Search

Uncertainty, external disturbance, and time delay present challenges to system stability, and the controllability of the settling time in existing control methods is limited, thus limiting their applicability in certain specific scenarios. To guarantee superior dynamic performance and stability, this paper further explores the predefined-time synchronization of uncertain time-delay hyperchaotic systems. Firstly, a novel sliding mode function is proposed, ensuring the synchronization error converges to the equilibrium point within a predefined time. Then, a suitable sliding mode controller is constructed so that the trajectories of the system state can be driven to the sliding mode surface within a predefined time. Secondly, based on the Lyapunov theory, sufficient conditions for its reachability and stability are given, and the effectiveness of the proposed strategy is verified by numerical simulation. In comparison, the proposed strategy exhibits a faster convergence rate, lower controller energy consumption, less chattering and strong robustness. The upper bound of the settling time can be flexibly set according to requirements. Finally, the effectiveness of the proposed strategy is further confirmed through an application example involving image encryption. [ABSTRACT FROM AUTHOR]

This article addresses robust output regulation for systems affected by disturbances generated by an uncertain exosystem as well as matched external disturbances. The robustness of the feedback loop is achieved by combining internal model based control with sliding mode control, resulting in a structurally simple controller. The design of the proposed controller is presented first for the full information problem, that is, the disturbances generated by the exosystem and the state‐information is available for the control algorithm. This requirement is relaxed in the second step of the controller design, where the observer‐based robust output feedback‐loop structure is developed. Results from a comparative simulation study are presented to illustrate the advantages and the effectiveness of the proposed controller concept. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

In this work, an adaptive fast terminal sliding mode control (AFSMC) approach based on joint torque estimation and friction compensation is proposed to enhance the trajectory tracking accuracy of robotic manipulators under variable load conditions. The joint torque estimation utilizes an improved harmonic drive compliance model and adaptive low‐pass filtering, and friction compensation employs a hybrid model accounting for velocity and load torque effects. These compensations reduce the upper bound of the uncertainty, while AFSMC further reduces dependency on upper uncertainty bounds and minimizes the chattering. The stability analysis using the Lyapunov method confirms the effectiveness of this approach. Experimental results demonstrate that the proposed controller achieves smaller root mean square and maximum error of trajectory tracking, thus significantly improving trajectory tracking accuracy under variable load conditions. [ABSTRACT FROM AUTHOR]

Path tracking plays a critical role in autonomous driving for autonomous ground vehicle (AGV). However, AGV faces challenges in accurate tracking and chatter reduction due to external disturbances, making it difficult to meet the tracking performance requirements. Currently, sliding mode control (SMC) and disturbances observer are primarily employed for disturbance estimation. However, ensuring finite‐time robust control remains a significant challenge. To ensure rapid convergence of tracking errors and effective disturbance rejection, this paper proposed a novel non‐singular fast terminal sliding mode (NFTSM) control scheme based on finite‐time disturbance observation (FDO). First, a novel NFTSM controller based on AGV dynamic model is developed to achieve fast convergence of tracking errors. Then, to mitigate disturbances effects and suppress chatter, an innovative FDO method is employed. Finally, based on FDO, the NFTSM‐FDO establishes a control scheme that enhances disturbances suppression and accelerates convergence. The simulation and experimental results demonstrate the innovation of the proposed method. Compared with other SMC methods, the results validate the effectiveness and advantages of the proposed approach, exhibiting fast convergence and superior tracking performance. [ABSTRACT FROM AUTHOR]

A neural network adaptive integral terminal sliding mode control method with input saturation is proposed for the horizontal vibration problem of high‐speed elevator car systems caused by uncertainties such as guideway excitation and shaft piston wind change. First, considering the input saturation problem existing in the elevator control actuator, a class of smooth functions is introduced to approximate the nonlinearity of switching saturation, and an eight‐degree‐of‐freedom asymmetric anti‐saturation nonlinear system model of the high‐speed elevator car is established; second, in order to solve the singularity problem existing in the terminal sliding‐mode control, a nonlinear term is introduced into the sliding‐mode design, and a neural network is utilized for the fitting of the complex unknown function, and the design of the an adaptive integral terminal sliding mode controller (AITSMC), which enables the state variables of the system to achieve finite time convergence and proves the stability of the system by using Lyapunov theory; finally, under the action of two typical guide excitations, the proposed controller is compared with the passive control and adaptive control (AC), and the results show that, after adopting the proposed control method, the vibration acceleration eigenvalue is reduced by more than 60%, which effectively suppresses the horizontal vibration of the car system and verifies the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This article investigates the fixed‐time rotating consensus problem of second‐order multi‐agent systems in both the leaderless and leader‐following cases. Specifically, in the leaderless case, a distributed controller is developed to drive all agents to reach rotating consensus in fixed‐time. In the leader‐following case, a distributed fixed‐time observer is first proposed to estimate the position of a rotating leader. Then, a local fixed‐time output feedback controller without any velocity measurements is proposed to achieve the leader‐following motion. Furthermore, an integral sliding mode control technique is applied to handle the case where the multi‐agent system is subject to time varying external disturbances. Based on the bi‐limit homogeneity method and Lyapunov theory, we prove that all the agents reach the rotating consensus within a fixed time independent of initial conditions. Finally, simulations illustrate the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

