Integral Sliding Mode Surface Research Articles

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables in the Takagi–Sugeno (T–S) fuzzy model of UMVs unknown. Consequently, traditional integral sliding mode techniques become infeasible. To address this issue, a control strategy combining integral sliding mode based on output feedback with a compensator utilizing switching mechanisms is proposed. First, a radial basis function neural network is used to approximate the nonlinear terms in the UMV T–S fuzzy model. In addition, an integral sliding mode surface is constructed based on fault estimation information and membership function estimation. On this basis, an FTC scheme based on integral sliding mode output feedback is developed to ensure that the UMV system is asymptotically stable and satisfies the prescribed H∞ performance index. Finally, simulation results are provided to demonstrate the effectiveness of the presented control strategy.

Integral sliding mode control and stability for Markov jump systems with structured perturbations and time-varying delay driven by fractional Brownian motion

The issues of stability and sliding mode control (SMC) for time-varying delay Markov jump systems (MJSs) with structured perturbations constrained by fractional Brownian motion (fBm) are explored. First, constructing a novel Lyapunov–Krasovskii functional (LKF) with exponential terms that contain the double-integral term, the pth moment exponential stability conditions are derived by utilizing the generalized fractional Itoˆ formula and conditional mathematical expectation. Subsequently, by designing the innovative integral sliding mode surface (SMS) associated with time-varying delay and the SMC law, the state trajectories of the dynamic systems can reach the designed SMS within a finite time. Ultimately, the numerical experiment is executed to confirm and ensure the accuracy and reliability of the obtained results.

Adaptive Neural Network Tracking Control of Robotic Manipulators Based on Disturbance Observer

This article presents an adaptive neural network (ANN) control scheme based on a disturbance observer that can achieve trajectory tracking control of robotic manipulators under external disturbances and dynamic model uncertainties. Firstly, an ANN controller based on full-state feedback is derived using the backstepping technique to achieve an online approximation of uncertainty. The integral sliding mode surface with a position error is introduced into the controller, which reduces the steady-state error of the system and enhances robustness. Then, a novel disturbance observer is designed to estimate both the approximation errors of the ANN and external disturbances, and to provide compensation for the controller, effectively suppressing the trajectory tracking errors caused by approximation errors and disturbances. Subsequently, the Lyapunov stability theory is utilized to demonstrate the stability of the developed control strategy and the boundedness of all closed-loop signals. Finally, numerical simulations are used to confirm the efficacy of the proposed control method.

Design of Lumped Disturbance Observer in Current Loop of IPMSM Based on Recursive Integral Sliding Mode Surface

To overcome the problem of current control effect being reduced by unideal factors in a motor control system, such as motor parameter variation, inverter dead time, nonlinearity of the system, etc., a sliding mode disturbance observer for an interior permanent magnet synchronous motor is proposed in this paper. The model of an interior permanent magnet synchronous motor with unideal factors is designed, and the unideal factors are unified into lumped disturbances of motor stator voltage. Then, the observer for lumped disturbance is designed. A recursive integral sliding surface is used to replace the terminal sliding surface to avoid the noise sensitivity and singularity problem of the traditional terminal sliding mode observer. The observer can estimate the lumped disturbance of the current loop without relying on the accurate system model in finite time. Moreover, the structure of the current loop does not need to be adjusted while using the observer to observe and compensate for disturbances. Experiments are carried out to verify the effectiveness of the proposed observer.

Adaptive integral sliding mode fault‐tolerant control for diesel engine air path system via disturbance observer

AbstractThis paper proposes a fault‐tolerant control strategy for the air path system of a turbocharged diesel engine, considering the simultaneous presence of matched and mismatched external disturbances, additive and loss of effectiveness fault modes in the EGR and VGT subsystems. Firstly, a disturbance observer based on theory is designed for estimating additive faults and external disturbances, and the upper bound of observation error is obtained. Based on the observation information, an integral sliding mode surface is designed, and the effectiveness of the sliding mode surface is analyzed. For the loss of effectiveness faults in the actuators, a novel adaptive update sliding mode controller is designed. The proposed control algorithm can get the fault information of the system and achieve fault‐tolerant control of through controller reconstruction. Ultimately, the effectiveness of the proposed method is validated through simulations and comparative analysis.

Security control of integral sliding modes for multi-agent systems under false data injection attacks

This paper aims to design a discrete integral sliding mode control (SMC) protocol, which is to address the consistency problem for the discrete multi-agent systems (MASs) with uncertain parameters under random false data injection (FDI) attacks. Firstly, an integral sliding mode surface is used to obtain the multi-agent error system and sufficient conditions to make it asymptotically stable. Secondly, the integral SMC law is proposed according to the arrival conditions of the SMC. The protocol makes the state trajectories of the system converge faster and fluctuate less, effectively weakening the FDI attacks and the uncertain parameter influence on the system. Finally, the effectiveness of the provided control mechanism is examined using numerical and practical application simulations.

