Sliding Mode Control Technique Research Articles

Analysis of single phase ZSI fed PV system in weak grids using fractional order sliding mode control technique

Nowadays, Photovoltaic (PV) system’s contribution to the power grid is increasing immensely. The PV system is linked with power grid through one or more inverters and a power conditioning unit to ensure smooth power delivery while also maintaining system voltage and frequency stability. However, due to grid load expansion, weak power grids have emerged as the dominant one today. As a result, the voltage and frequency of the grid got distorted. It may cause serious damage to the entire system in some cases. A single phase ZSI with the proposed Fractional order SMC technique is used to address these issues. The single phase ZSI consists of only two power switches and perpetuates the voltage transfer ratio like full bridge inverter. It also corroborates the sharing of power, regulatesactivepower,voltage, frequency, reactive powerand alleviates the harmonics in current. The input voltage of inverter is boostedby using theshoot through state and it also improvesthe reliability of inverter. The execution of the single phaseZSI withproposed FOSMCtechnique is assessed in MATLAB/Simulink to bear out the magnificent features of the proposed FOSMC in weak grid.

Nonlinear prescribed performance sliding mode control of hypersonic vehicles

SummaryThis paper addresses the adaptive saturation prescribed performance control problem for air‐breathing hypersonic vehicles with parameter uncertainties and unknown external disturbances. First of all, different from the traditional performance function, a novel class of performance functions is presented without the initial state information, which does not require to reset parameters even if the initial velocity and altitude change. To ensure the successful design of the velocity controller and altitude controller, the constrained errors are transformed into the unconstrained errors by the projection technique. Secondly, the adaptive neural network and the sliding mode control techniques are combined to design the adaptive neural network sliding mode controllers, which guarantee that the velocity and altitude tracking errors can respectively approach the predetermined regions within the identical preset finite time. Finally, the effectiveness of the designed controllers is verified by an example with comparisons.

Sensorless fuzzy-sliding mode control of five phases permanent magnet synchronous motor using MRAS: in three different operating modes

This paper presents a comprehensive study on sensorless control techniques for five-phase permanent magnet synchronous motors (5P-PMSMs). To optimize the speed control performance of (5P-PMSM), which has more advantages than its counterpart three-phase PMSM system, we utilized a combination of fuzzy logic and sliding mode control techniques to optimize the proposed sliding mode control. Additionally, the Model Reference Adaptive System (MRAS) is employed to estimate the speed and rotor position of the 5P-PMSM to enhance the robustness and adaptability of the control system. The modelling of the machine, detailed with a robust nonlinear strategy based on the sliding control, is introduced to track the system until the desired sliding surface is achieved first. To guarantee that the tracking errors converge, the sliding mode control has a chatter due to the discontinuous term. To mitigate the drawback, the proposed control is designed by combining SMC with fuzzy logic, enhancing the performance in a steady state. Examining the control performance of the integrated control fuzzy-SMC with MRAS in different operating modes, including three tests in reversal speed operation, open phase fault mode, and the low-speed operating mode under load torque. The main aim is to assess and analyze the robustness and performance of the proposed control strategy. The stability of the overall control system is examined using the Lyapunov theorem and Popov’s theory analysis of MRAS observer stability. The simulation results of the suggested control displayed by MATLAB-Simulink illustrate the effectiveness and adaptability of the sensorless control scheme across different operating conditions, offering promising prospects for practical implementation in industrial applications.

An efficient and robust varying-parameter projection neural network for sparse signal reconstruction

Sparse signal reconstruction plays an important role in many practical applications, and therefore, many scholars strive to study its various effective (approximate) solution approaches, including some projection neural network models with finite-time or fixed-time convergence due to their parallel nature and convenience for hardware implementation. However, we experimentally find that noise has a significant influence on the convergence performance of these models. To overcome this problem, in this paper, we propose a new efficient varying-parameter projection neural network model (VPPNN) using the sliding mode control technique and a novel time-varying parameter for sparse signal reconstruction. Theoretical analysis shows that this new model not only has shorter fixed convergence time under certain conditions but also has noise-tolerance when compared to the existing projection neural network models. Numerical simulation experiments (via sparse signal/image reconstruction) are performed to illustrate the superiority of the new proposed model over the existing ones in terms of the convergence rate and robustness.

