Classical Sliding Mode Control Research Articles

Two-Stage Predefined-Time Exact Sliding Mode Control Based on Predefined-Time Exact Disturbance Observer

This paper is concerned with the predefined-time exact sliding mode control issue of a class of high-order uncertain nonlinear systems with disturbances. The proposed control scheme is composed of a predefined-time exact disturbance observer and a two-stage predefined-time exact sliding mode controller. The disturbance observer can estimate the system disturbances accurately within an arbitrary predefined observation time, and the time can be set as the handover time between two control stages. The classic sliding mode controller guarantees bounded system states in the first control stage. Then, a predefined-time sliding mode controller is designed based on time-varying tuning function, regulating the system states to exact zero within a final predefined settling time in the second stage. It is shown that the control input signal is always chattering-free with respect to time. The effectiveness and superiority of the proposed control scheme is demonstrated with simulation examples.

Control method based on DRFNN sliding mode for multifunctional flexible multistate switch

To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation, a control method involving flexible multistate switches (FMSs) is proposed in this study. This approach is based on an improved double-loop recursive fuzzy neural network (DRFNN) sliding mode, which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults. First, an improved DRFNN sliding mode control (SMC) method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system. To improve the robustness of the system, an adaptive parameter-adjustment strategy for the DRFNN is designed, where its dynamic mapping capabilities are leveraged to improve the transient compensation control. Additionally, a quasi-continuous second- order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability. The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem. A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink. The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Novel control strategy for the global model of wind turbine

This paper presents a new nonlinear control for the overall model of a three-blade horizontal axis variable speed wind turbine (VSWT) including mechanical and electrical parts, with the aim of improving its performance and making it more profitable. The proposed control is an extension of the classical sliding mode control (SMC) by converting its sliding surface into a sliding sector. The classical SMC approach is widely used for nonlinear systems due to its stability against parameter variation, it is robustness against modeling uncertainties, its good results against external disturbances, and its ease of implementation in real time. Unfortunately, the SMC has a major drawback related to the chattering phenomenon. This phenomenon is due to the utility of a higher switching gain in the case of large uncertainties, it causes high-frequency oscillations once the sliding regime is reached, and it can cause a loss of accuracy by influencing the input control variables. This is the reason that aims to develop a new control law to eliminate the chattering and to guarantee stability, which is demonstrated by the Lyapunov theory. The effectiveness of the developed control is compared with the SMC and is illustrated by numerical simulations using MATLAB toolboxes.

Improved performance and robustness of synchronous reluctance machine control using an advanced sliding mode and direct vector control

AbstractThis article focuses on improving the control approach for a synchronous reluctance motor (SynRM) drive powered by a two‐level pulse width modulation (PWM) inverter. While classical sliding mode control (SMC) has been extensively used in control system design, it comes with various drawbacks such as pronounced chattering effects, considerable transient state errors, and reduced robustness. These limitations hinder its practical applicability. To enhance the performance of the SynRM, this paper introduces a novel strategy that combines direct vector control (DVC) with advanced sliding mode control (ASMC), here referring to third‐order sliding mode command (TOSMC), for regulating speed and dq‐axis stator currents. The primary objective of this approach is to achieve precise and efficient control while minimizing total harmonic distortion (THD) in current and reducing output torque fluctuations. Notably, this strategy capitalizes on the strengths of TOSMC and DVC. The efficacy of the proposed control scheme is verified through two sets of thorough simulations realized in MATLAB/Simulink environment. The first set of simulations encompasses the load–torque test, where the motor is subjected to two different levels of load torque. The results from these tests showcase the control scheme's performance under varying load conditions. The second set of simulations involves the speed variation test, where intentional changes are applied to the motor's speed. This test assesses the control approach's ability to handle dynamic speed changes effectively. The proposed control strategy is further compared with conventional control methods, including proportional–integral and second‐order sliding mode command (SOSMC) controls. The results consistently demonstrate the superior performance of the novel approach in terms of accurate control, robustness, and overall stability. The combination of DVC and TOSMC offers a promising avenue for achieving enhanced motor control in the presence of load disturbances and speed variations.

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.

Twin Rotor Control via Second Order Sliding Modes

The control problem of a twin rotor system is considered in this study. Since the twin rotor system has highly nonlinear and coupled dynamics, a second order sliding mode controller is proposed which reduces chattering. An estimation for the equivalent part of the controller is also proposed. The classical sliding controller is also calculated and adapted to the twin-rotor system to compare. The numerical results presented that the designed controller achieved superior performance than the classical sliding mode controller in terms of reference tracking and chatter attenuation.