Master-slave synchronization for uncertain Markov jump neural networks with time-delay based on the sliding mode control

<abstract><p>This paper investigated the master-slave synchronization for uncertain neural networks with time-delay by using the sliding mode control method. The uncertain parts in this neural network only needs to be bounded other than any structure condition. An integral sliding mode surface and sliding mode controller were designed such that the state trajectories of the neural networks could reach the sliding mode surface in finite time. Moreover, the computing method of the controller gain was proposed. Finally, a numerical example was provided to show the effectiveness of the obtained results.</p></abstract>

Robust adaptive fault tolerant control for nonlinear systems with actuator failure and mismatched disturbance

In this paper, a class of nonlinear systems with mismatched disturbance and actuator failure is investigated. A disturbance observer is proposed to estimate the disturbance first and the error of the estimation converges to zero exponentially. By introducing an integral sliding mode surface, the disturbance observer-based integral sliding mode fault tolerant control scheme is proposed to attenuate the disturbance and guarantee the stability of the system. In particular, the control law is designed for decoupling the partial disturbance and attenuating the disturbance that cannot be decoupled. Finally, two examples are given to illustrate the effectiveness of the proposed method.

Fixed-time nonsingular adaptive attitude control of spacecraft subject to actuator faults

In this article, a fixed-time adaptive fault-tolerant control approach is presented for the attitude tracking of rigid spacecraft subject to inertia uncertainties, external disturbances, and actuator faults. The designed controller is developed as a combination of the fixed-time integral sliding mode control and parametric adaptation technique. The fixed-time integral sliding mode controller has no singularity problem naturally by constructing a novel integral sliding mode surface based on the bi-limit homogeneous method. Moreover, the parametric adaptation technique is incorporated to estimate the total uncertainty indirectly. Benefiting from this development, the designed controller is smooth with no obvious chattering phenomenon and does not require any information on the upper bound of the total uncertainty. The attitude and angular velocity tracking errors under the designed controller can regulate to the minor fields about zero in fixed time. A remarkable feature of the designed controller is that it is not only robust against inertia uncertainties and external disturbances, but also insensitive to multiple types of actuator faults. Finally, simulation results show the effectiveness and merits of the presented control approach.

Sensorless HSPMSM Control of an Improved SMC and EKF Based on Immune PSO

Here, for controlling a high-speed flywheel permanent magnet synchronous motor (HSPMSM), a position sensorless control method for estimation of motor rotor position and speed is proposed to address the problems faced by mechanical position sensors of high cost, large size, and poor interference immunity. The extended Kalman filter (EKF) has difficulty obtaining the optimal covariance matrix when performing state estimation. Therefore, the particle swarm algorithm (PSO) with an immune mechanism is used to optimize the covariance matrix of the EKF. However, the EKF algorithm makes the system less robust due to its delay effect. Based on the traditional sliding mode control rate, the exponential convergence law is improved, and the continuous function sat(s) is used instead of the symbolic function sgn(s). This improves the convergence law and proves the asymptotic stability of the designed sliding mode variable structure controller based on Lyapunov’s stability theorem. Then, the novel control law is applied to the sliding mode surface (SMS). An ordinary sliding mode controller (OSMC) using a linear sliding mode controller (LSMC), a global sliding mode controller (GSMC) using a global sliding mode surface (GSMS), and an integral sliding mode controller (ISMC) using an integral sliding mode surface (ISMS) are designed for improving control. Joint simulation in MATLAB and Simulink verifies that the optimized EKF based on the immune PSO can improve precision and accuracy for controlling the electronic rotor position and speed. Comparing the new sliding mode controller with a traditional PI controller reveals that the proposed system has stronger resistance to load disturbance and better robustness.

Backstepping integral sliding mode control for pneumatic manipulators via adaptive extended state observers

In this paper, a nonlinear control strategy is proposed for a pneumatic manipulator based on an adaptive extended state observer and a backstepping integral sliding mode controller. A single degree of freedom dynamic model is established for the pneumatic manipulator using an Euler–Lagrange dynamic equation. The adaptive extended state observer is designed by an adaptive law to estimate uncertainties and disturbances. The backstepping integral sliding mode controller is proposed using an integral sliding mode surface based on backstepping technique. Comparative experiments verify effectiveness of the proposed nonlinear control strategy for the pneumatic manipulator.

