Showing papers on "Sliding mode control published in 2019"

An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators

Abstract: This paper develops a novel control methodology for tracking control of robot manipulators based on a novel adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC). In this approach, a novel backstepping nonsingular fast terminal sliding mode controller (BNFTSMC) is developed based on an integration of integral nonsingular fast terminal sliding mode surface and a backstepping control strategy. The benefits of this approach are that the proposed controller can preserve the merits of the integral nonsingular fast terminal sliding mode control (NFTSMC) in terms of high robustness, fast transient response, and finite-time convergence, as well as backstepping control strategy in terms of globally asymptotic stability based on Lyapunov criterion. However, the major limitation of the proposed BNFTSMC is that its design procedure is dependent on the prior knowledge of the bound value of the disturbance and uncertainties. In order to overcome this limitation, an adaptive technique is employed to approximate the upper bound value; yielding an ABNFTSMC is recommended. The proposed controller is then applied for tracking control of a PUMA560 robot and compared with other state-of-the-art controllers, such as computed torque controller, PID controller, conventional PID-based sliding mode controller, and NFTSMC. The comparison results demonstrate the superior performance of the proposed approach.

Double-Loop Integral Terminal Sliding Mode Tracking Control for UUVs With Adaptive Dynamic Compensation of Uncertainties and Disturbances

Abstract: This paper focuses on the trajectory tracking control of unmanned underwater vehicles (UUVs) in the presence of dynamic uncertainties and time-varying external disturbances. Two adaptive integral terminal sliding mode control schemes, namely, adaptive integral terminal sliding mode control (AITSMC) scheme and adaptive fast integral terminal sliding mode control (AFITSMC) scheme are proposed for UUVs based on integral terminal sliding mode (ITSM) and fast ITSM (FITSM), respectively. Each control scheme is double-looped: composed of a kinematic controller and a dynamic controller. First, a kinematic controller is designed for each of the two control schemes. The two kinematic controllers are based on ITSM and FITSM, respectively. These kinematic controllers yield local finite-time convergence of the position tracking errors to zero meanwhile avoid the singularity problem in the conventional terminal sliding mode control (TSMC). Then, using the output of the kinematic controller as a reference velocity command, a dynamic controller is developed for each of the two control schemes. The two dynamic controllers are also based on ITSM and FITSM, respectively. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bound of the lumped system uncertainty which consists of dynamic uncertainties and time-varying external disturbances so that the prior knowledge of the upper bound of the lumped system uncertainty is not required. The estimated parameters are then used as controller parameters to eliminate the effects of the lumped system uncertainty. The convergence rate of the integral terminal sliding variable vector is investigated and the local finite-time convergence of the velocity tracking errors to zero in the ITSM or FITSM is obtained. Finally, based on the designed kinematic and dynamic controllers, the finite-time stability of the full closed-loop cascaded system is shown. The two proposed control schemes improve the tracking accuracy over the existing globally finite-time stable tracking control (GFTSTC) and adaptive nonsingular TSMC schemes, and enhance the robustness against parameter uncertainties and external disturbances over the GFTSTC scheme. Compared with the conventional adaptive integral sliding mode control (AISMC) scheme, the two proposed control schemes offer faster convergence rate and stronger robustness against dynamic uncertainties and time-varying external disturbances for the trajectory tracking control of UUVs due to involving the fractional integrator. Comparative numerical simulations are performed on the dynamic model of the Omni Directional Intelligent Navigator UUV for two trajectory tracking cases. The convergence rate and robustness to uncertainties and disturbances are quantified as the convergent time and bounds of the steady-state position and velocity tracking errors, respectively. The results show that the two proposed control schemes improve at least 20s in convergence rate and enhance about 2% robustness in position tracking and 20% robustness in velocity tracking over the AISMC scheme.

