Showing papers on "Sliding mode control published in 2022"

Observer-Based Sliding Mode Control for Networked Fuzzy Singularly Perturbed Systems Under Weighted Try-Once-Discard Protocol

Abstract: In this article, the sliding mode control issue is investigated for a class of discrete-time Takagi–Sugeno fuzzy networked singularly perturbed systems via an observer-based technique. Moreover, to process the measurement output and schedule the transmission sequence for relieving the communication burden, a logarithmic quantizer and a weighted try-once-discard protocol are synthesized, which can further improve the network bandwidth utilization in networked control systems. Based on the fuzzy observer states, a novel fuzzy sliding surface is established by considering the singularly perturbed parameter properly, and we endeavor to synthesize a sliding mode control law such that the reachability of the prescribed sliding surface could be guaranteed. In addition, by virtue of the convex optimization theory and Lyapunov approach, sufficient conditions are developed to guarantee the asymptotic stability of the sliding mode dynamics as well as the error system with an expected $H_{\infty }$ performance. Finally, a verification example is presented to illustrate the feasibility and effectivity of the proposed method.

Modeling and Advanced Control of Dual-Active-Bridge DC–DC Converters: A Review

Abstract: This article classifies, describes, and critically compares different modeling techniques and control methods for dual-active-bridge (DAB) dc–dc converters and provides explicit guidance about the DAB controller design to practicing engineers and researchers. First, available modeling methods for DAB including reduced-order model, generalized average model, and discrete-time model are classified and quantitatively compared using simulation results. Based on this comparison, recommendations for suitable DAB modeling method are given. Then, we comprehensively review the available control methods including feedback-only control, linearization control, feedforward plus feedback, disturbance-observer-based control, feedforward current control, model predictive current control, sliding mode control, and moving discretized control set model predictive control. Frequency responses of the closed-loop control-to-output and output impedance are selected as the metrics of the ability in voltage tracking and the load disturbance rejection performance. The frequency response plots of the closed-loop control-to-output transfer function and output impedance of each control method are theoretically derived or swept using simulation software PLECS and MATLAB. Based on these plots, remarks on each control method are drawn. Some practical control issues for DAB including dead-time effect, phase drift, and dc magnetic flux bias are also reviewed. This article is accompanied by PLECS simulation files of the reviewed control methods.

Fuzzy SMC for Quantized Nonlinear Stochastic Switching Systems With Semi-Markovian Process and Application

Abstract: This article is concerned with the issue of quantized sliding-mode control (SMC) design methodology for nonlinear stochastic switching systems subject to semi-Markovian switching parameters, T–S fuzzy strategy, uncertainty, signal quantization, and nonlinearity. Compared with the previous literature, the quantized control input is first considered in studying T–S fuzzy stochastic switching systems with a semi-Markovian process. A mode-independent sliding surface is adopted to avoid the potential repetitive jumping effects. Then, by means of the Lyapunov function, stochastic stability criteria are proposed to be dependent of sojourn time for the corresponding sliding-mode dynamics. Furthermore, the fuzzy-model-based SMC law is proposed to ensure the finite-time reachability of the sliding-mode dynamics. Finally, an application example of a modified series dc motor model is provided to demonstrate the effectiveness of the theoretical findings.

Novel Neural Network Fractional-Order Sliding-Mode Control With Application to Active Power Filter

Abstract: In this article, a fractional-order sliding-mode control scheme based on a two-hidden-layer recurrent neural network (THLRNN) is proposed for a single-phase shunt active power filter. Considering the shortcomings of traditional neural networks (NNs) that the approximation accuracy is not high and weight and center vector of NNs are unchangeable, a new THLRNN structure which contains two hidden layers to make the network have more powerful fitting ability, is designed to approximate the unknown nonlinearities. A fractional-order term is added to a sliding-mode controller to have more adjustable space and better optimization space. Simulation and experimental studies prove that the proposed THLRNN strategy can accomplish the current compensation well with acceptable current tracking error, and have satisfactory compensation property and robustness compared with a traditional neural sliding controller.

