Adaptive Sliding Mode Technique Research Articles

Enhanced path tracking control of hydraulic support pushing mechanism via adaptive sliding mode technique in coal mine backfill operations

The hydraulic support pushing mechanism is the primary equipment utilized in coal mine backfill operations, playing a crucial role in enhancing filling efficiency, ensuring a stable filling body, and managing gob safety. This paper focuses on analyzing the dynamic model and the interrelationship of the hydraulic cylinder, which serves as the power source for the pushing mechanism. To address the intricate coupling effects arising from the hydraulic cylinders and the displacement-force induced by the shared pump, this study employs feedforward compensation for decoupling analysis. Additionally, this article introduces an adaptive sliding mode approach law and an adaptive synovial controller to combat issues such as buffeting and interference. The simulation results demonstrate that the sliding mode reaching law proposed in this paper can achieve a stable state in approximately 3 seconds, which is significantly better than other methods. Combining the experimental equipment information from a mining area in Hebei Province with Amesim-Simulink simulation results, it is evident that the adaptive sliding mode controller exhibits an error range between approximately 1.33E-4 and 1.5E-4 during the stable phase. This performance surpasses traditional PI and fuzzy PID controllers in terms of path tracking ability, effectively enabling precise control of the filling support pushing mechanism.

Sliding Mode-Based Distributed Trajectory Tracking Control of Four-body Train Systems

This paper considers the speed tracking of a four-body train system modelled mathematically based on Newton’s second law, which is described by a large-scale interconnected system with four subsystems. Uncertainties are included in the systems to represent the potential impacts on system performance caused by mechanical wear and external environmental changes. An adaptive sliding mode technique is employed to design a distributed control scheme to guarantee tracking accuracy. Coordinate transformations are introduced to transfer the model of train systems to a system in regular form to facilitate the design of the hyperplane and controllers. The Barbashin-Krasovskii theorem is employed to show the reachability of the hyperplane. In simulations, the Gaussian function is chosen as the desired signal, representing time-varying characteristics relevant to real-world situations, and the result demonstrates the feasibility of the proposed control strategy.

Consensus tracking for a class of fractional-order non-linear multi-agent systems via an adaptive dynamic surface controller

In this paper we investigate bottlenecks in adaptive dynamic surface control (DSC) and unveil an innovative consensus tracking controller to track the desired trajectory for a class of fractional-order multi-agent systems with non-linear dynamics. The study derives an algorithm by implementing graph theory and the DSC method. The main approaches in the control of fractional-order systems are the DSC and the adaptive DSC techniques to avoid the computational complexity of fractional-order virtual control law. According to these techniques, a virtual control law is formulated and the proposed controller is passed through a fractional-order dynamic surface. By employing the DSC and adaptive DSC laws, we demonstrate that the desired consensus tracking between agents can be ensured. To verify the performance of the new approach, we simulate the desirable scenarios and evaluate the results against a popular adaptive sliding mode technique.

Secure consensus control for multi-agent systems under communication constraints via adaptive sliding mode technique

The consensus tracking problem is investigated for a class of multi-agent systems (MASs) under communication constraints. In particular, as a result of the impact of amplitude attenuation and random interference, communication among followers may inevitably suffer from the fading phenomenon. Meanwhile, the controllers may also be subject to malicious deception attacks, which will disrupt the correct operation of the MASs. Thus, the agents can only update their states based on fading information exchanged with their neighbors and the false control input under attacks. The consensus tracking error variables are first designed via the fading signal received from neighbors. Then, an online estimation strategy is introduced to estimate the unknown attacks, based on which the adaptive sliding mode controller is designed to attenuate the effect of the time-varying attacks on MASs. Convergence analysis of the MASs under the designed control strategy is provided by using the Lyapunov stability theory and adaptive sliding mode control method. Finally, the effectiveness of the theoretical results is verified via numerical simulations.

A FPGA Based PI Adaptive Sliding Mode Controller for PEM Fuel Cell with Boost Converter

Proton exchange membrane (PEM) is one of the most popular fuel cells for renewable energy production, and this paper presents a DC/DC boost converter structure to improve energy efficiency. To achieve high output power as well as constant output voltage, a combined method consisting of proportional-integral controller and adaptive sliding mode technique is designed. Also, due to the use of adaptive technique, the proposed technique has the ability to cover the effects of uncertainty with an unknown high limit and in addition to improving the quality of output power and voltage of PEM, it eliminates permanent tracking error and guarantees closed loop system stability. To show the operational implementation capability and flexibility of the method, FPGA has been used, which in addition to showing real-time performance, provides the ability to execute the controller at high speeds. Operationality and the possibility of practical implementation of the planned scheme on the existing systems provide the possibility of increasing the efficiency of energy extraction without further investment. The stability of the closed-loop system is achieved using Lyapunov technique and the results of simulation and comparison indicate the optimal performance of the system under the planned scheme and high efficiency in comparison with existing approaches.