This work introduces a new actuator fault estimation approach coupled with a fault‐tolerant control (FTC) strategy for uncertain systems in an output feedback framework. The proposed method involves constructing a Multi‐Layer Neural Network (MLNN) observer‐based fault estimation unit to accurately predict system states and potential faults in the actuator channel. An online control allocation (CA) scheme is then developed, utilizing the derived estimates to actively reconfigure the virtual control signals among the healthy redundant actuators in the event of actuator malfunction. Furthermore, an adaptive neural network‐based output integral sliding mode control scheme is designed based on the virtual control. This integration enhances the overall system's robustness and significantly reduces the chattering effect. The stability analysis of the proposed fault estimations scheme is initially performed using MLNN structure, followed by a comprehensive closed‐loop stability analysis to establish the stability of the entire system. Finally, the effectiveness of the proposed method is validated on a nonlinear six‐degree‐of‐freedom model of multirotor unmanned aerial vehicle aircraft. Numerical simulations under different fault and failure scenarios validate the efficacy of the proposed method. The comparative analysis of the proposed scheme is conducted with the static output feedback control allocations and adaptive allocation strategy. This analysis focuses on evaluating performance using metrics such as root mean square error and mean square deviation, particularly in the presence of faults and failures. The results demonstrate the superior performance of the proposed scheme in fault/failure conditions. [ABSTRACT FROM AUTHOR]

The major contribution of this study is the feedback design of a finite-time convergence sliding mode control to solve the trajectory-tracking problem in a class of mechanical systems. Some advantages are that the controller presents a continuous signal by integration of the high-frequency switching term. Another benefit is the design and implementation of an uncertainty and disturbance estimator (UDE) to robustify the closed-loop system. We use Lyapunov tools to develop the closed-loop stability analysis and to give an expression of the convergence time t = t through this, we can reduce the convergence time by tuning the gains of the controller. We illustrate the performance of the proposed control structure via numerical simulations conducted for a mass-spring-damper system and experiments developed in a pendular system. [ABSTRACT FROM AUTHOR]

This paper presents a joint sliding mode control algorithm with fuzzy adaptive gain to address the problem that the lateral stability of distributed drive electric vehicles is affected by system parameter perturbation and external environment disturbances under steering conditions. The control system is designed by considering the influence of road conditions and tire nonlinearity, taking the yaw rate and sideslip angle as control variables. The difference between the expected value and the actual value of the control quantity is taken as the input to obtain the expected front-wheel angle for feedback correction. Aiming at the problem that it is difficult to obtain the critical driving state parameters of vehicles and to directly measure the road adhesion coefficient which affects the vehicle's lateral stability, this paper presents a simplified unscented Kalman filter observer which is designed to dynamically estimate the vehicle state parameters and road adhesion coefficient for the lateral stability controller. Based on CarSim and MATLAB/Simulink, a co-simulation model is developed and verified under different working conditions. The results reveal that the proposed lateral stability control algorithm effectively reduces the front wheel steering angle, improving the vehicle's handling stability while reducing the driver's operating burden and improving driving safety. [ABSTRACT FROM AUTHOR]

An event-triggered-super twisting sliding mode control (ET-STSMC) with saturation function in reaching law have been designed for a nonlinear Quadcopter model with bounded disturbance and its performance is compared with Event Triggered-Sliding mode control (ET-SMC). Simulation results have been obtained for altitude and attitude tracking, demonstrating the stability of the closed-loop system with the proposed control. The event-triggering conditions are derived based on the Lyapunov method, ensuring non-accumulation of inter-event execution time. Experiments have been performed in real-time to analyse the robustness and computational cost in terms of the number of control updates of the proposed control strategy under normal flight, external disturbances, and parameter uncertainty. Simulation and experimental results show that ET-STSMC can achieves better tracking performance and robustness with reduced computational cost compared to ET-SMC during all flight conditions. [ABSTRACT FROM AUTHOR]

In this research, we present a dynamic high gain observer (HGO) combined with a sliding mode controller (SMC) for a novel shape memory alloy (SMA) actuator. The dynamic model of the SMA actuator contains nonlinearities with hysteresis, which makes the estimation of velocity and acceleration of the actuator challenging. We first design a dynamic HGO to estimate velocity and acceleration of the SMA actuator by considering nonlinearities with hysteresis in the dynamics. We then develop a SMC for the actuator using the estimated velocity and acceleration. The proposed SMC in conjunction with the dynamic HGO is tested experimentally for the actuator. For comparison, trajectory tracking experiments are also conducted by using PID without an observer, SMC without an observer, and SMC with a non-dynamic HGO. Our results confirm that the dynamic HGO combined with SMC can enhance trajectory tracking accuracy while reducing the chattering phenomenon. [ABSTRACT FROM AUTHOR]

This paper proposes a dual-output DC–DC power conversion system based on Photovoltaic (PV) technology. PV panels are connected to a series compensated Buck-Boost Converter (SCBBC) to harvest solar energy, while a sliding mode controller (SMC) ensures maximum power point tracking (MPPT). During the intermediate phase, a synchronized Buck-Boost Converter (SBBC) topology is used to ensure effective charging and discharging of batteries. Additionally, a PI-SMC hybrid control strategy is applied at the back end to the Super Lift Luo Converter (SLLC) to maintain the load voltage at a desired value. A Gravitational Search Algorithm (GSA)-based PI controller controls the input current, while the output voltage is controlled by the outer loop (SMC). We use a single-loop SMC approach to validate the performance of the proposed dual-loop control scheme. According to the presented results, the dual-loop control scheme demonstrated higher dynamic performance in controlling input current and output voltage. [ABSTRACT FROM AUTHOR]