Sliding Mode Dual-Channel Disturbance Rejection Attitude Control for a Quadrotor

Abstract: In this article, a sliding mode dual-channel disturbance rejection control based on an extended state observer is proposed for the attitude control of a quadrotor under unknown disturbances. There exist an inner disturbance rejection channel (IDRC) and an outer disturbance rejection channel (ODRC) in this control scheme. In the IDRC, a low-frequency disturbance compensator is proposed to obtain the disturbance compensation value and to compensate the low-frequency component of the lumped disturbance. In the ODRC, a novel sliding mode controller with a variable-gain switching term and a constant-gain switching term is designed, and the switching terms are used to compensate the virtual disturbance estimation error and the high-frequency component of the lumped disturbance. The low-frequency and high-frequency components of the lumped disturbance can be estimated and the influence of the virtual disturbance estimation error is reduced by using the proposed control scheme. The stability of the system is proved by using the Lyapunov theory. Finally, the effectiveness of the proposed scheme is tested by numerical simulations and platform experiments.

Adaptive Attitude Control of a Quadrotor Using Fast Nonsingular Terminal Sliding Mode

Abstract: As one type of unmanned aerial vehicles, the quadrotor typically suffers from payload variations, system uncertainties, and environmental wind disturbances, which significantly deteriorate its attitude control performance. To provide high-speed, accurate, and robust attitude tracking performance for the quadrotor, an adaptive fast nonsingular terminal sliding mode (AFNTSM) controller is proposed in this article. The proposed AFNTSM controller combines the advantages of fast nonsingular terminal sliding mode (FNTSM), integral sliding mode, and adaptive estimation techniques, which are effective to achieve the desired tracking performance and suppress control signal chattering. Furthermore, unlike conventional methods, the adaptive estimation removes the requirements for the upper bound information of the disturbances. It is proved that the proposed AFNTSM can guarantee finite-time convergence and zero tracking error for the quadrotor attitude control. Finally, comparative study with the FNTSM control only and conventional sliding mode control is conducted through experiments and the results demonstrate that the proposed AFNTSM can achieve faster convergence and stronger robustness in line with theoretical analysis.

Fuzzy Multiple Hidden Layer Recurrent Neural Control of Nonlinear System Using Terminal Sliding-Mode Controller

Abstract: This study designs a fuzzy double hidden layer recurrent neural network (FDHLRNN) controller for a class of nonlinear systems using a terminal sliding-mode control (TSMC). The proposed FDHLRNN is a fully regulated network, which can be simply considered as a combination of a fuzzy neural network (FNN) and a radial basis function neural network (RBF NN) to improve the accuracy of a nonlinear approximation, so it has the advantages of these two neural networks. The main advantage of the proposed new FDHLRNN is that the output values of the FNN and DHLRNN are considered at the same time, and the outer layer feedback is added to increase the dynamic approximation ability. FDHLRNN was designed to approximate the nonlinear sliding-mode equivalent control term to reduce the switching gain. To ensure the best approximation capability and control performance, the proposed FDHLRNN using TSMC is applied for the second-order nonlinear model. Two simulation examples are implemented to verify that the proposed FDHLRNN has faster convergence speed and the FDHLRNN with TSMC has good dynamic property and robustness, and a hardware experimental study with an active power filter proves the feasibility of the method.

Speed-Current Single-Loop Control With Overcurrent Protection for PMSM Based on Time-Varying Nonlinear Disturbance Observer

Abstract: A novel finite-time control with q -axis current constrained based on time-varying second-order nonlinear disturbance observer is investigated to improve the performance of overcurrent protection and disturbance rejection for permanent magnet synchronous motor (PMSM) system. In general, the hardware could be damaged by a large transient current for achieving high-precision tracking performance when PMSM starts up. To this end, a speed-current single-loop control with q-axis current constrained is constructed by a novel finite-time controller for speed regulation of the PMSM system, which can balance well between the overcurrent protection and dynamic performance. The estimated peak generated by the high gain to ensure a precise accuracy will be integrated into the control system at the initial moment in the traditional nonlinear disturbance observer. Taking this into account, parameter uncertainties, nonmodeled dynamics, and estimated peak at the initial moment of the PMSM system are estimated by a time-varying second-order nonlinear disturbance observer. Finally, rigorous stability analysis is established for the proposed composite strategy. Comparative simulations and experiments are designed on proportion integration differentiation, sliding mode control (SMC), and the proposed method. Results demonstrate that the proposed method has better robustness and overcurrent protection property.

