closed-loop networked MJSs, and the sliding region is reached around the specified sliding surface. Moreover, based on the iteration optimizing accessibility of objective function, an effective SMC approach under genetic algorithm is proposed to minimize the convergence region around the sliding surface. Finally, the effectiveness of the proposed method is proved by the F-404 aircraft model.

Vadim I. Utkin and sliding mode control

Professor Vadim I. Utkin, long recognized for his powerful sliding mode control approach, which he founded in the early 1960s, passed away on September 18, 2022. The authors were close to Professor Utkin for many decades and have had the opportunity to observe his pioneering research resulted in many contributions to modern control theory. The present paper is a tribute to Professor Utkin, in which the authors recall the main milestones of his scientific path.

Data‐driven integral terminal sliding mode fault‐tolerant control for a collection of discrete‐time nonlinear systems

AbstractThe manuscript proposes a data‐based integral terminal sliding mode control approach to determine fault‐tolerant control (FTC) concerning a class of discrete‐time nonlinear systems (DTNS) containing sensor fault. The proposed scheme can be readily implemented because it purely utilizes the input and output data of the system to employ a model called the compact form dynamic linearization (CFDL) data model, while the one‐step forward approximator is employed to estimate the fault function term in the system. Moreover, the fault diagnosis mechanism utilizes a time‐varying threshold with prescribed performance to judge whether the fault occurs. Hence, the problem of a standard fixed threshold used at the start‐up state of the control system is resolved. Then, the discrete‐time integral terminal sliding mode fault‐tolerant control (DITSM‐FTC) method is proposed. Concurrently, the sturdiness of the proposed method is assured by hypothetical investigation. When compared with the literature, the fundamental features of the proposed method are presented as follows: (1) the problem pertinent to fault utilizing a data‐driven model is resolved; (2) a fault diagnosis mechanism with prescribed performance is proposed, and (3) one step forward approximator is utilized to devise an estimation approach of fault detection. Finally, the efficacy of the proposed method is presented by running simulations.

Stability analysis of a cart-pendulum model with variable convergence rate: A sliding mode control approach for impulsive stochastic systems

In this paper, a sliding mode control problem with variable convergence speed for impulsive stochastic systems based on the cart-pendulum model is investigated. Firstly, the cart-pendulum is modeled as impulsive stochastic system and the interval-driven stability criterion for variable convergence rate is given according to the idea of pole configuration. Meanwhile, the corresponding sliding mode surface functions are designed by pre-adjusting the intervals which in turn regulate the convergence rate of the target system states. To attenuate the oscillation phenomenon that exists in the sliding mode control, the new continuous control rate function is designed on the basis of the saturation function. In addition, a sliding mode control strategy for impulsive stochastic systems is presented to ensure the reachability of the designed sliding surface in finite time and the stability of the reduced-order system under motion of the sliding mode. Finally, the cart-pendulum simulation results demonstrate the effectiveness and feasibility of the sliding mode control.

Automatic vibration control method for grasping end of flexible joint robot

Because flexible robots have flexible components such as reducers, there are problems of accuracy deviation and end vibration in the process of external interference and trajectory tracking. This leads to the proposal of a Sliding Mode Control Approach Based on RBF Neural Network (SMC-RBF) parameter optimization. This method is mainly applied to reduce the end vibration and running position error of flexible robot. Firstly, the Newton-Euler method is used to establish the dynamic model of robot considering joint flexibility. At the same time, the experiment optimizes the Sliding Mode Control (SMC) method through RBF neural network. The experiments verify the control methods of the two-joint flexible robot and the six-joint flexible robot respectively. In the control of two-joint robot, the maximum tracking curve error of SMC is only about 0.25 rad under the interference of pulse signal; And the recovery time is only about 1 s. In the control of 6-joint robot, the maximum error of RBF-sliding mode control method on XYZ axis is 0.7 mm, 0.25 mm and 1.25 mm respectively; The error on three axes is smaller than that of traditional PD control method. The results demonstrate that the tracking error of the improved mode control is small, the chattering phenomenon of the robot system is weakened as well.

An LMI adaptive-barrier function global sliding mode control of uncertain nonlinear systems with input saturation

This paper proposes a barrier function-based adaptive control strategy with a nonlinear sliding surface for a class of uncertain dynamic systems with input saturation. Its main objectives are to ensure robustness to parametric and non-parametric uncertainties whilst eliminating the reaching phase. A global nonlinear switching surface is defined and an adaptive barrier function sliding mode control approach is derived. The barrier strategy is adopted to ensure the convergence of the states to the desired values without overestimating the control gains. System stability is analyzed using the Lyapunov stability theory. The control parameters are obtained using the linear matrix inequality (LMI) approach. The control law is designed to remove the reaching phase. The effectiveness of the proposed approach was validated using a simulation study. The proposed control approach can easily be implemented to various nonlinear uncertain systems.

A Hybrid Solar Photovoltaic and Wind Turbine Power Generation for Stand-Alone System with IoT-Based Monitoring and MPPT Control

The goal of this effort is to monitor and manage a hybrid stand-alone photovoltaic (PV) and wind energy system (WES) using the Internet of Things (IoT). The suggested hybrid system uses Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) and Perturb and Observe (P&O)-based Sliding Mode Control (SMC) approaches. The cost-effective Arduino Uno board in Matlab is used to analyze the P&O and INC MPPT methods. Energy from renewable sources is stored in a battery, and the output voltage of each source is monitored using the blynk app and GSM 800c module. Simulation results validate the controller’s operation, and the performance of both MPPT algorithms is compared. Experimental outcomes demonstrate the effectiveness of the IoT-based controller and its characteristic functionalities. Overall, this proposed hybrid PV and WES configuration offers advantages such as reduced human resources, cost-effectiveness, time savings, enhanced reliability, and improved data collection and control capabilities.