Adaptive Backstepping Sliding Mode Control Research Articles

Speed Control of Switched Reluctance Motor using Adaptive Fuzzy Backstepping Sliding Mode Control

Speed Control of Switched Reluctance Motor using Adaptive Fuzzy Backstepping Sliding Mode Control

Adaptive backstepping sliding mode subject-cooperative control for a pediatric lower-limb exoskeleton robot

The passive-assist rehabilitation mode with a fixed desired trajectory neglects the subject’s active involvement and degrades the therapeutic performance in case of partial muscle strength. Therefore, this study proposes a novel subject-cooperative control based on a variable admittance control scheme and a robust trajectory control scheme for a pediatric lower-limb exoskeleton robot. Initially, the system description and dynamic modeling are briefly explained. Thereafter, a neural-fuzzy–based variable admittance control ( nf VAC) is designed to incorporate a realistic subject-exoskeleton interaction and consider the subject’s active participation. Finally, a robust adaptive backstepping sliding mode control with rapid reaching law is used to handle parametric uncertainties and external disturbances. A stepwise selection of Lyapunov functions is utilized to address the stability of the trajectory control. The effectiveness of the proposed adaptive backstepping sliding mode–neural-fuzzy variable admittance control (ABSM- nf VAC) scheme is compared with two contrast control schemes, namely, adaptive backstepping-fixed admittance control (AB-FAC) and adaptive terminal sliding mode-fuzzy variable admittance control (ATSM- f VAC) for the active-assist mode with the effect of sudden reflex. Based on the numerical results, the suggested cooperative controller has demonstrated favorable tracking performance, compliant interaction, and safety aspects during gait training.

Adaptive backstepping sliding mode compensation control for electro‐hydraulic load simulator with backlash links

AbstractWhen a mechanical backlash between the loading piston rod and the steering gear piston rod connection of the electro‐hydraulic load simulator (EHLS), it will lead to poor loading accuracy. To solve this problem, an adaptive backstepping sliding mode controller based on the backlash feedforward compensation and state observer is proposed. First, the mechanism of surplus force generation in the EHLS is analyzed, and a mathematical model containing position disturbance and backlash nonlinearity is established based on the analysis results. Second, a state observer is designed to estimate the system state and the parameter adaptive law is designed to estimate the system parameters. Third, the adaptive backstepping method is combined with the non‐singular terminal sliding mode control (NTSMC) strategy to deal with the position disturbance and parameter uncertainty and to enhance the system's dynamic performance. Finally, a backlash feed‐forward compensator is engineered to restrain the detrimental effects caused by the backlash nonlinearity, and the simulation experimental results show that the designed new method can realize the precise loading of the EHLS under different working conditions, and the surplus force is suppressed better at the same time.

Enhancing pressure control of low-friction pneumatic actuator with eddy current damper via valve dead-zone compensation

This article addresses the high-performance pressure control of a pneumatic actuator that incorporates an air-bearing piston and an eddy current damper (ECD). After optimizing the pneumatic actuator, achieving precise pressure control relies on maintaining an accurate and stable airflow through the control valve. A terminal sliding mode adaptive control method (TSMAC) is proposed, proficiently integrating considerations for dead zone nonlinearities in the proportional valve and the effects of unmodeled disturbances in the pneumatic actuator. Using the opening area of the proportional valve as the input to the pneumatic system greatly simplifies the control process and reduces the workload required for valve parameter calibration. The Lyapunov-based stability analysis demonstrates that excellent asymptotic output tracking can be achieved with low steady-state error simply by knowing the boundaries of the valve opening area. The control effect of the proposed control strategy is compared with an adaptive backstepping sliding mode control method based on a linearly fitted proportional valve model on an established constant pressure control test bench. Experimental results under various loads and operating conditions illustrate the effectiveness of the proposed approach.