Fuzzy-Model-Based Sliding Mode Control of Nonlinear Descriptor Systems

Abstract: This paper addresses the problem of sliding mode control (SMC) for a type of uncertain time-delay nonlinear descriptor systems represented by T–S fuzzy models. One crucial contributing factor is to put forward a novel integral fuzzy switching manifold involved with time delay. Compared with previous results, the key benefit of the new manifold is that the input matrices via different subsystems are permitted to be diverse, and thus much more applicability will be achieved. By resorting to Frobenius’ theorem and double orthogonal complement, the existence condition of the fuzzy manifold is presented. The admissibility conditions of sliding motion with a strictly dissipative performance are further provided. Then, the desired fuzzy SMC controller is synthesized by analyzing the reachability of the manifold. Moreover, an adaptive fuzzy SMC controller is also proposed to adapt the input saturation and the matched uncertainty with unknown upper bounds. The feasibility and virtue of our theoretical findings are demonstrated by a fuzzy SMC controller implementation for a practical system about the pendulum.

Adaptive Sliding Mode Consensus Tracking for Second-Order Nonlinear Multiagent Systems With Actuator Faults

Abstract: This paper investigates the consensus tracking problem of second-order nonlinear multiagent systems (MAS) with disturbance and actuator fault by the sliding mode control method. The communication topology of the MAS is directed and only part of the followers have access to the leader’s information. First, a discontinuous sliding mode tracking protocol is studied for consensus tracking of the MAS. Second, to address the shortcoming of chattering and difficulty of setting the control gain in the discontinuous protocol, a continuous sliding mode tracking protocol with an adaptive mechanism is developed. The adaptive mechanism will adjust the gain of the control automatically and enable the tracking protocol to work well without prior knowledge of the MAS. Third, the performance of the adaptive sliding mode protocol for consensus tracking of the MAS in the presence of actuator faults of biased fault and partial loss of effectiveness fault is further investigated. Finally, numerical simulations are performed to illustrate the efficiency of the theoretical results.

A Disturbance Observer Based Sliding Mode Control for a Class of Underactuated Robotic System With Mismatched Uncertainties

Abstract: In this note, a high-order disturbance observer for a class of underactuated robotic systems with mismatched uncertainties is proposed To improve its estimation performance, a choice method of optimal gain matrices of the high-order disturbance observer is obtained as the solution of an optimization problem A high-order disturbance observer based sliding mode control method is also designed for this class of underactuated robotic system with mismatched disturbance The stabilities of both the disturbance observer and the controlled closed-loop system are proved by the Lyapunov theorem Simulations on a benchmark Acrobot system demonstrate the efficiency of proposed approaches

Adaptive Neural-Fuzzy Robust Position Control Scheme for Maglev Train Systems With Experimental Verification

Abstract: The magnetic suspension system of a low-speed maglev train is presented in this paper. The design and realization of the magnetic suspension controller are discussed, and a nonlinear mathematical model of the magnetic suspension system is built. Then, the proportion integration differentiation controller is investigated, which indicates that it is sensitive to disturbances. To reject the disturbance and parameter perturbations, an adaptive neural-fuzzy sliding mode controller is presented, which employs a sliding mode control, adaptive-fuzzy approximator, and the neural-fuzzy switching law. The sufficient simulation and experimental results are included to demonstrate that the presented robust controller significantly reduces the impact of the disturbance and parameter perturbations with a smooth control current.

Extended State Observer-Based Sliding Mode Control of an Omnidirectional Mobile Robot With Friction Compensation

Abstract: This paper presents a reduced-order extended state observer (ESO) based sliding mode control scheme for friction compensation of a three-wheeled omnidirectional mobile robot. Compared with previous works, the proposed control approach is attractive from an implementation point of view. It does not require any explicit friction model, with quite low computation cost. First, a dynamic model with unknown friction forces is given. Then, the controller is designed, consisting of two parts. One part of the control effort is to compensate the friction effects, which are estimated by a reduced-order ESO without using any explicit friction model. The inverse of inertia matrix is also avoided in the proposed reduced-order ESO. The other part of the control effort is designed based on a second-order sliding mode technique known as super-twisting algorithm, in presence of parameter uncertainties. In addition, stability analysis of the designed control system is presented. Extensive experiments are conducted to verify the effectiveness and robustness of the proposed control design in compensating different friction effects.