Sliding Mode Control in Power Converters and Drives: A Review

Abstract: Sliding mode control (SMC) has been studied since the 1950s and widely used in practical applications due to its insensitivity to matched disturbances. The aim of this paper is to present a review of SMC describing the key developments and examining the new trends and challenges for its application to power electronic systems. The fundamental theory of SMC is briefly reviewed and the key technical problems associated with the implementation of SMC to power converters and drives, such chattering phenomenon and variable switching frequency, are discussed and analyzed. The recent developments in SMC systems, future challenges and perspectives of SMC for power converters are discussed.

Event-Triggering and Quantized Sliding Mode Control of UMV Systems Under DoS Attack

Abstract: This paper is concerned with security control of nonlinear unmanned marine vehicle (UMV) systems under a networked environment. The UMV system and land-based control station are connected by a communication network. Considering the limited communication resource in the marine environment, the dynamic event-triggering mechanisms are proposed in the sensor to controller and controller to actuator sides simultaneously. Meanwhile, the triggered output data is then quantized by a logarithmic quantizer before being sent to the remote control station. First, based on the Takagi-Sugeno (T-S) fuzzy theory, the nonlinear UMV system is molded as a T-S fuzzy model. Then a hybrid switched fuzzy system is established by taking the DoS attack and quantization effect into account. An observer-based sliding mode control (SMC) scheme is proposed to stabilize the system under DoS attack, and the observer gains and controller gains can be obtained by solving a set of matrix inequalities. Finally, a benchmark UMV system is used to show the effectiveness of control scheme.

Adaptive Attitude Control of a Quadrotor Using Fast Nonsingular Terminal Sliding Mode

Abstract: As one type of unmanned aerial vehicles, the quadrotor typically suffers from payload variations, system uncertainties, and environmental wind disturbances, which significantly deteriorate its attitude control performance. To provide high-speed, accurate, and robust attitude tracking performance for the quadrotor, an adaptive fast nonsingular terminal sliding mode (AFNTSM) controller is proposed in this article. The proposed AFNTSM controller combines the advantages of fast nonsingular terminal sliding mode (FNTSM), integral sliding mode, and adaptive estimation techniques, which are effective to achieve the desired tracking performance and suppress control signal chattering. Furthermore, unlike conventional methods, the adaptive estimation removes the requirements for the upper bound information of the disturbances. It is proved that the proposed AFNTSM can guarantee finite-time convergence and zero tracking error for the quadrotor attitude control. Finally, comparative study with the FNTSM control only and conventional sliding mode control is conducted through experiments and the results demonstrate that the proposed AFNTSM can achieve faster convergence and stronger robustness in line with theoretical analysis.

Adaptive Second-Order Sliding Mode Control: A Lyapunov Approach

Abstract: This article proposes an adaptive second-order sliding mode (ASOSM) controller design by means of the Lyapunov method. The notable feature of the proposed algorithm is that it only needs boundedness of the uncertainties, whereas boundedness of the derivatives of uncertainties is not demanded. Under the proposed ASOSM control scheme, the gain can be dynamically tuned, which avoids gain overestimation. The finite-time stability of the closed-loop ASOSM dynamics is proved via the Lyapunov theory. Finally, the simulation results are shown to validate the theoretical analysis.

Fuzzy Integral Sliding-Mode Control for Nonlinear Semi-Markovian Switching Systems With Application

Abstract: The issue of sliding-mode control (SMC) design is studied for a class of nonlinear semi-Markovian switching systems (S-MSSs) via T–S fuzzy approach. Compared with previous literature, novel integral sliding-mode surfaces (ISMSs) are developed to depend on the designed controller gains and projection matrices. The aim of this work is to design an appropriate fuzzy SMC law under complex stochastic semi-Markovian switching process. For this purpose, the novel ISMSs are developed under the T–S fuzzy modeling framework. Then, based on the weak infinitesimal operator theory, sufficient conditions are given for stochastic stability criteria relying on the sojourn-time. Furthermore, an appropriate fuzzy SMC law is proposed to drive the state signals onto the predefined fuzzy manifold. Finally, an electric circuit model illustrates the effectiveness of the theoretical findings.