This study introduces a novel control approach for a twin rotor multi-input multi-output system (TRMS), specifically targeting the pitch and yaw movements. The proposed method employs a sliding mode controller (SMC) with variable gains, aiming to overcome limitations like chattering and excessive control effort. Unlike traditional controllers, the gains here dynamically adjust based on the error state, enhancing the robustness of the system against external disturbances and parameter uncertainties. The control algorithm draws inspiration from both first-order and higher-order sliding mode controllers. To rigorously assess the robustness of the controller, Gaussian White noise is incorporated into the model. By dynamically adjusting gains, the proposed approach aims to minimize control effort while mitigating control signal overestimation arising from model uncertainties. Furthermore, stability analysis confirms that the operating point of the closed-loop system converges within a finite time. The effectiveness of this novel controller is validated through simulations using the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

This study investigates the issue of vehicle platoon control for nonlinear heterogeneous vehicle platoon systems containing a leader and several followers subject to unknown uncertainties and disturbances. Platoon control has been shown to effectively achieve the consensus of vehicles, increase road capacity, and enhance traffic safety. Achieving that the vehicle platoon maintains a desired inter-vehicle spacing and reaches the velocity consensus is the main objective of platoon control. To achieve vehicle consensus and avoid collisions, the new distributed cooperative sliding mode control protocols are proposed for the heterogeneous platoon to ensure the convergence of vehicle spacing errors and velocity errors and to guarantee string stability. The spacing policy and information flow topology are introduced within the development of the platoon control strategies. Furthermore, the novel distributed neural adaptive control strategies utilizing the nonsingular updating method are developed to address the problem of the unknown uncertainties and heterogeneities in the platoon vehicles. The proof of the ultimate boundedness of the spacing and velocity errors is carried out by utilizing the Lyapunov theory. The analysis of string stability is conducted to confirm the effectiveness of the vehicle platoon control strategies. Finally, the correctness and efficacy of the control strategies can be verified through a numerical example. [ABSTRACT FROM AUTHOR]

This paper considers real-time parameter variations of dish Stirling solar thermal system (DSTS) and combined solar parabolic trough-thermal power system (HTP)-based hybrid power system pertaining to frequency containment. A maiden attempt has been made by considering a detailed modelling of variable speed DSTS system for load frequency control (LFC), which shares the total load along with a battery energy storage system (BESS) and HTP in the proposed hybrid power system. Frequency oscillations resulting from the variations in load demand and/or power output variation of DSTS due to intermittent solar insolation in the hybrid power system needs to be contained employing an appropriate technique. To this end, a novel tilt integral-sliding mode controller (TISMC) optimized by improved African vulture optimization algorithm (IAVOA) has been introduced. Improvement in the existing AVOA has been made by introducing a joint opposite selection (JOS) operator, which shows better performance in exploitation and exploration phases of minimizing frequency error. The performance of the proposed controllers is compared with proportional (P), proportional-integral (PI), proportional-integral-derivative (PID) and proportional-integral-Sliding mode controller (PISMC) for LFC. Finally, performance of the proposed technique is validated in real-time system using OPAL-RT OP4510. From the MATLAB simulation and OPAL-RT results, it has been observed that the IAVOA-based TISMC is the best controller for controlling frequency deviations of the proposed hybrid power system. [ABSTRACT FROM AUTHOR]

In this paper, attitude tracking control with arbitrary convergence time for rigid spacecraft is considered. First, a novel time-varying sliding function is proposed to achieve free-will arbitrary time convergence when the system states reside on the sliding surface. With such a sliding function, an attitude tracking controller is designed to guarantee that the states of the closed-loop system converge to the sliding surface within a predetermined time in the presence of external disturbances. The free-will arbitrary time convergences of the closed-loop system and sliding function are illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

Renowned for their adeptness in smoothing current flow and maintaining balanced operation, 2-phase interleaved boost converters (IBC) demonstrate remarkable efficiency, especially when confronted with demanding loads. This makes them a preferred choice for high-power applications such as renewable energy systems, high-power supplies, and electric vehicle power trains. In contrast, standard boost converters are typically favored in low-power, low-demand scenarios. The control of a 2-phase IBC involves running two boost converters in parallel but with a phase shift to reduce ripple currents, improve efficiency, and increase power handling capabilities. To ensure stability and optimal performance, the control strategies for these converters focus on achieving balanced operation between the phases. Hence, the control of 2-phase IBC presents a significant challenge due to their non-minimum phase behavior. The core focus of this article is the implementation of a composite model predictive control (MPC) technique to regulate a 2-phase interleaved boost converter. It introduces a novel approach, model predictive sliding mode control (MPSMC), which leverages the strengths of both MPC and sliding mode control (SMC). The benefits of this hybrid method, termed MPSMC, are thoroughly developed and simulated using MATLAB/Simulink. The results, as discussed in the respective section, provide an in-depth understanding of its effectiveness in practical applications. [ABSTRACT FROM AUTHOR]