Developing and Implementing a Quantum Algorithm for the Sliding Mode Controller Using Multiple Qubit Operators: Application to DC Motor Speed Drive

With the advent of quantum computing, almost all classical computing concepts must be translated into quantum equivalents. Control theory, in particular, requires a large numbers of calculations. This paper designs and presents a quantum sliding mode controller. The controller uses two qubit states, one for detecting tracking errors and the other for determining the signs of the errors. The control signal to be applied to the system is stored in the third qubit state. This new controller is implemented on a DC motor to control the angular velocity using electrical current as an input signal. In terms of tracking error energy performance, the results show that the quantum sliding mode controller is just as efficient as the classical sliding mode controller. However, the quantum controller outperforms its predecessor by using 76% to 79% less control energy, allowing for smaller actuators. This represents a significant advancement in control theory in the era of quantum computers. Indeed, actuator control energy is the main drawback of the classical sliding mode control and reducing this energy is one of the main challenges for the control community.

An improved standalone photovoltaic system with hybrid dual integral sliding mode and model predictive control for MPPT

AbstractIn this research paper, a double diode model‐based photovoltaic (PV) system with a proposed hybrid dual integral sliding mode control (DISMC) and model predictive control (MPC) based maximum power point tracker (MPPT) has been started for a standalone power system. Compared with the single diode model, the advanced model dual diode provides accurate maximum power point (MPP) estimation with high velocity and more searching efficiency. It also delivers the extrapolation of current‐voltage characteristics of the photovoltaic system under any weather situation. Compared to classical sliding mode control (SMC) and dual integral sliding mode controller (DISMC) based MPPT, the proposed hybrid dual integral sliding mode controller (DISMC) and model predictive control (MPC) MPPT provide high, robust behavior with minimized steady‐state error. A high gain multilevel boost converter is employed, which provides an output voltage directly proportional to the level number. Moreover, the predictive model controller extracts peak power from the PV module by predicting errors in further sampling periods and switching pulses. The proposed hybrid MPPT method provides a fixed switching frequency of a high gain multilevel boost converter under varying environmental and loading conditions. Practical responses justify the capability of advanced MPPT control using the dSPACEDS1104 platform.

Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling

In this paper, a hydraulic motor controller is designed with a fuzzy supported integral sliding mode algorithm. The hydraulic system used in the study was modeled using artificial neural networks. Ability of handling nonlinearity of systems makes sliding mode controller to be a good choose for this system. The integral sliding mode controller can supply the robustness the system against the uncertainties. The basic idea of the proposed control method is to use fuzzy logic for the adaptation of the integral sliding mode control switching gain. Such adjustment reduces the chattering that is the most problem of classical sliding mode control. The equivalent control is computed using the radial basis function neural network. Simulation results of the presented method were compared with conventional PID controller results. It proved that it is more efficient to control the hydraulic system with integral fuzzy sliding mode control using neural network.

Cascade Control of Grid-Connected NPC Converters via Sliding Mode Technique

This paper proposes a two-stage control strategy including an adaptive sliding mode control (ASMC) and a nonlinear high-gain observer (HGO) for the three-level neutral-point-clamped (NPC) converter in dc microgrids. In the outer loop, an ASMC is utilized to regulate the dc-link voltage. By introducing an adapted gain, the tradeoff between the chattering and dynamic performance of the classic sliding mode control is overcome, thus the transient response of the NPC converter can be further enhanced without increasing the chattering. In addition, a nonlinear HGO is cooperated with the ASMC method to reject exogenous disturbance for the NPC converter, which not only assures a high disturbance rejection capacity but also accommodates the inevitable measurement noise in the actual applications. For the inner loop, in consideration of the parameter uncertainty, a high-gain observer-based second-order sliding mode (SOSM) control is adopted to assure the steady state performance and the robustness of the NPC converter. Finally, a set of comparative experimental results confirm the effectiveness and superiority of the proposed control scheme implemented in the NPC converter. Additionally, the robustness under parameter variation of the proposed method is also validated.

High-Performance Induction Motor Speed Control Using a Robust Hybrid Controller With a Supertwisting Sliding Mode Load Disturbance Observer

To enhance the speed control performance of a three-phase induction motor (IM) controlled by the vector control strategy, a new design of a hybrid controller (HC) is proposed based on the super-twisting algorithm (STA) and fuzzy approach. STA is chosen for its ability to decrease the ingrained chattering phenomenon in the classical sliding mode control (SMC) with maintaining tracking precision and robustness. Nevertheless, the control gains included in the control law have an evident impact on suppressing the chattering phenomenon and increasing the system's dynamic response speed. Therefore, firstly, a robust HC based on the fuzzy logic control (FLC) approach that operates as a fuzzy supervisor to on-line self-tune the value of the gains according to the system states is suggested to achieve high dynamic performance and limit the chattering effect. Secondly, to enhance the disturbance refusal capability, a super-twisting sliding mode load disturbance observer (STSMLDO) is developed to estimate the load torque disturbances. Then the estimated disturbance is introduced into the equivalent control law. Subsequently, the system stability is verified by the Lyapunov theorem. Finally, the superiority of the proposed scheme is validated through comparison with the advanced and traditional controllers in simulation and experimental studies.