Self-Triggered Sliding Mode Control for Networked PMSM Speed Regulation System: A PSO-Optimized Super-Twisting Algorithm

Abstract: This article is concerned with the design of a super-twisting algorithm (STA) based sliding mode controller for permanent magnet synchronous motor (PMSM) speed regulation system under the self-triggered mechanism. By using the strict Lyapunov function approach, it is shown that the tracking error converges to an ultimate domain within the finite-time sense under the proposed self-triggered STA. A feasible self-triggered strategy is designed for both cases with and without external perturbation. Moreover, a nonlinear optimization problem is formulated in terms of the tradeoff between the ultimate domain and the communication burden. The optimized STA gains are obtained by solving the above-formulated optimization problem via a particle swarm optimization algorithm. Finally, the applicability of the proposed self-triggered STA for PMSM is verified by simulation and experiment results.

Simultaneous Arrival to Origin Convergence: Sliding-Mode Control Through the Norm-Normalized Sign Function

Abstract: In this article, simultaneous arrival to origin (SATO) convergence is defined—all state elements arriving at the origin at the same time. Accordingly, a relevant sufficient condition is proposed for SATO convergence. Based on this formulation of SATO convergence, the classical and norm-normalized (NN) sign functions are revisited. Their differences are studied with applications in sliding-mode control design. Both functions (expectedly when properly invoked) contribute to system stability, while the NN sign function enables the system to accomplish SATO convergence. This finding shows the distinctive merit of the NN sign function in achieving more than finite-time stability for a sliding-mode control system. Extensions to the scenario with a networked system are studied, where, using the NN sign function, the networked system (now with the SATO convergence property) drives all the agents to reach consensus simultaneously. Additionally, for double integrator systems and Euler–Lagrange systems, singularity-free sliding-mode control laws are designed and demonstrated to achieve SATO convergence.

A new adaptive sliding mode controller based on the RBF neural network for an electro-hydraulic servo system.

Abstract: Accuracy and robust trajectory tracking for electro-hydraulic servo systems in the presence of load disturbances and model uncertainties are of great importance in many fields. In this work, a new adaptive sliding mode control method based on the RBF neural networks (SMC-RBF) is proposed to improve the performances of a robotic excavator. Model uncertainties and load disturbances of the electro-hydraulic servo system are approximated and compensated using the RBF neural networks. Adaptive mechanisms are designed to adjust the connection weights of the RBF neural networks in real time to guarantee the stability. A nonlinear term is introduced into the sliding mode to design an adaptive terminal sliding mode control structure to improve dynamic performances and the convergence speed. Moreover, a sliding mode chattering reduction method is proposed to suppress the chattering phenomenon. Three types of step, ramp and sine signals are used as the simulation reference trajectories to compare different controllers on a co-simulation platform. Experiments with leveling and triangle conditions are presented on a robotic excavator. Results show that the proposed SMC-RBF controller is superior to existing proportional integral derivative (PID) and sliding mode controller (SMC) in terms of tracking accuracy and disturbance rejection.

Observer‐based adaptive fuzzy hierarchical sliding mode control of uncertain under‐actuated switched nonlinear systems with input quantization

Abstract: In this article, an observer‐based adaptive fuzzy hierarchical sliding mode control (HSMC) scheme is put forward for uncertain under‐actuated switched nonlinear systems in the presence of quantized input signals. The issues of quantized input signals from a hysteretic quantizer, external disturbances, unmeasured system states and completely unknown nonlinear functions are taken into account for the under‐actuated system. First, the chattering phenomena can be effectively avoided by adopting the considered hysteretic quantizer. Then, fuzzy logic systems (FLSs) is utilized to approximate the unknown smooth nonlinear functions representing the system uncertainties. Furthermore, a switched fuzzy state observer is established to estimate the unmeasured system states. Based on the Lyapunov stability theory, the proposed control scheme can ensure the boundedness of all signals in the closed‐loop system and make the system output track given reference signals well. Finally, a numerical simulation example is given to verify the effectiveness of the proposed control scheme.