Synchronous reluctance motor (SynRM) has been a hot research topic in recent years. In this paper, a composite speed controller based on the concept of super-twisting sliding mode (STSM) control is designed and innovatively applied to SynRM. For current control, the maximum torque per ampere (MTPA) strategy is used. For torque control, a design method based on an STSM controller is given. In order to solve the chattering phenomenon existing in STSM, a simple structure disturbance observer (DOB) is further introduced as a feed-forward compensation to offset the disturbances. A novel composite sliding mode speed controller is formed based on DOB and STSM. By using Matlab/Simulink, a composite sliding mode speed control system was built. The characteristics of the motor such as current, speed, and torque were researched. Compared to the STSM controller, the speed overshoot of the new controller is reduced by up to 50% (for no-load start). The speed drop is reduced by up to 75% (for sudden load), and the recovery time is shortened by up to 50%. The results show that the designed composite speed control system has better dynamic performance. [ABSTRACT FROM AUTHOR]

To solve the problem of poor control performance of internal permanent magnet synchronous motors (IPMSM) due to parameter perturbations and external perturbations when adopting mode-free sliding mode control (MFSMC) algorithm, a double-closed-loop model-free super-twisting terminal sliding mode control (MFSTTSMC) algorithm of IPMSM based on third-order super-twisting observer (TOSTO) is proposed. Firstly, according to the new model-free control (MFC) algorithm, an ultra-local expansion model of IPMSM speed-current double closed-loop is established. Secondly, based on the ultra-local expansion model, a double closed-loop MFSTTSMC is designed to achieve global rapid convergence of system state errors. At the same time, a TOSTO is designed to estimate the disturbance in real time and carry out feedforward compensation, which enhances system robustness. Finally, the viability and superiority of the proposed control algorithm is demonstrated through simulation and experiments. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel robust nonlinear optimal second-order sliding mode controller using the homotopy perturbation method (RNOSOSMC-HPM) to maximize wind power capture and minimize the mechanical stress on the drive train. To design the nonlinear optimal controller, the homotopy perturbation method (HPM) is applied to compute the approximate solution of the partial differential Hamilton-Jacobi-Bellman (HJB) equation. Next, the nonlinear optimal controller is combined with a second-order sliding mode controller to create robustness and eliminate chattering. The RNOSOSMC-HPM controller can provide safe wind turbine operation under uncertainties and create a good trade-off between maximizing the wind power captured and attenuating the mechanical loads by minimizing the control input. To investigate the effectiveness of the presented the RNOSOSMC-HPM controller, we compare the results of the proposed method with some existing control schemes in two different scenarios. The results indicate that the RNOSOSMC-HPM controller furnishes desired responses. [ABSTRACT FROM AUTHOR]

This work studies the sliding mode control (SMC) of semi-Markov switching systems (S-MSSs) with time delay in discrete domain. The time delay is first considered in studying discrete S-MSSs with SMC strategy. Owing to their excellent engineering background and advantages in complex system modeling, S-MSSs have a wide range of application prospects. By virtue of the delay-dependent Lyapunov-Krasovskill functional and the probability form of semi-Markov switching signal, a novel convex mean-square stability of the underlying system is provided through a new set of less conservative linear matrix inequalities and suitable semi-Markov conditions. Furthermore, an appropriate delayed SMC mechanism is built to drive the states onto the quasi-sliding mode and remain there for all subsequent time. Finally, an electronic throttle model is presented to validate the availability of the proposed method. [ABSTRACT FROM AUTHOR]

A proposed approach for efficient energy management for lithium-ion battery and supercapacitor hybrid energy storage system is outlined in this study. The primary aim is to ensure the electric vehicle receives a stable and high-quality supply of electricity. The suggested management strategy focuses on maintaining the bus voltage at a consistent level while meeting the varying load demands with high-quality power across different scenarios. To achieve this, a management controller is employed, which utilizes a metaheuristics technique to define the parameters of the integral sliding mode control. The supercapacitor units are responsible for controlling the direct current (DC) bus, while the lithium-ion battery plays a role in balancing power distribution on the common line. This study evaluates the potential benefits of integrating salp swarm algorithm techniques into the controller's performance. The findings of the study suggest combining metaheuristic optimization methods with integral sliding mode control. Can lead to improvements in power quality. The proposed management algorithm not only efficiently allocates power resources but also safeguards them, ultimately ensuring a consistent and high-quality power supply for the electric vehicle. [ABSTRACT FROM AUTHOR]

ABSTRACT This article investigates a satellite sun‐safe controller based on a super‐twisting disturbance observer (STDO) with interval analysis. First, a variable gain sliding mode control (SMC) algorithm is proposed to ensure that the satellite can achieve a fixed‐axis rotation and sun‐pointing attitude. The controller gains are adjusted according to the disturbance estimation value and the interval of the disturbance estimation error. The important feature of the adaptation algorithm is in non overestimating the values of the control gains. To achieve the purpose of non‐overestimating, a STDO is constructed to estimate the unknown disturbance. Additionally, the interval of the disturbance estimation error is obtained by interval analysis to update the controller gain in real time. Then, the stability and convergence of the closed‐loop system, including the variable gain sliding mode controller and the super‐twisting observer, are verified by using the Lyapunov theory. Finally, hardware‐in‐the‐loop (HIL) experimental results demonstrate that the proposed method not only performs better in terms of convergence and accuracy than the state‐of‐the‐art sun‐safe controller design method but also achieves more negligible chattering in the presence of disturbance torque compared to the fixed gain SMC method. [ABSTRACT FROM AUTHOR]