Stick–Slip Suppression in Drill String Systems Using a Novel Adaptive Sliding Mode Control Approach

A novel control technique is presented in this paper, which is based on a first-order adaptive sliding mode that ensures convergence in a finite time without any prior information on the upper limits of the parametric uncertainties and/or external disturbances. Based on an exponent reaching law, this controller uses two dynamically adaptive control gains. Once the sliding mode is reached, the dynamic gains decrease in order to loosen the system’s constraints, which guarantees minimal control effort. The proof of convergence was demonstrated according to Lyapunov’s criterion. The proposed algorithm was applied to a drill string system to evaluate its performance because such systems present variable operating conditions caused by, for example, the type of rock. The effectiveness of the proposed controller was evaluated by conducting a comparative study that involved comparing it against a commonly used sliding mode controller, as well as other recent adaptive sliding mode control techniques. The different mathematical performance measures included energy consumption. The proposed algorithm had the best performance measures with the lowest energy consumption and it was able to significantly improve the functioning of the drill string system. The results indicated that the proposed controller had 20% less chattering than the classic SM controller. Finally, the proposed controller was the most robust to uncertainties in system parameters and external disturbances, thus demonstrating the auto-adjustable features of the controller.

Nonlinear robust sliding mode - Backstepping hybrid control for WECS -theoretical design and experimental evaluation

This paper proposes a new contribution in the field of optimizing control techniques for wind systems to enhance the quality of the energy produced in the grid. Although the Sliding Mode control technique, whether classical or involving the use of artificial intelligence, has shown interesting results, its main drawback lies in the oscillation phenomenon commonly referred to as “chattering.” This phenomenon affects the accuracy and robustness of the system, as well as the parametric variation of the system. In this work, we propose a solution that combines two nonlinear techniques based on the Lyapunov theorem to eliminate the chattering phenomenon. It is a hybrid approach between the Backstepping strategy and the Sliding Mode, aiming to control the active and reactive powers of the doubly fed induction generator (DFIG) connected to the electrical grid by two converters (grid side and machine side). This hybrid technique aims to improve the performance of the wind system in terms of precision errors, stability, as well as active and reactive power. The proposed solution has been validated in the Matlab & Simulink environment to assess the performance and robustness of the proposed model, as well as experimentally validated on a test bench using the DSPACE 1104 card. The obtained results are then compared with other techniques, demonstrating a significant improvement in performance.

Fractional Order T–S Fuzzy Chaotic Models for Secure EEG Signal via a Wireless Communication Protocol Using a Disturbance Observer and Sliding Mode Control Technique

Fractional Order T–S Fuzzy Chaotic Models for Secure EEG Signal via a Wireless Communication Protocol Using a Disturbance Observer and Sliding Mode Control Technique

Adaptive neural predefined-time hierarchical sliding mode control of switched under-actuated nonlinear systems subject to bouc-wen hysteresis

For switched under-actuated systems subject to bouc-wen hysteresis, an adaptive neural predefined-time control scheme is presented first time in this paper. To improve the robustness and response rate of the system under consideration, a hierarchical sliding mode control technique is introduced. Based on a predefined-time stability criterion, the stabilization time of the system can be directly preset under the designed controller. Besides, the convergence time depends only on the preset value and is independent of all other parameters. The projection algorithm is introduced to avoid the singularity problem in the controller design process. Meanwhile, it is proved that all signals of the closed-loop system are bounded after a preset time through the Lyapunov stability theory. Finally, a simulation example and a comparison example are given to further illustrate the effectiveness and superiority of developed control approach.