A robust voltage control of dual active full bridge converter based on RBF neural network sliding mode control with reduced order modeling approach

This paper presents a control method of dual active full bridge (DAB) DC/DC converter based on neural network Sliding mode control under the reduced order modeling method, which is used to enhance the output voltage regulation and improve the system robustness. Sliding mode control (SMC) is famous for its robustness and improving the dynamic performance of nonlinear systems. However, it includes drawbacks such as complex modeling, chattering, and decreased tracking performance. Therefore, through the method of reduced order modeling, the Radial Basis Function neural network algorithm is selected to modify and design the traditional sliding mode variable structure controller, completing the design of neural network approximation terms and adaptive laws. The proposed reduced order modeling and RBF(Radial Basis Function Neural Network)-SMC scheme simplifies the dual active full bridge modeling process, completes the parameter approximation of the sliding mode controller, and eliminates the chattering problem. Firstly, through simulation and comparative analysis of commonly used modeling methods for dual active full bridge, a reduced order modeling method was adopted to simplify the design process. Then, by ingeniously designing the sliding mode surface and Radial Basis Function control law, and using neural network to modify the Sliding mode control technology, the chattering problem, load disturbance and voltage fluctuation influence of the sliding mode controller are improved. The stability of the control method is proved by Lyapunov stability theory. Finally, the proposed RBF-SMC method is compared with PI linear control and classical Sliding mode control methods through simulation and experiments to verify the effectiveness of the proposed control method.

Path following control for large inland ships in a restricted waterway using the nonlinear terminal sliding mode method

In order to solve the problem of path following for large ships travelling in restricted waterways, an adaptive Line-Of-Sight (LOS) guidance with the Nonlinear Terminal Sliding Mode (NTSM) algorithm is proposed in this paper. Compared to classical Sliding Mode Controller (SMC) and Adaptive Sliding Mode Controller (ASMC), the proposed system enables large ships to track the desired path much faster, meanwhile, the course stability can also be achieved with the controller saturation and environmental disturbance. To solve the problems of high nonlinearity and uncertainty of ship motion in restricted waters, the mathematical model with Extended state observer (ESO) is proposed to linearize problem. A drift angle observer is established to observe the drift angle during the vessel's navigation, and the LOS guidance law is used to achieve accurate tracking of the desired trajectory. The simulation results show that the inland ships under the control of the proposed scheme can accurately track the desired trajectory in a restricted waterway. The proposed algorithm has good robustness under the effect of environmental disturbances.

Whale Optimization Algorithm Enhances the Performance of Knee-Exoskeleton System Controlled by SMC

Physiotherapeutic exoskeleton devices have recently been developed to help people rehabilitate impaired limb mobility and replace the use of physiotherapists. Such systems are characterized by high nonlinear and time-varying coefficients. In order to cope with such difficult control challenges, a need arose for reliable nonlinear controllers. While in this study the Sliding Mode Control (SMC) was used to track the trajectory of the knee exoskeleton-system (KES) while having parameter uncertainty. In addition, the whale optimization algorithm (WOA) was introduced and developed to adjust the thickness design parameters for further optimization of its performance. The simulation was performed on a calculator using the MATLAB-Simulink program to conduct a comparative study between the optimal and Classical SMC where the results of comparison with the test parameters used by the SMC showed, the results of the proposed optimal SMC revealed that the positioning inaccuracy of the knee increased by 31.8807% and it follows from this result that the controller could successfully perform tracking the track well. Also, the control system created at the optimal thickness has a better dynamic performance than the classical thickness. Index Terms— Optimal, Knee exoskeleton system, Whale optimization approach, Sliding mode control.

Direct Torque Control of an Induction Motor Using Fractional-Order Sliding Mode Control Technique for Quick Response and Reduced Torque Ripple

The performance of electric drive propulsion systems is often degraded by the high torque and flux ripples of an electric drive. Traditional control methods, such as proportional plus integral (PI) controllers and classical sliding mode controllers (SMCs), have shown good response and reduced torque ripple, but even lower ripple content at low voltage levels is required for its effective use in electric vehicle (EV) applications. In this paper, a new direct torque control (DTC) technique with space vector pulse width modulation (SVPWM) using fractional-order sliding mode control (FOSMC) for a two-level inverter (2LI) at constant switching frequency is proposed. The effectiveness of this proposed controller is compared with a conventional proportional-integral controller and a conventional sliding mode controller (SMC). Simulink models are developed using MATLAB version R2018a to analyze the robustness of the proposed control strategy. Simulation results demonstrate the advantage of the proposed controller in reducing the torque ripples at steady state with less settling time during sudden load change conditions. The proposed control technique also demonstrates better utilization of the stator flux through flux trajectory waveforms.