Research on a Permanent Magnet Synchronous Motor Sensorless Anti-Disturbance Control Strategy Based on an Improved Sliding Mode Observer

This paper designs an improved sliding mode observer (ISMO) compound control scheme combined with a disturbance observer to solve the chattering and anti-disturbance problems of the traditional sliding mode observer (SMO) for permanent magnet synchronous motor (PMSM) in a sensorless control system. First, the sign function is replaced by an exponential type input function, and the fuzzy control rules are developed to automatically regulate the boundary layer control coefficient of the exponential input function, thereby changing the convergence characteristics of the exponential input function and improving the system observation accuracy. Then, the integral sliding mode surface and the quadratic radical term function of the square of the state variable are introduced to reduce system chattering. The proposed ISMO is proved using Lyapunov’s law to guarantee the whole system is stable. Based on the exponential input function and the integral sliding surface, an improved sliding mode disturbance observer (ISMDO) is constructed as a feed-forward compensator, which can optimize the dynamic performance of the improved observation system and ensure the strong robustness of the system by compensating the q-axis current. Finally, MATLAB/Simulink simulation and experimental platform verification have been carried out, which confirms the feasibility of the proposed composite control scheme.

Direct Speed Composite Control of SPMSM Drive System

The surface mounted permanent magnet synchronous motor (SPMSM) is a complex and nonlinear system. Therefore, single control method is difficult to perform well in different operations. For this reason, the direct speed composite control of SPMSM drive system is proposed in this paper. First, the control laws are deduced from the designed sliding mode surface and integral sliding mode surface under non-cascaded structure respectively. On the basis of guaranteeing the system stability, the dynamic weight factor is designed innovatively with speed error to perceive system state and allocate the ratio of two control laws in real time. Accordingly, the proposed composite control can be implemented by dynamic weight factor and make full use of two abovementioned control laws. Furthermore, by establishing ultra-local model of the SPMSM drive system, the nonlinearities, uncertainties and unknown disturbances of the system are estimated together and fed back to the controller, and the system robust improvement can be achieved consequently. At last, system simulation and experimental researches validate that the proposed direct speed composite control realizes smooth transition of two control methods and improves dynamic and steady-state control performance of the system.

A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors

To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.

Fixed-time generalized super-twisting control for path tracking of autonomous agricultural vehicles considering wheel slipping

Efficient path tracking control for autonomous agricultural vehicles (AAVs) is the key technology for realizing agriculture 4.0 and precision agriculture, which makes smart farms more sustainable, profitable, and eco-friendly. It is well recognized that model nonlinearity, unknown disturbances, and wheel slipping are common problems in practical AAV systems in operation. To tackle these issues and improve the path tracking performance, a novel fixed-time generalized super-twisting control scheme is proposed for AAVs in this paper. First, a fixed-time integral sliding mode surface is designed for the considered vehicle by fusing the lateral offset and heading offset together. Then, an innovative auxiliary system dynamics is constructed to collaborate with the foregoing sliding mode surface, compensating for the adverse effects of wheel slipping effectively. Subsequently, based on the kinematic offset model of AAVs, a new type of generalized super-twisting controller is designed to achieve superior path tracking with robustness. Unlike existing super-twisting controllers, the generalized super-twisting continuous controller can fully eliminate chattering by replacing the previous discontinuous terms with a nonsmooth term. Further, rigorous theoretical analysis is conducted by raising a fresh Lyapunov function to verify the closed-loop control system stability. Finally, extensive field experiments have been carried out to show that the proposed control scheme significantly outperforms typical comparative control schemes.

Discrete-Time Active Disturbance Rejection Current Control of PM Motor at Low Speed Using Resonant Sliding Mode

A discrete-time active disturbance rejection control (ADRC) method using resonant sliding mode is proposed to solve the disturbance characteristics of the current loop of permanent magnet (PM) motor at low speed. The extended state observer (ESO) is used to estimate the disturbance, but there is a contradiction between disturbance rejection and noise rejection in parameter design of ESO, which will affect the accuracy of the estimation, especially at low speed. In order to solve the problem, sliding mode control is combined with ADRC, while traditional integral sliding mode control still has poor rejection effect on the specific frequency harmonics. The resonant sliding mode is proposed to add resonance term to the integral sliding mode surface, which mitigates the impact of the disturbance that ESO fails to estimate on the tracking accuracy. Therefore, resonant sliding mode in the feedback control law of ADRC (RSM-ADRC) is employed to current loop to reduce the steady-state error. Meanwhile, the stability of the proposed algorithm is verified by discretization method. The steady and dynamic performances of the four control methods are compared through experiments to verify the feasibility and effectiveness of the proposed method. For example, when the reference current of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis is 0A and 1A respectively at 50rpm, the total harmonic distortion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current decreases from 1.68% to 0.64% and the 6th harmonic of current also drops to 0.135%. Despite the sudden change of inductance parameters, the steady-state current response is largely unaffected.