ABSTRACT This article introduces a third‐order super‐twisting sliding mode control (Gen‐STSMC) algorithm designed for the secure operation of a grid‐connected photovoltaic (PV) system. The improved method changes the traditional super‐twisting sliding mode control (STSMC) technique by incorporating both a linear term and a higher power term to reduce convergence time and chattering effects. This strategy generates the optimal control signals to regulate the output power of the PV system by compensating the state‐dependent uncertainties using the linear and growing term. The controller's stability analysis is conducted to demonstrate its rapid convergence compared to PI and conventional STSMC scheme. A comparative simulation study against PI and STSMC is conducted to showcase the controller's rapid convergence and robust performance in various grid‐connected PV system scenarios. Experimental tests are also performed to validate the controller's effectiveness in maintaining stable power generation in the presence of environmental fluctuations and DC link voltage variations. [ABSTRACT FROM AUTHOR]

Although widely used in industrial applications, strong nonlinearity and coupling, high computational complexity prevent high precision tracking control of manipulator. In this paper, to overcome the rely on system model and achieve prescribed convergence, a novel hybrid observer‐based model‐free adaptive high‐order fast terminal sliding model control scheme (HO‐MHTSMC) with prescribed performance is proposed for trajectory tracking control of robot manipulators in the existence of friction and external disturbance. The ultra‐local model is used to approximate the original complex system in a model free form in a short sliding time window, which avoid the accurate modeling of the manipulator system. To compensate for the lumped uncertainties, a hybrid observer based on adaptive time‐delay estimation and adaptive second order sliding mode observer (SOSM) is proposed to achieve finite‐time observation and zero estimation error. Besides, a transformation using prescribed performance function is applied to the system to ensure the transient and steady‐state performance of the trajectory tracking in joint space. Furthermore, a high‐order fast terminal sliding mode control algorithm with backstepping control strategy is used to stabilize the whole system and reduce the chattering problem in conventional sliding mode control. The stability analysis of the system is provided by Lyapunov theorem. Finally, numerical study and co‐simulations show that the proposed control scheme has better performance in tracking accuracy and robustness compared with conventional control schemes. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a prescribed performance model‐free adaptive platooning sliding mode control (PP‐MFAP‐SMC) problem for the nonlinear vehicular platooning systems (VPSs) under denial‐of‐service (DoS) attacks is studied. Firstly, the partial form dynamic linearization (PFDL) technique is employed to convert the nonlinear VPSs into an equivalent linear data model, in which the nonlinear features of the VPSs are compressed into an unknown time‐varying pseudo gradient (PG) vector. Then, an observer is devised to acquire the estimation value of the unknown time‐varying PG vector. To lower the complication of the design, the constrained tracking error is converted into the unconstrained one. Based on which, the sliding mode control (SMC) strategy is proposed to enhance the robustness of the VPSs. Further, a PP‐MFAP‐SMC algorithm with an attack compensation mechanism is developed to ensure that the vehicular tracking errors of the position and velocity can converge to the predefined regions, respectively. Eventually, the effectiveness of the developed algorithm is demonstrated by an actual VPS with the comparisons. [ABSTRACT FROM AUTHOR]

Summary: The primary objective of this paper is to enhance the efficient utilization of communication resources. To achieve this, the paper delves into the disturbance observer based adaptive heading control strategy for Unmanned Marine Vehicles with event‐triggered and input quantization. Furthermore, in order to mitigate the impact of slow time‐varying external disturbances within the control system, the disturbance observer is employed for estimation. Within the context of a networked control, control input is subjected to quantization via an input quantizer, and the process of input quantization is described by using a linear analytical model. Importantly, no foreknowledge of quantization parameters is necessary for the quantized feedback controllers. Subsequently, the sliding mode control method is combined with event‐triggered mechanismss to design quantization feedback control system. The stability of the closed‐loop system is established in line with the fundamental tenets of Lyapunov stability theory, validating the bounded nature of both observation and heading tracking control errors. The effectiveness of the proposed heading control scheme is further underscored through a series of simulation experiments. [ABSTRACT FROM AUTHOR]

Modular multilevel green converter based high voltage direct current (MMC‐HVDC) transmission system has become a practical solution to interconnect renewable energy sources to main AC grids. Connecting the MMC to a weak AC system is still a challengeable problem. This paper proposes a sliding mode control‐based method for the MMC. By considering short circuit ratio parameter of the AC grid as uncertainty, a suitable mathematical model is developed. Also, relations among control parameters and their validity conditions are obtained. The proposed control scheme has faster dynamic responses to uncertainty and external disturbances compared to the conventional vector current control method with proportional–integral controller. At last, simulation results in the MATLAB/SIMULINK software environment are presented that the proposed control scheme is effective. [ABSTRACT FROM AUTHOR]