Continuous Sliding-Mode Control Strategies for Quadrotor Robust Tracking: Real-Time Application

Abstract: The design of robust tracking control for quadrotors is an important and challenging problem nowadays. In this paper, a robust tracking output-control strategy is proposed for a quadrotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a finite-time sliding-mode observer, which estimates the full state from the measurable output and identifies some types of disturbances. It is also composed of a combination of PID controllers and continuous sliding-modes controllers that robustly track a desired time-varying trajectory with exponential convergence despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on the input-to-state stability (ISS) and finite-time ISS properties. Finally, experimental results in real time show the performance of the proposed control strategy.

Precision Motion Control of Permanent Magnet Linear Synchronous Motors Using Adaptive Fuzzy Fractional-Order Sliding-Mode Control

Abstract: The aim of this study is to develop an adaptive fuzzy fractional-order sliding-mode control (AFFSMC) strategy to control the mover position of a permanent magnet linear synchronous motor (PMLSM) system. First, the mathematical model of the PMLSM is investigated by using the principle of field oriented control. Subsequently, a fractional-order sliding-mode control (FSMC) is designed by means of a new fractional-integral sliding surface. Because it is difficult to determine the hitting control gain for the FSMC in practice, the AFFSMC is further developed in which an uncertainty observer is developed to observe uncertainties while an adaptive fuzzy reaching regulator is designed to concurrently compensate for observation deviations and suppress the chattering phenomenon. The adaptive laws are derived to tune the control parameters online based on the Lyapunov stability theorem. Thus, the uncertainty bound information is not required while the chattering can be attenuated. Finally, experiments demonstrate that the proposed AFFSMC system performs the robust control performance and precise tracking response for the PMLSM drive system against the parameter variations and external disturbances.

Event-Triggered Sliding Mode Control of Discrete-Time Markov Jump Systems

Abstract: This paper studies the problem of event-triggered sliding mode control of discrete-time Markov jump systems (MJSs). Two kinds of classical control schemes, which are observer-based control and state-feedback control schemes, are employed to handle the proposed synthesis problem. The event-triggered observer-based sliding mode controller and event-triggered state-feedback sliding mode controller are established by plunge of discrete-time event detectors into the studied control system, respectively. Moreover, the proposed event-triggered sliding mode controllers can guarantee the MJSs to be stochastically stable with ${H}_{\infty}$ performance, and ensure the finite-time reachability of the specified sliding manifold. Simulation results are provided to illustrate the effectiveness of the proposed theoretical results.

An Adaptive Droop Control Scheme for DC Microgrids Integrating Sliding Mode Voltage and Current Controlled Boost Converters

Abstract: One of the most widely used techniques for controlling the dc microgrid is the droop control method. The associated problems of the droop-based systems, such as the current sharing errors and the voltage deviation are solved using current sharing loops and secondary control loop, respectively. This paper presents an adaptive droop scheme for dc microgrids to overcome the non-linearity of the system. The droop resistance is adjusted using the adaptive PI controller to eliminate the current sharing error of each unit in the microgrid. In addition, another adaptive PI controller is dedicated for the secondary loop to regulate the dc bus voltage of the microgrid by shifting the droop lines. In the proposed scheme, only the current and voltage at the dc bus of the microgrid need to transmit through low-bandwidth communication channels to individual units. Moreover, the sliding mode control, which is distinguished by robustness and fast dynamic response, is utilized to manipulate the output voltage and the input current of each converter, instantaneously. The dynamic performance of the proposed adaptive droop scheme is evaluated using the PSCAD/EMTDC simulation package.