Linear Parameter Varying Observer-Based Adaptive Dynamic Surface Sliding Mode Control for PMSM

This paper presents an adaptive dynamic surface sliding mode control technique to address the issue of system parameter changes in permanent magnet synchronous motor (PMSM) position servo systems. The proposed method involves adopting a linear parameter varying (LPV) observer-based parameter identification algorithm and adaptive control technique. Initially, a mathematical model of the PMSM is established, and the system parameters are divided into nominal and perturbation values. This allows for the reconstruction of the system model into a state space equation that incorporates the unknown perturbation parameters. To accurately estimate these unknown parameters, an LPV observer is designed based on the reconstructed model. Additionally, an adaptive dynamic surface sliding mode control technique is explored to achieve the desired tracking performance. Meanwhile, an exponential reaching law is introduced to expedite the dynamic behavior of the system and mitigate chattering. Finally, a suitable Lyapunov function is selected to ensure the overall stability of the system. The simulation results demonstrate the effectiveness of the parameter identification and control algorithm in achieving good identification and tracking control ability for PMSM systems.

Dynamic performance enhancement of nonlinear AWS wave energy systems based on optimal super-twisting control strategy

This paper presents a Super-Twisting Algorithm (STA) sliding mode control technique as an alternative to the conventional Proportional-Integral (PI) control system. This application is specifically in the context of a nonlinear Archimedes Wave Swing (AWS) device, which functions as a wave energy converter system (WECS) connected to the power grid. The main goal is dynamic performance enhancement of such wave energy systems under network disturbances. Two STA controllers areessential for the rectifier control system in the grid-connected system to capture the most power from waves while limiting losses in the AWS linear generator. In addition, four STA controllers are incorporated into the inverter control loop to preserve the DC link and common coupling voltages at the preset values. The Honey-Badger Algorithm (HBA) is applied for the optimization of gain parameters of the STA controllers, which are compared to the PI gains adjusted using the coot, the hybrid augmented grey wolf optimizer and cuckoo, and PSO search techniques to assess the worthiness of adopting this new control approach. The grid-connected AWS experiences a variety of faults, includingsymmetrical and unsymmetrical faults with successful and unsuccessful breaker reclosures. Finally, the system is experimentally validated using the OP4510 real-time simulator. The experimental results reveal that the HBA-STA controllers outperformPI controllers in omitting fluctuations in the regulated variables, making the STA a strong contender as a control method.

Barrier-Function-Based Adaptive Fast-Terminal Sliding-Mode Control for a PMSM Speed-Regulation System

Barrier-function-based adaptive fast-terminal sliding-mode control approaches have been devised to enhance the precision of speed regulation of permanent magnet synchronous motors (PMSMs). Firstly, the speed loop utilizes fast-terminal sliding-mode control, which contributes to a faster convergence rate and enhances the robustness of the system. By adopting this control technique, the system can quickly reach the desired speed setpoint and effectively handle disturbances. Secondly, an adaptive law based on the barrier function is employed to adjust the control gain adaptively. The proposed adaptive law considers the magnitude of the disturbance and effectively mitigates chattering resulting from excessive switching gain. Unlike conventional control methods, the design of the adaptive fast-terminal sliding-mode control does not require attaining the upper limit of the lumped disturbances. Experimental results are presented to validate the proposed approach. These results demonstrate that the proposed method outperforms the conventional terminal sliding mode control technique in terms of handling both external and internal disturbances.