This paper presents Super Twisting Sliding Mode Control with a novel Fuzzy PID Surface for improved trajectory tracking of quadrotor unmanned aerial vehicles under external disturbances. First, quadrotor dynamic model with six degrees of freedom (6-DOF) is developed using Newton-Euler Method. Then, a robust Sliding Mode Control based on a new Fuzzy PID Surface is designed to be capable of automatically adjusting its gain parameters. The proposed SMC controller applies super twisting algorithm with PID surface to reduce chattering and a fuzzy logic controller to automatically adjust the gain parameters in order to enhance robustness. Furthermore, the solution to stability has been given by the Lyapunov method. The controller's performance is tested through various trajectories, parameter variations, and disturbance scenarios, comparing it with recent alternatives such as Sliding Mode Control, Fuzzy Sliding Mode Control, and Fuzzy Super Twisting Sliding Mode Control using numerical simulations. The simulation results show that the proposed controller has better tracking performance, parameter variation handling, and disturbance rejection capability compared with the aforementioned controllers. Additionally, the control efforts of the proposed method are minimal and smooth, proving it to be an economically feasible controller and operationally safe for the quadrotor. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper introduces an innovative adaptive fixed‐time sliding mode control (SMC) method that eliminates chattering, enhancing trajectory tracking accuracy and robustness in nonlinear dynamical systems facing uncertainties and external disturbances. The proposed control scheme ensures fixed‐time convergence of system states to a predefined neighborhood around the origin, independent of initial conditions. An innovative adaptive tuning law is proposed to estimate the unknown upper bounds of synthetic uncertainties and disturbances without requiring prior knowledge. This law forces system states to trend to the sliding surface within a fixed time, achieving stabilization of tracking errors at the origin without undesirable chattering and while avoiding singularities. Comprehensive simulations and comparisons among four control strategies (C1, C2, C3, and C4) demonstrate that the proposed C1 control strategy outperforms others in terms of faster convergence speed, higher tracking accuracy, less chattering, and stronger robustness. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper proposes a novel finite‐time adaptive continuous robust control method for buck converters, combining dynamic sliding mode theory with a mismatched disturbance observer. While traditional sliding mode control can effectively manage matched disturbances, it often falls short when faced with mismatched disturbances, potentially compromising system performance. Our developed control strategy introduces a nonlinear sliding mode‐based disturbance observer and an adaptive continuous robust sliding mode control to guide state variables towards desired values. To mitigate the chattering phenomenon, the proposed controller incorporates a super‐twisting algorithm, ensuring continuous control command behavior. We conducted a rigorous finite‐time stability analysis of the control procedure using Lyapunov theory. Furthermore, comprehensive experimental results demonstrate that our proposed control method significantly reduces disturbance effects and enhances the buck converter's performance in terms of robustness and accuracy. [ABSTRACT FROM AUTHOR]

ABSTRACT Aiming 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. [ABSTRACT FROM AUTHOR]

This study presents a new Maximum Power Point Tracking (MPPT) approach for solar photovoltaic (PV) systems, combining the Super‐Twisting Algorithm (STA) and Grey Wolf Optimizer (GWO). The STA‐GWO‐MPPT method improves efficiency in dynamic conditions by using STA for control and GWO for parameter optimization, enhancing stability and robustness. Performance evaluation is conducted through MATLAB/Simulink simulations and experimental validation on a small‐scale test bench. Various quantitative metrics, including rise time, settling time, power production, efficiency, root mean square error (RMSE), and standard deviation (STD), are employed for assessment. Results indicate significantly faster convergence speeds for the proposed method compared to conventional MPPT techniques. Specifically, the rise time for the proposed method is 0.0129 seconds, outperforming Fuzzy Logic Control (FLC) (0.2638 seconds) and Grey Wolf Optimizer with Sliding Mode Control (GWO‐SMC) (0.0181 seconds). Additionally, the proposed method exhibits superior tracking efficiency, with an average efficiency of 99.33%, surpassing FLC (96.93%) and GWO‐SMC (99.19%). Moreover, it reduces power fluctuations, with an RMSE of 7.819% and STD of 6.547%, compared to FLC (RMSE: 13.471%, STD: 4.519%) and GWO‐SMC (RMSE: 8.507%, STD: 6.108%). Overall, this study contributes valuable insights into enhancing MPPT efficiency in solar PV systems, with implications for both research and practical applications. [ABSTRACT FROM AUTHOR]

During the loading process, significant external position disturbances occur in the electro–hydraulic load simulation system. To address these position disturbances and effectively mitigate the impact of uncertainty on system performance, this paper first treats model parameter uncertainty and external disturbances as lumped disturbances. The various states of the servo valve and the pressures within the hydraulic cylinder chambers are then examined. Building on this foundation, the paper proposes a nonlinear multi-mode variable structure independent load port electro–hydraulic load simulation system that is tailored for specific loading conditions. Secondly, in light of the significant motion disturbances present, this paper proposes an integral sliding mode active disturbance rejection composite control strategy that is based on fixed-time convergence. Based on the structure of the active disturbance rejection control framework, the fixed-time integral sliding mode and active disturbance rejection control algorithms are integrated. An extended state observer is designed to accurately estimate the lumped disturbance, effectively compensating for it to achieve precise loading of the independent load port electro–hydraulic load simulation system. The stability of the designed controller is also demonstrated. The results of the simulation research indicate that when the command input is a step signal, the pressure control accuracy under the composite control strategy is 99.94%, 99.86%, and 99.76% for disturbance frequencies of 1 Hz, 3 Hz, and 5 Hz, respectively. Conversely, when the command input is a sinusoidal signal, the pressure control accuracy remains high, measuring 99.94%, 99.8%, and 99.6% under the same disturbance frequencies. Furthermore, the simulation demonstrates that the influence of sensor random noise on the system remains within acceptable limits, highlighting the effective filtering capabilities of the extended state observer. This research establishes a solid foundation for the collaborative control of load ports and the engineering application of the independent load port electro–hydraulic load simulation system. [ABSTRACT FROM AUTHOR]