Observer-Based Adaptive Sliding Mode Control of NPC Converters: An RBF Neural Network Approach

Abstract: This paper proposes a novel control strategy for three-level neutral-point-clamped (NPC) power converter. The proposed control scheme consists of three control loops, i.e., instantaneous power tracking control loop, voltage regulation loop, and voltage balancing loop. First, in the power tracking control loop, a set of adaptive sliding mode controllers are established to drive the active and reactive power tracking to their desired values via radial basis function neural network technology. In the voltage regulation loop, an efficient but simple adaptive controller is designed to regulate dc-link output voltage where the load is considered as an external disturbance. Moreover, a composite controller is developed in the voltage balancing loop to ensure imbalance voltages between two dc-link capacitors close to zero, in which a reduced-order observer is used to estimate sinusoidal disturbance improving the converter performance. The effectiveness and superiority of the proposed control strategy for the NPC power converter are compared with other control schemes through experimental results.

Adaptive Fractional Fuzzy Integral Sliding Mode Control for PMSM Model

Abstract: This paper aims to address the stabilization problem of permanent magnet synchronous motor (PMSM) based wind energy conversion system (WECS) through a novel adaptive fractional fuzzy integral sliding mode control scheme in contrast to the traditional integer order control schemes. The main objective of modeling the fractional order control for nonlinear PMSM is to enhance the convergence rate which is effectively better when compared to integer order control schemes. In addition, this paper intensively investigates the performance of fractional order controllers in both PMSM and surface-mounted PMSM-based WECS through analyzing the global stability of closed-loop system based on Lyapunov stability theory. In this regard, the nonlinear PMSM model is transformed into equivalent linear submodels through an effective Takagi–Sugeno fuzzy membership rules. Then, a novel automated (adaptive) controller is designed along with fractional sliding surface, which involves an integral term to control the considered PMSM. In general, adaptive controllers are much more effective than manual controllers. Further, the sufficient conditions are derived in terms of linear matrix inequalities via constructing the novel fractional fuzzy Lyapunov functional with quadratic terms, which guarantees the global stabilization of PMSM-based WECS. Overall performance and effectiveness of the proposed theoretical results are demonstrated through numerical simulations.

Robust Speed Control of PMSM Using Sliding Mode Control (SMC)—A Review

Abstract: Permanent magnet synchronous motors (PMSMs) are known as highly efficient motors and are slowly replacing induction motors in diverse industries. PMSM systems are nonlinear and consist of time-varying parameters with high-order complex dynamics. High performance applications of PMSMs require their speed controllers to provide a fast response, precise tracking, small overshoot and strong disturbance rejection ability. Sliding mode control (SMC) is well known as a robust control method for systems with parameter variations and external disturbances. This paper investigates the current status of implementation of sliding mode control speed control of PMSMs. Our aim is to highlight various designs of sliding surface and composite controller designs with SMC implementation, which purpose is to improve controller’s robustness and/or to reduce SMC chattering. SMC enhancement using fractional order sliding surface design is elaborated and verified by simulation results presented. Remarkable features as well as disadvantages of previous works are summarized. Ideas on possible future works are also discussed, which emphasize on current gaps in this area of research.

Robust Adaptive Nonsingular Terminal Sliding Mode Control for Automatic Train Operation

Abstract: In this paper, we develop robust adaptive nonsingular terminal sliding mode (NTSM) control methodologies to solve the position and the velocity tracking control problem of the automatic train operation (ATO) system subject to unknown parameters, model uncertainty, and external disturbances. A novel nonlinear nonsingular terminal sliding manifold is proposed by considering that its parameter is unknown, which need to be estimated via a proposed non-negative adaptive law. And a corresponding novel robust adaptive NTSM control strategy, which enables the position tracking error and the velocity tracking error of the ATO system to converge to zero, and eliminates the singularity caused by terminal sliding mode controller, is proposed. Furthermore, unknown parameters of the sliding manifold and the ATO system can be estimated online by the proposed methodology. Simulation results show the effectiveness of the proposed methodologies in this paper.