An Improved Integral Sliding Mode Control for PMSM Drives Based on New Variable Rate Reaching Law With Adaptive Reduced-Order PI Observer

This paper focuses on speed control in a permanent-magnet synchronous motor (PMSM). To promote the speed tracking performance and anti-disturbance property of PMSM speed regulation system against various unknown disturbances, such as parameter mismatch, load torque variation, friction force, and so on, an improved integral sliding mode control (IISMC) method based on a new variable rate reaching law (NVRRL) and an adaptive reduced-order proportional integral observer (AROPIO) is proposed. The NVRRL method can reduce chattering, and convergence time of the system state at the same time compared to the existing sliding mode reaching law. An anti-windup sliding mode surface is proposed to overcome the overshoot problem of the integral sliding mode surface when the reference speed is large and rises in steps or large ramps. To further improve the system tracking accuracy and anti-disturbance ability, an AROPIO is used to estimate lumped disturbances and provides feedforward compensation for the IISMC. The simulation and experimental results show that the proposed IISMC+AROPIO method not only achieves high speed tracking accuracy and fast convergence speed but also achieves strong anti-interference ability.

Fractional order neural sliding mode control based on the FO-Hammerstein model of piezoelectric actuator

Piezoelectric actuators (PEA) are extensively utilized in high-precision micro-measurement and operation. However, owing to the rate-dependent nature of its hysteresis, its accuracy in certain applications would suffer significantly, and the system would become unstable. To address this issue, a new method for developing a feedback control system that can reduce the rate-dependent impacts of PEA on the positioning system is provided using PEA as the research object. This strategy is based on the fractional order Hammerstein model (FO-Hammerstein). For the fractional order model, a novel fractional order integral sliding mode surface is proposed here that can accurately delineate the dynamic characteristics of PEA. This sliding mode surface is composed of a fractional polynomial and an integral term, which can better minimize static errors and monitor reference signals, and it is built using a fractional neural sliding mode control (BP-FSMC) method. The control technique can be extensively utilized in various systems, such as FO-Hammerstein and those described by the fractional transfer function. The research introduces a neural network and an artificial bee colony algorithm (DeC-ABC) that are used to alter the system’s parameters. The study’s findings reveal that a system with high resilience can follow the signals from both composite and single input sources. Compared with the fractional order sliding mode control approach on the basis of extended state observer, the fractional order sliding mode control method based on single parameter adaptive law and the proportional integral sliding mode control method on the basis of feedforward compensation, this method has a quicker response time and lower tracking error.

Improved Fixed-Time Stabilization of Fuzzy Neural Networks With Distributed Delay via Adaptive Sliding Mode Control

This paper investigates fixed-time stabilization of fuzzy neural networks with distributed delay by designing an adaptive sliding mode controller. Firstly, according to stability theory and related inequalities, a new fixed-time stability theorem is put forward, and the settling time is given. In order to stabilize the system, a new integral sliding mode surface is designed, and the corresponding sliding mode control strategy and adaptive sliding mode control strategy are established. Some criteria that can be obtained, and it is shown that the neuronal states of neural networks will arrive at the sliding surface in a fixed time, and then approach zero along the sliding surface. Compared with existing sliding mode control techniques, this work extends the previous related results by choosing different parameters of the controller and the sliding mode manifold to gain various protocols. Finally, two examples are provided to verify the validity of the theorems in this work.

Event‐triggered adaptive control based on integral sliding mode surface for a class of linear systems with matched disturbance

AbstractIn this paper, we propose an event‐triggered adaptive integral sliding mode control scheme for a class of linear systems with external disturbance. In this method, the controller is designed using a triggered‐state‐dependent integral sliding mode, which can ensure the robustness and avoid the shortcomings of traditional sliding mode arrival stage. The triggering mechanism utilizes a time‐varying trigger threshold instead of a traditional fixed threshold, which not only realizes the dynamic update of the control law, reduces the overhead of network communication but also ensures that the system trajectory enters the bounded area. The lower bound of inter event time guarantees the avoidance of the Zeno phenomenon. Next, in order to reduce the impact of high‐frequency chattering of the control signal effectively and allow the gain of the discontinuous control term to be adjusted automatically according to the rate of change of the disturbance, a dual‐layer nested adaptive gain scheme based on equivalent control is considered. This scheme does not require a priori boundedness of the disturbance and its rate of change. Through Lyapunov stability analysis, the event‐triggered adaptive sliding mode controller can make the system trajectory converge in finite time and ensure the robustness of the control. Finally, the simulation results verify the effectiveness and simplicity of this method.