Power cyber–physical systems such as multi-area power systems (MAPSs) have gained considerable attention due to their integration of power electronics with wireless communications technologies. Incorporating a communication setup enhances the sustainability, reliability, and efficiency of these systems. Amidst these exceptional benefits, such systems' distributed nature invites various cyber-attacks. This work focuses on the equal power sharing of MAPSs in the event of false data injection (FDI) attacks. The proposed work uses a sliding mode control (SMC) mechanism to ensure timely detection of challenges such as FDI attacks and load change, making MAPSs reliable and secure. First, a SMC-based strategy is deployed to enable the detection and isolation of compromised participants in MAPS operations to achieve equal power sharing. Second, time-varying FDI attacks on MAPSs are formulated and demonstrate their impact on equal power sharing. Third, a robust adaptive sliding mode observer is used to accurately assess the state of the MAPS to handle state errors robustly and automatically adjust parameters for identifying FDI attacks and load changes. Lastly, simulation results are presented to explain the useful ability of the suggested method. [ABSTRACT FROM AUTHOR]

To address the issue of uncertainty in the occurrence time of voltage sags in power grids, which affects power quality, a voltage state prediction method based on LSTM neural networks is proposed for predicting voltage states. For the problem of quickly and accurately compensating for voltage sags, a DVR system based on a new approach law of sliding mode variable structure control is proposed, which significantly reduces chattering, improves response speed, and enhances the robustness of the system. The stability of the system is proven based on Lyapunov stability theory. Simulation experiments are conducted to analyze the voltage state prediction effect based on the LSTM neural network and the compensation effect of the novel reaching law of sliding mode variable structure control under different levels of voltage sag, validating the effectiveness and correctness of the proposed solution. [ABSTRACT FROM AUTHOR]

In this paper, a robust bumpless transfer control scheme for tracking control is proposed to avoid large jumps in the control signals for a switched system (SS) with unmatched uncertainty and disturbance. The robust bumpless controller comprises a robust linear feedback control (RLFC) and a continuous sliding mode control (CSMC) based on the given robust integral sliding mode (RISM). The RLFC meets the requirement of bumpless indices, and the CSMC suppresses the unmatched uncertainty and disturbance. First, the RLFC design is proposed, and the linear feedback coefficients satisfy the bumpless indices, despite the uncertainty and disturbance. Then, a RISM surface design is proposed, in which the uncertain SS satisfies the given H-infinity robust performance index, and can resist the unmatched uncertainty. Consequently, the CSMC ensures that the RISM surface can be reached in finite time from the initial time instant. By composing the CSMC with the RLFC, the control scheme achieves the robust trajectory tracking and the suppression of the control signal bumps during switching. Finally, the proposed robust bumpless transfer control scheme was applied to the different examples, and the simulation results verified its effectiveness. [ABSTRACT FROM AUTHOR]

In this article, the stabilization of coupled time fractional parabolic partial differential equations subject to external disturbances is investigated. By using sliding mode control method and backstepping approach, a boundary state feedback controller is designed to reject the matched disturbance and achieve the Mittag‐Leffler input‐to‐state stability of closed‐loop system. The existence of the generalized solution to the closed‐loop system is proven by Galerkin approximation scheme. Simulations are presented to illustrate the validity of our theoretical results. [ABSTRACT FROM AUTHOR]

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Recently renewable energy such as a photovoltaic (PV) system has been utilized more and more since it is pollution-free and permanent. To maintain the PV system functioning at, or near, the peak power point of the PV panel under different conditions such as fluctuating solar irradiation, temperature, and other factors, maximum power point tracking algorithms are required. In this study, a novel hybrid robust intelligent controller for a photovoltaic system is proposed. Three loops are used for creating the proposed controller, ensuring the controller's robustness. The first loop's objective is to locate the photovoltaic system's highest power spots. In the second loop, a novel fractional-order sliding model observer based on deep reinforcement learning optimization approach is proposed as a result of the design of a reliable controller under the lumped uncertainty in the system. Designing a novel back-stepping fast non-singular terminal fractional-order sliding mode controller is achieved at the final step. This method offers a nice transition response, a small tracking error, with a quick response to changes in solar radiation. Numerical analysis shows that the performance of the photovoltaic system by the proposed controller has been able to increase the efficiency of the system significantly. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of bounded and unknown delay of a J-type thermocouple sensor on controlling a Shape Memory Alloy (SMA) actuated rotary actuator. To compensate for the delay, a nonlinear adaptive predictor is utilized, which predicts the exact temperature of the present moment using the output of the sensor. A robust sliding mode control is then designed to track the reference input, which is the rotation angle of the pulley. In addition to temperature estimation, the inner system identification algorithm of the predictor identifies the heat transfer coefficients of the experimental setup. Experimental tests demonstrate the precise control of the proposed algorithm. The tracking error of the adaptive predictor with sliding mode control is compared to that of a regular sliding mode controller without temperature delay compensation consideration, showing the superior performance of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach utilizing a sliding mode controller to control a quadrotor effectively in the presence of structural faults. While previous research has extensively explored fault-tolerant control for UAVs, particularly addressing faulty actuators and sensors, there remains a significant gap in addressing control methods for quadrotors experiencing structural faults. We focus specifically on scenarios where a fault in one of the quadrotor's rotors diverts thrust from the vertical axis, complicating traditional control methods. Our proposed method involves two key steps: firstly, identifying the fault vector using a terminal sliding mode observer, and secondly, calculating appropriate control inputs using a sliding mode method based on the estimated fault vector. Simulation results demonstrate the robustness of this approach, showing accurate control performance even in the presence of multiple faults and disturbances. The system's reliability hinges on the convergence of the disturbance observer's estimation error to zero within a finite time frame. In conclusion, the developed controller offers a dependable solution for safely controlling a faulty quadrotor amidst high nonlinearity and uncertainty. [ABSTRACT FROM AUTHOR]