Adaptive Sliding Mode Control of Vehicular Platoons With Prescribed Tracking Performance

Abstract: This paper investigates a vehicular platoon control problem with prescribed tracking performance in the presence of actuator saturation, uncertain parameters, and unknown disturbances. Two adaptive sliding mode control schemes based on leader–predecessor and leader–bidirectional information flows are presented to ensure string stability and strong string stability, respectively, with a prescribed tracking performance. The actuator saturation nonlinearity is addressed by approximating it with a smooth hyperbolic tangent function. The effects of uncertain parameters and exogenous disturbances are dealt with by introducing a set of adaptation laws. The effectiveness of the proposed control schemes is demonstrated via numerical simulation results.

MME-EKF-Based Path-Tracking Control of Autonomous Vehicles Considering Input Saturation

Abstract: This paper investigates the path-tracking control issue for autonomous ground vehicles with the integral sliding mode control (ISMC) considering the transient performance improvement. The path-tracking control is converted into the yaw stabilization problem, where the sideslip-angle compensation is adopted to reduce the steady-state errors, and then the yaw-rate reference is generated for the path-tracking purpose. The lateral velocity and roll angle are estimated with the measurement of the yaw rate and roll rate. Three contributions have been made in this paper: first, to enhance the estimation accuracy for the vehicle states in the presence of the parametric uncertainties caused by the lateral and roll dynamics, a robust extended Kalman filter is proposed based on the minimum model error algorithm; second, an improved adaptive radial basis function neural network (RBFNN) considering the approximation error adaptation is developed to compensate for the uncertainties caused by the vertical motion; third, the RBFNN and composite nonlinear feedback (CNF) based ISMC is developed to achieve the yaw stabilization and enhance the transient tracking performance considering the input saturation of the front steering angle. The overall stability is proved with Lyapunov function. Finally, the superiority of the developed control strategy is verified by comparing with the traditional CNF with high-fidelity CarSim-MATLAB simulations.

Robust Adaptive Sliding Mode Control for Switched Networked Control Systems With Disturbance and Faults

Abstract: In this paper, the problem of switched networked control systems (SNCSs) with external disturbance and actuator /sensor faults is investigated. Meanwhile, the communication constraints such as network-induced delay, packet dropouts, and packet disorder are considered in a communication network. A robust adaptive sliding mode control method is proposed for disturbance damping and faults tolerance, which is designed on an observer and second-order discrete-time adaptive sliding mode function. Furthermore, the reachability of sliding motion is proved. Then, the networked predictive control method is employed to compensate the communication constraints. Finally, the stability of the closed-loop system is proved, and a numerical example and a mechanical system simulation example are executed to verify the effectiveness of the proposed method.

A Novel Sliding Mode Estimation for Microgrid Control With Communication Time Delays

Abstract: This paper deals with the sliding mode estimation for microgrid with time delays. Delay has a great impact on large power grids’ management for microgrid, which terribly reduces the stability and quality of microgrid. Random delay caused by load dependent congestion, constant transmission delay and constant delay in microgrid are considered in this paper. To eliminate the adverse effects of delays, a novel sliding mode estimation-based controller is designed to predict time delays and microgrid states, and to reject the disturbance of estimation errors. The mathematical inverter model containing electrical characteristics is regarded as the model of practical microgrid system. Delay estimation with learning parameter and state estimation are derived according to the inverter model. By regarding estimation errors as disturbance of sliding mode control (SMC), the control signal of SMC is adaptively changed in the sliding mode estimation-based control loop to ensure the stability of system and accuracy of estimation. Exponential reaching law (ERL) is implemented to improve the chattering issues and reaching performance of SMC. Lyapunov approach is exploited to analyze the stability of sliding motion. Finally, the proposed SMC strategy is validated by simulation experiments of a microgrid with time delays.