Decentralized Adaptive Sliding Mode Control of Large-Scale Semi-Markovian Jump Interconnected Systems With Dead-Zone Input

Abstract: In this article, a decentralized adaptive sliding mode control scheme is proposed for stabilization of large-scale semi-Markovian jump interconnected systems, in which dead-zone linearity in the input and unknown interconnections among subsystems are tackled. First, by designing an integral sliding surface for each subsystem, local sliding mode dynamics are obtained in good property of dynamics. Second, sufficient conditions are established for checking the stochastic stability of the sliding mode dynamics with generally uncertain and unknown transition rates. Third, a variable structure controller is designed to guarantee finite-time reachability of sliding surface, and the unknown interconnections among subsystems are compensated by adaptive laws. Finally, a numerical example is provided to verify the effectiveness of the proposed control scheme.

Observer-Based Sliding-Mode Control for Grid-Connected Power Converters Under Unbalanced Grid Conditions

Abstract: This article proposes a novel robust control strategy for three-phase power converters operated under unbalanced grid conditions. A consolidated control objective is obtained in the stationary $\alpha \beta$ frame, which can be flexibly adjusted according to the degree of oscillation in the active and reactive powers and the balance of the three-phase current. Based on the dynamics of the converter and control objective, a control scheme in a cascaded framework is presented, in which an adaptive observer is applied to estimate the positive and negative sequences of the grid voltage. In the current tracking loop, a super-twisting algorithm current controller coupled with a super-twisting differentiator is implemented to track the current references, featuring rapid dynamics, and improved robustness. Additionally, in the voltage regulation loop, an effective composite controller is developed to regulate the dc-link voltage, where a super-twisting observer is used to estimate the load disturbance, thereby improving the performance of the converter. The experimental results are provided to confirm the effectiveness and superiority of the proposed control strategy.

Adaptive Second-Order Sliding Mode Control for Grid-Connected NPC Converters With Enhanced Disturbance Rejection

Abstract: In this article, a two-stage control scheme consisting of an adaptive-gain second-order sliding mode (SOSM) controller and a switched high-gain observer (HGO) is proposed for the three-level neutral-point-clamped (NPC) converter. The adaptive-gain SOSM control method is applied both in the voltage regulation loop and instantaneous power tracking loop, thus, the boundary of the disturbance derivative does not need to be known a priori . Compared with the fixed-gain SOSM, it provides a faster dynamic and a better steady-state response for the NPC converter. On the other hand, the conventional disturbance compensation observer used in the power system suffers from the adverse effects of measurement noise, which limits the performance of the observer. A switched HGO is combined with the adaptive-gain SOSM controller in the voltage regulation loop to address this issue. By using a switched observer gain, the switched HGO greatly diminishes the performance degradation induced by the inevitable measurement noise. Finally, several experiments between the representative extended state observer-based SOSM control scheme and the proposed control method are carried out for a comparison. The results demonstrate the feasibility and effectiveness of the proposed approach.

Self-Constructing Fuzzy Neural Fractional-Order Sliding Mode Control of Active Power Filter

Abstract: In this article, a fractional-order sliding mode control (FOSMC) scheme is proposed for mitigating harmonic distortions in the power system, whereby a self-constructing recurrent fuzzy neural network (SCRFNN) is used to weaken the effect of compound nonlinearity caused by unknown uncertainties and environmental fluctuations. The fractional-order sliding mode controller (SMC) is constructed to maintain the control system to be asymptotically stable and a fractional-order calculus is introduced into an SMC to soften the sliding manifold design and realize chattering reduction. Considering parameter variations existing in the power system model, SCRFNN is adopted to approximate the unknown dynamics, which is able to dynamically update network structure by optimizing the fuzzy division, and a feedback connection is incorporated into the feedforward neural network, which is regarded as a storage unit to enhance the capability of coping with temporal problem. The control scheme combining the FOSMC with the SCRFNN can make the tracking error and its time derivative converge to zero. Experimental studies demonstrate the validity of the designed scheme, and comprehensive comparisons illustrate its superiority in harmonic suppression and high robustness.