ABSTRACT This 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. [ABSTRACT FROM AUTHOR]

ABSTRACT The problem of air feed system control with guaranteed prescribed performance and fixed time control is investigated for proton exchange membrane fuel cell (PEMFC). First of all, the original model of PEMFC air feed system is converted to fully actuated system using higher order fully actuated system (HOFAS) approach. A fixed time extended state observer (ESO) is employed to approximate the cathode pressure. The parameter uncertainty is compensated by an adaptive radial basis function neural network (RBFNN). Then a prescribed performance sliding mode controller is designed with fixed convergence time. The proposed control law could guarantee the prescribed transient response for oxygen excess ratio (OER) error under stack current changing and bounded uncertainty. Lyapunov approach is utilized to proof fixed‐time stability of proposed controller. Simulation results of the study tests illustrate that the presented controller is efficient under constant OER tracking control, constant OER tracking control with parameter perturbation, and variable OER tracking control, respectively. [ABSTRACT FROM AUTHOR]

One‐dimensional thrust vectoring turbojet vertical takeoff and landing (VTOL) aircraft have attracted research attention due to their high thrust‐to‐weight ratios and their solution for the slow speed response of turbojet engines. However, there are some uncertainties and physical limitations in their systems, such as external disturbances, unknown parameters and input saturation. To improve the accuracy and convergence speed of trajectory tracking, a fixed‐time control method that is robust to saturation is proposed. The system dynamics are established, and an auxiliary system is built within a fixed time control framework to address the influence of input saturation and increase the error convergence rate. Nonsingular fast terminal sliding mode technology is combined with a few adaptive laws to ensure the robustness of the closed‐loop system against dynamic uncertainties and improve the precision of steady‐state control. The stability of the control system is proven based on Lyapunov, and the controller parameters are optimized based on particle swarm optimization (PSO). The proposed method based on fixed‐time stability guarantees that the states of the closed‐loop system can reach the residual set around zero within the designed time, and an expression for the upper bound on the convergence time is given. Finally, numerical simulations demonstrate the superiority of the proposed method based on the error integral criterion. [ABSTRACT FROM AUTHOR]

A new control approach based on fuzzy sliding mode control (FSMC) is proposed to regulate the chaotic vibration of an axial string. Hamilton's principle is used to formulate the nonlinear equation of motion of the axial translation string, and the von Kármán equations are used to analyse the geometric nonlinearity. The governing equations are nondimensionalized as partial differential equations and transformed into a nonlinear 3-dimensional system via the third-order Galerkin approach. An active control technique based on the FSMC approach is suggested for the derived dynamic system. By using a recurrent neural network model, we can accurately predict and effectively apply a control strategy to suppress chaotic movements. The necessity of the suggested active control method in the regulation of the nonlinear axial translation string system is proven using different chaotic vibrations. The results show that the study of the chaotic vibrations of axially translating strings requires nonlinear multidimensional dynamic systems of axially moving strings; the validity of the proposed control strategy in controlling the chaotic vibration of axially moving strings in a multidimensional form is demonstrated. [ABSTRACT FROM AUTHOR]

In this work, a control strategy based on fuzzy sliding mode control (FSMC) is applied to effectively manage the large-amplitude chaotic vibrations exhibited by a simply supported beam. The analysis considers the nonlinear beam structure, which is subjected to an external load. Hamilton's principle is employed, and the equations of motion are derived for the studied structure. The 3rd Galerkin discretization is employed to derive the ordinary differential governing equation of the structure. A control strategy is presented to decrease the response of the obtained multidimensional system. The vibration of a one-dimensional system is compared with that of the derived multidimensional system. As shown throughout the study, a multidimensional nonlinear system of the structure must be considered for accurate dynamic estimation. By using the recurrent neural network (RNN) model, we can accurately predict chaotic motion and effectively apply control strategies to suppress chaotic motion. The efficacy and suitability of the employed control strategy have been demonstrated by controlling chaos in the beam's multidimensional system. [ABSTRACT FROM AUTHOR]

ABSTRACT To enhance the power quality of microgrid inverters and reduce the influence of changes in inductance parameters and external disturbances on the direct power control of the inverter system, a terminal sliding mode control strategy with a variable exponential power reaching law has been proposed. The designed new reaching law comprises a variable exponential term and an enhanced power term. The variable exponential term contains an arctangent function, and the power term coefficient is replaced by a function about the sliding mode. Therefore, the convergence rate can be adaptively adjusted based on different stages of the system, ensuring a faster rate of convergence throughout the process of approaching the sliding mode surface. To weaken the effects of changes in inductance parameters, a power disturbance observer is designed to estimate the internal disturbances induced by the filtered inductance in the system. Subsequently, a sliding mode control law containing disturbance observations is derived. Moreover, a variable exponential terminal sliding surface is designed to adjust the convergence rate of system errors on the sliding surface in stages, thereby enhancing the control performance of the system. The simulation results show that the new reaching law has faster convergence rate and better dynamic performance. The convergence speed of the system error can be accelerated by the designed variable exponential terminal sliding surface. The sliding mode control strategy with the variable exponential power reaching law is applicable to the power control system of three‐phase inverters in microgrids, thereby significantly enhancing the dynamic performance and robustness of the system. [ABSTRACT FROM AUTHOR]