A FPGA based PI adaptive sliding mode controller for PEM fuel cell with boost converter

Proton exchange membrane (PEM) is one of the most popular fuel cells for renewable energy production, and this paper presents a DC/DC boost converter structure to improve energy efficiency. To achieve high output power as well as constant output voltage, a combined method consisting of proportional-integral controller and adaptive sliding mode technique is designed. Also, due to the use of adaptive technique, the proposed technique has the ability to cover the effects of uncertainty with an unknown high limit and in addition to improving the quality of output power and voltage of PEM, it eliminates permanent tracking error and guarantees closed loop system stability. To show the operational implementation capability and flexibility of the method, FPGA has been used, which in addition to showing real-time performance, provides the ability to execute the controller at high speeds. Operationality and the possibility of practical implementation of the planned scheme on the existing systems provide the possibility of increasing the efficiency of energy extraction without further investment. The stability of the closed-loop system is achieved using Lyapunov technique and the results of simulation and comparison indicate the optimal performance of the system under the planned scheme and high efficiency in comparison with existing approaches.

Dual Penta-Compound Combination Anti-Synchronization with Analysis and Application to a Novel Fractional Chaotic System

This paper studies a fractional-order chaotic system with sine non-linearities and highlights its dynamics using the Lyapunov spectrum, bifurcation analysis, stagnation points, the solution of the system, the impact of the fractional order on the system, etc. The system considering uncertainties and disturbances was synchronized using dual penta-compound combination anti-synchronization among four master systems and twenty slave systems by non-linear control and the adaptive sliding mode technique. The estimates of the disturbances and uncertainties were also obtained using the sliding mode technique. The application of the achieved synchronization in secure communication is illustrated with the help of an example.

Sliding Mode with Adaptive Control of Robot Manipulator Trajectory Tracking using Neural Network Approximation

This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique with RBF Neural Network (ASMCNN) for Robotic Manipulator tracking control in presence of uncertainities and disturbances. The aim is to design an effective trajectory tracking controller without any modelling information. The ASMCNN is designed to have robust trajectory tracking of Robot Manipulator, which combines Neural Network Estimation with Adaptive Sliding Mode Control. The RBF model is utilised to construct a Lyapunov function-based adaptive control approach. Simulation of the tracking control of a 2dof Robotic Manipulator in the presence of unpredictability and external disruption demonstrates the usefulness of the planned ASMCNN.

Analysis and Application Using Quad Compound Combination Anti-synchronization on Novel Fractional-Order Chaotic System

In this manuscript, a novel fractional-order chaotic model has been investigated. The characteristic dynamics of the model have been investigated using various tools such as Lyapunov dynamics, bifurcation diagrams, equilibrium point analysis, Kaplan York dimension, existence and uniqueness of solution. The Lyapunov spectrum, bifurcation diagrams and attractors are discussed over a range of fractional order of 0.8 to 1. The considered system is synchronized by using a novel technique quad compound combination anti-synchronization using two control methods, viz. nonlinear and adaptive sliding mode technique. The obtained results of synchronization are compared with some existing literature and also illustrated its application in secure communication.

Adaptive sliding mode robust control based on multi‐dimensional Taylor network for trajectory tracking of quadrotor UAV

In this study, multi-dimensional Taylor network (MTN) inspired sliding mode robust control theory based adaptation laws are proposed to realise trajectory tracking for a quadrotor unmanned aerial vehicle. Compared with existing methods, the composite disturbance considered in this study includes external multiple interference and fuselage parameter perturbation, which is more in accord with reality. Through a linear state transformation, the uncertain coefficients and unknown external disturbances are grouped together and the original kinetic model is decoupled into two subsystems of position and attitude that make the control design become feasible. MTNs are used to compensate the lumped non-linearities, and the adaptive sliding mode technique is employed to construct the controller. Different from the controllers based on neural networks, MTN contains only addition and multiplication, which greatly lessens the computational complexity and improves the real-time performance. By the Lyapunov theory, the position tracking error, attitude tracking error and fuselage load identification error are bounded in probability have been proved and the stability of the system is guaranteed. Simulation studies demonstrate the effectiveness and superiority of the proposed trajectory tracking control scheme.