Stochastic disturbance with finite-time chaos stabilization and synchronization for a fractional-order nonautonomous hybrid nonlinear complex system via a sliding mode control

This paper provides a novel approach to studying the chaos control and synchronization of fractional-order hybrid Darcy–Brinkman systems (FOHDBs). We use the truncated Galerkin method to transform the system of partial differential equations (PDEs) into ordinary differential equations (ODEs) based on Fourier modes in a nonlinear low-dimensional Brinkman model. In the nonlinear complex system, hybrid nanoparticles and fluid flow physical characteristics are considered to be external disturbances. As a result, the implications of model uncertainty and external disruptions are fully absorbed into the problem, further complicating it and resulting in highly complex and unpredictable behaviors. In addition, To assure the occurrence of the sliding motion in a finite amount of time, an appropriate robust fractional sliding mode technique is proposed. Sliding motion is shown to occur in finite time using the fractional Lyapunov stability. Following that, we discussed control techniques for achieving infinitesimally close to an equilibrium of chaotic states and tracking errors. It is important to note that FOHDBs and external stochastic disturbances can be controlled using the proposed fractional nonsingular terminal sliding mode control technique. Finally, the effectiveness and applicability of the suggested finite-time control technique are graphically illustrated by the analytical and numerical simulations.

Secure control for remote networked stochastic systems via integral sliding mode

This paper deals with the secure control problem for a class of networked stochastic systems with false data injection attacks via an integral sliding mode control technique. The networked control system is with a hierarchical structure, and the main controller and a remote controller are considered to realize the secure control against false data injection attacks on the network between a main controller and the plant. A mode-shared event-triggering controller is designed as the main controller, by utilizing a time delay approach. An input–output model based on a two-term approximation is applied to cope with the formulated time-varying delay. Then, the scaled small gain theory is employed to analyze the stability of the resulting system. Sufficient conditions on ensuring the desired system performance are derived and then the controller parameters are synthesized. Moreover, an elaborated sliding mode control law is proposed for the desired secure control action. Finally, two simulation examples are permitted to verify the effectiveness of the theoretical derivations.

Online reinforcement learning control via discontinuous gradient

SummaryThis work proposes a reinforcement learning control scheme for systems affected by persistent external perturbations. This scheme relies on and high‐order sliding mode control techniques combined to estimate the parameters with a certain degree of precision and simultaneously attenuate persistent and state‐dependent perturbations. The proposed solution is a novel design technique based on the minimization method via Discontinuous Gradient. The stability of the proposed scheme is proved via the Lyapunov approach.

Simulation-Based Evaluation of Sliding Mode Control with Washout Filter for Power Balancing in Battery Energy Storage Systems

This research paper presents a simulation-based evaluation of a novel sliding mode control (SMC) approach with a washout filter for power balancing in battery energy storage systems (BESS). Unlike traditional proportional-plus integral control methods, the proposed SMC technique is specifically tailored for charging and discharging BESS units. The primary objective of this study is to investigate the efficacy of the proposed SMC-based scheme in achieving optimal power balancing at the DC bus of the BESS. A comparative analysis is conducted to assess the performance of the developed SMC strategy against the conventional proportional-plus integral controller. MATLAB simulations utilizing Simulink and the Sim Power System toolbox are employed to obtain comprehensive results. The findings of this study provide valuable insights into the effectiveness of the SMC with washout filter for enhancing power balancing in BESS applications, thereby contributing to advancements in energy storage system control methodologies. Keywords: Sliding Mode Control (SMC), Washout Filter, Power Balancing, Battery Energy Storage Systems (BESS), Simulation-based Evaluation, MATLAB Simulation

Speed Control for BLDC Motor for Electric Vehicles Applications by Different Kinds of Sliding Mode Control Techniques

Speed Control for BLDC Motor for Electric Vehicles Applications by Different Kinds of Sliding Mode Control Techniques

Model-free low-power observer based robust trajectory tracking control of UAV quadrotor with unknown disturbances

PurposeThe purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane.Design/methodology/approachTo achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer.FindingsThe finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique.Practical implicationsThis paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced.Originality/valueAlthough extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

Discrete-time integral terminal sliding mode load following controller coupled with disturbance observer for a modular high-temperature gas-cooled reactor