Appointed Fixed Time Observer-Based Sliding Mode Control for a Quadrotor UAV Under External Disturbances

Abstract: In this article, a study of the appointed fixed time control problem is presented for the quadrotor unmanned aerial vehicle attitude control system subject to external disturbances. Based on the appointed fixed time sliding mode variable and the adaptive technique, a novel sliding mode observer is first established to estimate the external disturbances within the appointed settling time. Subsequently, an appointed fixed time controller is proposed to track the desired attitude regardless of the initial states. To circumvent the singularity problem of the above controller, a novel improved adaptive sliding mode control law is designed by employing a nonlinear function and a modified sliding mode observer. Moreover, the chattering phenomenon is attenuated by replacing the sign function with hyperbolic tangent function. The appointed practical fixed time stability of the closed-loop attitude control system is proved and analyzed rigorously utilizing the Lyapunov theory. Finally, the effectiveness and fine performance of the proposed schemes are illustrated by numerical simulation results.

Self-Triggered Sliding Mode Control for Networked PMSM Speed Regulation System: A PSO-Optimized Super-Twisting Algorithm

Abstract: This article is concerned with the design of a super-twisting algorithm (STA) based sliding mode controller for permanent magnet synchronous motor (PMSM) speed regulation system under the self-triggered mechanism. By using the strict Lyapunov function approach, it is shown that the tracking error converges to an ultimate domain within the finite-time sense under the proposed self-triggered STA. A feasible self-triggered strategy is designed for both cases with and without external perturbation. Moreover, a nonlinear optimization problem is formulated in terms of the tradeoff between the ultimate domain and the communication burden. The optimized STA gains are obtained by solving the above-formulated optimization problem via a particle swarm optimization algorithm. Finally, the applicability of the proposed self-triggered STA for PMSM is verified by simulation and experiment results.

A Novel Discrete Compound Integral Terminal Sliding Mode Control With Disturbance Compensation For PMSM Speed System

Abstract: A novel discrete compound integral terminal sliding mode control (C-ITSMC) is proposed for permanent magnet synchronous motor (PMSM) speed system in this article. In this control scheme, the integral terminal sliding mode control (ITSMC) is first introduced to realize state convergence in finite time. Then, an extended state observer-based compensator is designed to solve the problem that sliding mode control needs large switching gain to handle disturbances. Third, a predictive control-based optimal control signal is obtained, and this optimal control signal is considered as an assistant control signal to drive the state to reach quasi-sliding mode in an optimal manner. In this way, reaching quality is improved and the tracking error band is further reduced. Finally, a compound control scheme is obtained. The major advantages of this scheme are characterized by output-based information only used, low order of controller, excellent model adaptability, and disturbance rejection ability. Experimental results show that the proposed control scheme can effectively reduce the output error and enhance the robustness of PMSM speed system.

Input–Output Finite-Time Asynchronous SMC for Nonlinear Semi-Markov Switching Systems With Application

Abstract: This article investigates the input–output finite-time stability (IO-FTS) for nonlinear hidden semi-Markov switching systems (S-MSSs) via the asynchronous sliding mode control (SMC) approach. Under the assumption that a detector is set up to estimate the mode value, the mode of the original system is not directly accessible. The asynchrony between the system and controller is described as a hidden semi-Markov model (HSMM). Many practical factors, such as semi-Markov switching parameters, finite-time interval, asynchronous phenomenon, uncertain parameters, and nonlinearity, are taking into account during the SMC design process. We aim to design an efficient finite-time asynchronous SMC scheme under a hidden semi-Markov switching effect. A novel sliding switching surface (SSS) is constructed, in which the SMC law rises asynchronously with original S-MSSs. Then, by means of finite-time stability, an asynchronous SMC law is synthesized to guarantee that the associated hidden S-MSSs fulfill the reaching condition within a finite time. Furthermore, sufficient conditions are derived in view of the IO-FTS of sliding mode dynamics under the framework of a novel inequality lemma. Results are given for the application of this control design method to a single-link robot arm model (SLRAM).