Finite-Time Adaptive Fuzzy-Neural-Network Control of Active Power Filter

Abstract: In this paper, an adaptive fuzzy-neural-network (AFNN) control using nonsingular terminal sliding mode control is proposed for active power filter (APF) as a current controller to attenuate the effect of unknown external disturbances and modeling uncertainties. First, the dynamic model for APF is built in which both the system parameter variations and external disturbance are considered. Then, a nonsingular terminal sliding mode control based on the backstepping (NTSMB) approach is presented for the current control system to solve singularity point problem and realize the fast and finite-time convergence. Moreover, AFNN is designed to relax the requirement of the prior knowledge of system parameters to improve the robustness of NTSMB. In the AFNN strategy, AFNN framework is designed to mimic the NTSMB, where the parameters are adjusted online by the adaptive law derived from the projection algorithm and the Lyapunov stability analysis, to guarantee tracking performance and stability of the closed-loop system. Simulation studies demonstrate that the proposed control methods exhibit excellent performance in both steady-state and transient operation compared to traditional sliding mode control. Experimental results are provided using a fully digital control system in order to validate the performance of the proposed controller.

Adaptive Backstepping Sliding Mode Control for Boost Converter With Constant Power Load

Abstract: The negative impedance characteristics of a constant power load (CPL) can easily lead to the instability of the DC bus voltage. To improve the stability of the DC bus voltage, an adaptive backstepping sliding mode control strategy for a boost converter with the CPL in DC microgrid is proposed. First, to carry out the backstepping control, the zero dynamic stability of the system under different output functions is studied by using input-output exact feedback linearization theory. The model is transformed into a linear system in Brunovsky canonical form, which solves the nonlinear problem caused by the CPL and the non-minimum phase problem of the boost converter. Then, under the premise of ensuring large signal stability, an adaptive mechanism is introduced into the design of the backstepping sliding mode control. The adaptive backstepping sliding mode controller is designed by adaptively updating the switching gain in real time. Furthermore, the Lyapunov theory is used to prove the global asymptotic stability of the overall closed-loop system. Finally, the numerical simulation and experimental results show that the proposed control strategy has better dynamic regulation performance and stronger robustness compared with the conventional double closed-loop PI control method.

Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators

Abstract: A robust adaptive control method is proposed in this paper based on recurrent fuzzy wavelet neural networks (RFWNNs) system for industrial robot manipulators (IRMs) to improve high accuracy of the tracking control. The RFWNNs consist of four layers, and second layer has the feedback connections. Wavelet basis function is used as fuzzy membership function. In general, it is not easy to adopt a model-based method to achieve this control object due to the uncertainties of the IRM, such as unknown dynamic, disturbances and parameter variations. To solve this problem, all the parameters of the RFWNNs system are tuned online by an adaptive learning algorithm, and online adaptive control laws are determined by Lyapunov stability theorem. In addition, the robust controller is designed to deal with the approximation error, optimal parameter vectors and higher-order terms in Taylor series. Therefore, with the proposed control, the desired tracking performance, stability and robustness of the closed-loop manipulators system are guaranteed. The simulations and experimental performed on a three-link IRMs are provided in comparison with fuzzy wavelet neural network and robust neural fuzzy network to demonstrate the effectiveness and robustness of the proposed RFWNNs methodology.

New Results on Sliding-Mode Control for Takagi–Sugeno Fuzzy Multiagent Systems

Abstract: This paper investigates the sliding-mode control (SMC) problem of Takagi–Sugeno (T–S) fuzzy multiagent systems (MASs). A cooperative fuzzy-based dynamical sliding-mode (SM) controller is designed and the overall closed-loop T–S fuzzy MAS is constructed. A new model transformation method for T–S fuzzy MASs is presented to transform the fuzzy weighting matrix into a set of fuzzy weighting scalars. By applying the method of linear matrix inequality, a general stability analysis approach for T–S fuzzy MASs is proposed. Moreover, the energy-cost constraint problem is studied by using the linear quadratic regulator method. Finally, numerical examples are provided to illustrate the effectiveness of the proposed theoretical approaches and the improved performance compared to existing results.