With the appearance of digital computers and microprocessor technologies, the control systems used in nuclear reactors continue to transform from analog devices to digital ones in recent years. A heavy challenge is that applying the pre-existing intelligent load following control algorithms developed in the continuous-time domain to the current digital devices of the nuclear reactors may yield the so-called digital chattering effects, and even trigger system instability. To this end, this paper presents a discrete-time integral terminal sliding mode controller (DTITSMC) coupled with a discrete-time disturbance observer (DTDO) for the load following of a modular high-temperature gas-cooled reactor (MHTGR). The common continuous-time MHTGR model is first transformed into a discrete-time form with consideration of model uncertainties, exogenous disturbances, and discretization errors. Then, on the basis of this discrete-time MHTGR model, a DTDO that can estimate the lumped disturbances, composed of model uncertainties, exogenous disturbances, discretization errors, and unmeasured system states, is developed, subsequently being combined with the designed DTITSMC scheme in order to enhance the system robustness. The proposed DTITSMC scheme coupled with the DTDO is novel in that it can be directly implemented on the digital control system of the MHTGR, while at the same time providing an improved load following control performance, owing to the integration of the state-of-the-art sliding mode control techniques, backstepping control techniques, and the disturbance feedforward compensation supported by the disturbance observer techniques. Both the estimation error convergence of the DTDO and the overall system stability are theoretically proved by the Lyapunov stability theory in this paper. Finally, the feasibility and superiority of the proposed DTITSMC scheme coupled with the DTDO over the previous discrete-time linear sliding mode controller (DTLSMC) and discrete-time proportional–integral–derivative controller (DTPIDC) are further confirmed by simulation studies, where in the absence of lumped disturbances, the value of the accumulative absolute load error (AALE) produced by the proposed DTSMPPC scheme coupled with the DTDO is merely 0.0575% and 0.2675% to that of the previous DTLSMC and the optimized DTPIDC, respectively, while in the presence of lumped disturbances, the value of the AALE produced by the proposed DTSMPPC scheme coupled with the DTDO is merely 0.006% and 0.1952% to that of the previous DTLSMC and the optimized DTPIDC, respectively.

Flatness‐based sliding mode control for stabilizing a spherical pendulum on a quadrotor

AbstractThis paper presents the problem of transporting a suspended load by a quadrotor. A full model considering the quadrotor and the dynamics of the suspended load, in a three‐dimensional space, is proposed considering as control inputs the torques and the thrust force due to the motors. The solution proposed consists of simple control strategies based on the tangent linearization of the model, which is controllable and therefore flat. A sliding mode control technique is developed for the thrust force and torques associated with the Euler angles in order to track a desired trajectory of the vehicle in a three‐dimensional space with minimum oscillation of the suspended load. The control strategy results to be relatively simple to implement and achieves local stability of the tracking errors, as well as robustness to internal nonlinearities, which are neglected in the linearization process and other external disturbances. The attractiveness of the sliding surfaces and the stability of the tracking errors are formally studied using Lyapunov stability theory. Simulation results are given to show the performance of the proposed control strategy.

Adaptive gain scheduling based event-triggering control design for robust performance of active magnetic bearing

This article proposes an efficient adaptive robust control for the eight-pole active magnetic bearing based on a heteropolar structure. Due to the uncertain behavior of active magnetic bearing, the mathematical model of active magnetic bearing is considered to be highly nonlinear and uncertain. As the rotor displacement and velocity are the measurable states, sliding mode control is designed to estimate state variables. Also, a matched disturbance term is used to deal with undesirable disturbances in the active magnetic bearing system. The controller is developed for an active magnetic bearing using the event-triggering-based sliding mode control technique. However, the stability of the proposed scheme has been achieved with the help of Lyapunov theory. Furthermore, the adaptive gain scheduling approach based on a neural network has been augmented to adjust the gain of the proposed controller for active magnetic bearing adaptively. The simulation studies have been performed in detail to demonstrate the use of proposed scheme for the robust control of active magnetic bearings. Finally, a comparative analysis of the proposed control design scheme with a conventional controller has been performed to achieve improved performance satisfying the plant constraints.