Chattering suppression and hydrodynamic disturbance estimation of underwater manipulators using adaptive fuzzy sliding mode control

Robotic manipulators are nowadays widely used in various underwater scenarios, but their motion control remains a challenging task due to hydrodynamic effects. This article proposes a novel adaptive fuzzy sliding mode control (AFSMC) strategy for precise and robust control of underwater manipulators. To simulate the movement of the robotic manipulators in the underwater environment, the Unified Robot Description Format (URDF) file of a custom-designed electric underwater manipulator is imported into the Simscape Multibody and the hydrodynamic disturbance is modeled according to Morison’s equation. Furthermore, the proposed control strategy takes advantage of the universal approximation capability of fuzzy systems to avoid chattering and observe disturbances by adjusting the control gains of classical sliding mode control (CSMC). And adaptive laws are designed to update the parameters of the fuzzy systems. The strong friction caused by the seal is also compensated by actual test data. In the simulation experiments, a special environment of water flow and variable loads is considered. The results demonstrate that the AFSMC strategy can achieve high precision and strong robustness against disturbances for trajectory tracking. More importantly, the chattering caused by CSMC can be eliminated and the hydrodynamic disturbance can be estimated with high precision through the proposed control strategy.

Application of third-order sliding mode controller to improve the maximum power point for the photovoltaic system

In this research work, a third-order sliding mode control (TOSMC) is suggested to achieve the maximum power point (MPP) in a photovoltaic (PV) system application under variable weather conditions. Due to chattering phenomena, power losses increase when using the classical sliding mode control, and to reduce the steady-state error, ensure a good dynamic response, and achieve high power efficiency, a TOSMC strategy is applied to control the photovoltaic system. The studied system contains the PV panel, the DC–DC boost converter, the resistive load, and the proposed MPP tracking (MPPT) technique based on a TOSMC algorithm. This designed system is simulated using Matlab software, and the obtained simulation results show smaller steady-state error and good overall efficiency.

Tilting Control of Rotor Suspended by Complex Magnetic Bearings with Coupling Torques

For a novel Vernier-gimballing magnetically suspended flywheel (Vernier-gimballing MSFW) with conical magnetic bearing (MB) and Lorentz MB, the rotor’s dynamic model is constructed based on the characteristics of both coupling torque generated by conical MB and nonlinear titling torques generated by Lorentz MB. To make the high-speeding rotor tilt precisely and fast to output large moment, the Vernier-gimballing control method based on the extended state observer (ESO) combined with feedback linearization is presented originally considering torques’ complex nonlinearities, and the sliding mode control (SMC) with ESO is designed to improve the robustness of the closed-loop system. Simulations and experimental tests to verify the rightness and validity of SMC with ESO have been done and all research results indicate that the rotor can track the tilting signal faster and more accurately than classic SMC to output high precision moment.

Robust adaptive sliding mode control for path tracking of unmanned agricultural vehicles

In this paper, a novel adaptive sliding mode control (ASMC) for path tracking of unmanned agricultural vehicles is proposed. It is shown that the designed ASMC is capable of driving the closed-loop lateral position error dynamics to converge to zero asymptotically, where the sliding mode observer (SMO) is designed to estimate the system state so as to adaptively adjust the uncertain bounds of cornering stiffness. Compared with the classical sliding mode control technique, the proposed ASMC not only guarantees strong robustness with respect to parameter uncertainties, disturbance and varying road conditions, but also requires no prior knowledge of the road information. Simulation and experimental results from a typical agricultural wheeled vehicle are provided to verify the excellent performance of the proposed scheme.

Adaptive optimized fractional order control of doubly‐fed induction generator (DFIG) based wind turbine using disturbance observer

AbstractWind energy systems are pollution free and clean form of the renewable energy production. The dynamic model of a wind turbine system based on a doubly fed induction generator (DFIG) is exposed to external disturbances, uncertainties, and nonlinear dynamics. In this paper to ensure the system robustness against external disturbance and uncertainty in system parameters, a novel optimized fractional order robust adaptive sliding mode controller is proposed by utilizing a disturbance observer. The controller's main goal is to track the maximum power point of the wind turbine. In order to show the superiority of the proposed method, the results under normal conditions and in the presence of disturbance and uncertainty have been compared with the classical sliding mode control (SMC) and adaptive sliding mode control (ASMC). The parameters of all three controllers have been optimized by ant colony optimization (ACO) algorithm. The proposed method does not need the knowledge of the upper bounds of model uncertainty and disturbance. Also by using the fractional order operators in the control signal of the proposed method, its robustness against model uncertainty and disturbance is increased and it can extract the maximum power than the other compared methods.