Multiswitching hybrid synchronization using disturbance observer adaptive sliding mode control on fractional order chaotic system

In this manuscript we have analysed identical financial systems of fractional order with external disturbances taken into consideration and introduced the disturbance observer to estimate the disturbance. We have applied adaptive sliding mode technique to synchronize these identical systems. Numerical simulations have been performed in MATLAB to validate the effectiveness of the method proposed. The obtained results show the usefulness and suitability of the method used to achieve the synchronization. A comparison has been made between the obtained and published results and application in secure communication has also been displayed.

Adaptive Robust Tracker Design for Nonlinear Sandwich Systems Subject to Saturation Nonlinearities

SUMMARYThis paper addresses the tracking problem for uncertain nonlinear sandwich systems that consist of two nonlinear subsystems and saturation nonlinearity, which is sandwiched between the subsystems. The considered sandwich system is also subject to a nonsymmetric input saturation constraint. Due to the nonsmooth characteristics of sandwiched saturation nonlinearity and also the input saturation function, the design procedure deals with hard challenges. To overcome these difficulties, a recursive approach is suggested that consists of two phases. For the implementation of the proposed approach, a tracking problem is solved in each phase. In the first phase, the second subsystem with sandwiched saturation nonlinearity is considered and the output tracking problem of the desired time-varying reference signal is solved using backstepping method. The outcome of the first phase is the desired reference signal that should be tracked by the first subsystem in the next phase. In the second phase, the robust control input is designed for the first subsystem by employing adaptive sliding mode technique such that, despite the nonsymmetric input saturation constraint, model uncertainty and external disturbances, the output of the first subsystem follows the desired signal that is obtained in the previous phase. The simulation results for a mechanical sandwich system are illustrated to verify the effectiveness of the proposed control method.

Adaptive sliding mode observer–based decentralized control design for linear systems with unknown interconnections

In this study, a class of linear interconnected systems with unknown interconnections between subsystems is considered. Primarily, an observer is designed to reconstruct an equivalent of unknown interconnections that are considered uncertain. A decentralized controller will be thereafter designed to keep the stability of the original system when the estimated system is at risk of instability due to the lack of information on interconnections. To design a decentralized observer and to estimate states of each subsystem, without knowing the relations between subsystems, a combination of Luenberger observer along with the adaptive sliding mode technique is used. Because the interconnected system might generally be unstable, a state feedback controller is used to stabilize each subsystem using estimated states together with the output of other subsystems. The stability of the system and the convergence of the discrepancy between real states and that of estimated are guaranteed, gaining the Lyapunov theory. Simulation results signify that the proposed decentralized controller based on a new adaptive sliding mode observer is highly efficient for linear interconnected systems with unknown interconnections.

A Novel Adaptive Speed Observer Using Neural Network and Sliding-Mode for SPIM Drives

In this paper, a novel Stator Current Based Model Reference Adaptive System (SC_MRAS) speed estimation scheme using neural network (NN) and Sliding Mode (SM) is proposed to improve the performance of the MRAS speed observer for high-performance Six Phases Induction Motor (SPIM) drives, especially at low and zero speed region, where the poor performance of observers is still always a large challenge. In this novel SC_MRAS scheme, a two-layer linear NN, which has been trained online by means of the Total Least Squares (TLS) algorithm, is used as an adaptive model to estimate the stator current and this model is employed in prediction mode. These novel proposed can ensure that the whole drive system achieves faster satisfactory torque and speed control and strong robustness, the observer operate better accuracy and stability both in transient and steady-state operation. Especially, in this proposed observer, the rotor flux, which is needed for the stator current estimation of the adaptive model and providing to the controller, is identified based on adaptive SM technique. The improvement of Rotor Flux Estimation for SC_MRAS-Based Sensorless SPIM Drives help to eliminate the disadvantages in SC_MRAS based observer such as stator resistance sensitivity, and flux open loop integration which may cause dc drift and initial condition problems or instability in the regenerating mode of operation, therefore, enhancing the rotor flux estimation, speed estimation and control accuracy at very low and zero stator frequency operation help improve the overall observer and drive system performance. The indirect field oriented control (IFOC) for speed control of a sensorless SPIM drive using the proposed observer is built by MATLAB/ Simulink. The simulation results are presented under sensorless speed control performance to validate the effectiveness of the proposed estimation and control algorithms.

Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation

Proton exchange membrane fuel cell (PEMFC), according to its merits of high energy density, zero emission, and low noise, has been widely applied in industrial appliances. A full bridge converter is used to implement PEMFC-powered DC motor bidirectional rotation in this paper. For the sake of the regulations of DC motor angular velocity as well as bus voltage, an adaptive backstepping sliding-mode control (ABSMC) technique integrated with Chebyshev neural network (CNN) is proposed. Based on the equivalent-circuit method, the control-oriented model of the PEMFC-powered motor system is structured. By constructing Lyapunov function, the adaptive laws and control laws can be obtained to achieve bus voltage and angular velocity regulations simultaneously. Moreover, the proposed neural network is applied to estimate the uncertainties of the system through orthogonal basis Chebyshev polynomials. To highlight the advantages of proposed technique, a proportional-integral (PI) control was introduced subsequently and two controllers were compared via numerical simulations. The simulation results demonstrate that CNN estimation method in conjunction with backstepping sliding-mode shows fast and accurate response even though the existence of system uncertainties and external disturbances.

Synchronization of Non-Integer Complex Chaotic Systems with Uncertainty and Disturbances via Adaptive Sliding Mode Technique

In this paper we concern the adaptive sliding mode control technique for synchronization of fractional order chaotic systems with uncertainties and disturbances. This technique is used to design control law through suitable sliding surface and estimate the external disturbances. Computational results using MATLAB verified the effectiveness of the proposed scheme.

Iterative Learning Control Combination with Adaptive Sliding Mode Technique for a Hypersonic Vehicle

Aiming at the complicated nonlinearities, high uncertainties and strong coupling of hypersonic vehicle, a new adaptive iterative learning control method is put forward. The proposed controller combined iterative learning control with sliding mode control. Firstly, a nonlinear design model for the attitude control is established according to the attitude motion equations of hypersonic vehicle. With regard to a class of nonlinear system, a new iterative learning control combination with sliding mode control is proposed and then applied to the nonlinear design model. Finally, Lyapunov-like function method is used to prove the boundedness of all signals of the closed-loop system and the convergence of the tracking errors to zero over iterations. Simulation results are provided to show the effectiveness and robustness of the proposed control scheme compared with traditional sliding mode control. Furthermore, it also possesses stronger robustness against uncertainties and disturbances.

Fuzzy Disturbance Observer-Based Adaptive Sliding Mode Control for Reusable Launch Vehicles With Aeroservoelastic Characteristic

This paper investigates the problem of attitude tracking control for reusable launch vehicles (RLVs) with aeroservoelastic characteristic and disturbances in reentry phase. An aeroservoelastic model for reentry RLV is first established, where the synthetic disturbances are considered as well. Then a novel disturbance observer combined with fuzzy logic system is constructed by using both fuzzy approximation error and observation error to provide the disturbance estimation. The fuzzy disturbance observer (FDO) can be employed to the control scheme to counteract the perturbations and guarantee the estimation errors for converging to a small neighborhood around origin. Incorporated with the designed FDOs, the adaptive sliding mode technique is proposed for developing attitude angle and angular rate subsystem controllers, respectively, to ensure the reentry attitude tracking performance. Rigorous proof shows that the uniform stability of the closed-loop system under the proposed control law can be guaranteed by using Lyapunov technique. Finally, numerical simulations are conducted in this paper to illustrate the effectiveness of the developed technique for the RLV.

Adaptive Backstepping Sliding Mode Control for Equilibrium Position Tracking of an Electrohydraulic Elastic Manipulator

The electrohydraulic elastic manipulator (EEM) includes an electrohydraulic servo system and a variable stiffness mechanism. It is a complex system with nonlinear elements, such as friction, parametric uncertainties, and modeling error as well as coupling torques in the elastic joint. This paper focuses on developing an equilibrium position controller for the EEM with the presence of the matched and unmatched uncertainties. The proposed controller is based on a backstepping scheme optimized using an adaptive sliding mode technique and an adaptive nonlinear PI structure. To estimate parameters of known functions in the system dynamics, the parametric learning laws are employed, while adaptive switching gain laws are used to adjust robust gains of discontinuous control terms. The robust switching gains increase or decrease as state control variables move away or close to the surfaces, respectively. Working together, these kinds of adaptation laws can effectively deal with the problem of matched and unmatched uncertainties. Next, the Lyapunov approach is used to prove the robustness and stability of the whole system. The proposed method is practically implemented and compared with other controllers to demonstrate the effectiveness of the proposed method with the variant stiffness and the uncertainties.

Security control for Markov jump system with adversarial attacks and unknown transition rates via adaptive sliding mode technique

This paper is concerned with the security control problem for a class of Markov jump systems subject to false data injection attack and incomplete transition rates. An on-line estimation strategy is provided for the time-variant and unknown cyber-attack modes. And then, an adaptive sliding mode controller is synthesized with different robust terms for different modes to guarantee the reachability of the specified sliding surface. Moreover, the sufficient conditions for the stability of the closed-loop systems are derived. Finally, it is shown from simulation results that the effect of both false data injection attack and incomplete TRs can be effectively attenuated by the present adaptive SMC method.