Adaptive fuzzy-neural network effectively disturbance compensate in sliding mode control for dual arm robot

In this study, an Adaptive Backstepping Sliding Mode Controller (ABSMC) is introduced based on the Radial Basis Function (RBF) neural network and a fuzzy logic modifier. The proposed method is used to control a Dual-Arm Robot (DAR) – a nonlinear structure with unstable parameters and external disturbances. The control aims to track the motion trajectory of both arms in the flat surface coordinate within a short time, maintaining stability, and ensuring that the tracking error converges in finite time, especially when influenced by unforeseen external disturbances. The nonlinear Backstepping Sliding Mode Control (BSMC) is effective in trajectory tracking control; however, undesired phenomena may occur if there are uncertain disturbances affecting the system or model parameters change. It is proposed to use a neural network to estimate a nonlinear function to handle unknown uncertainties of the system. The neural network parameters can be adaptively adjusted to optimal values through adaptation rules derived from Lyapunov's theorem. Additionally, fuzzy logic theory is also employed to adjust the controller parameters to accommodate changes or unexpected impacts. The performance of the Fuzzy Neural Network Backstepping Sliding Mode Control (FNN-BSMC) is evaluated through simulation results using Matlab/Simulink software. Two simulation cases are conducted: the first case assumes stable model parameters without uncertain disturbances affecting the joints, while the second case considers a model with changing parameters and disturbances. Simulation results demonstrate the effective adaptability of the proposed method when the system model is affected by various types of uncertainties from the environment

Adaptive sliding mode attitude control of quaternion model for aircraft based on neural network minimum parameter learning method

AbstractThis paper studied the back-stepping adaptive sliding mode control (SMC) attitude problem of quaternion aircraft model based on radial basis function (RBF) network approximation. Firstly, a sliding mode controller is designed based on the back-stepping method (BSM) for the nonlinear aircraft model. Secondly, a RBF network algorithm is designed to compensate for the unknown and uncertain parts of the aircraft system. RBF network has simple network structure and good generalisation ability, avoids lengthy and unnecessary calculations, realises adaptive approximation of unknown parts in the aircraft model, and through the adjustment of adaptive weights, the convergence and stability of the entire closed-loop system (CLS) are guaranteed. Finally, the anti-interference performance of the controller is verified by simulation of the actuator fault model. Our proposed method has all-right control performance indicated by the simulation results.

Adaptive backstepping fast terminal sliding mode control of dynamic positioning ships with uncertainty and unknown disturbances

Considering the complexity of the operating environment of marine ships, higher demands are placed on the positioning accuracy and positioning performance of Dynamic Positioning (DP) systems. This paper designs an Adaptive Backstepping Fast Terminal Sliding Mode Control (ABFTSMC) to solve the problems of low positioning accuracy, slow convergence, and poor anti-interference performance in ship positioning due to uncertainty of dynamic model parameters and unknown time-varying environmental disturbances. A Fast Terminal Sliding Mode Control (FTSMC) is combined with backstepping techniques to ensure the robustness of the system to uncertainties and disturbances. Meanwhile, an adaptive law is used to estimate the unknown uncertainty terms. Moreover, the Lyapunov stability criterion is used to prove the convergence and stability of the designed controller. Multiple simulation results show that ABFTSMC has better control performance compared with Adaptive Backstepping Control (ABC) and Adaptive Backstepping Sliding Mode Control (ABSMC). All the comparisons could fully verify the effectiveness and superiority of the proposed control method.

Robustness Study of a Modular Smart Transformer Based on a Combined Control Strategy under Disturbed Operating Conditions in the Smart Distribution Grid

With the large-scale integration of renewable energy sources (RES) and electric vehicles, the smart distribution grid (SDG) represents a promising alternative to power distribution systems. However, the conventional transformer (CT) is a passive device that cannot meet SDG requirements. In this context, the smart transformer (ST) based on modular architecture is considered an attractive alternative to CT since it provides multiple DC buses in medium voltage (MV) and low voltage (LV) grids. This article proposes a modular ST model including a cascaded H-bridge rectifier in the MV AC-DC stage, dual active bridge converters in the high-frequency DC-DC stage, and a four-leg inverter in the LV DC-AC stage for SDG applications. To improve its dynamic performance, an adaptive backstepping-sliding mode control is introduced. The proposed controller enables the automatic estimation of unknown parameters, especially in the presence of intermittent RESs, by the adaptive laws of the adaptive backstepping controller (ABC) and the improvement of the ST robustness under grid disturbances by introducing the discontinuous control of the sliding mode controller (SMC). The obtained simulation results prove the effectiveness of the selected ST model and the higher robustness of the proposed controller against grid disturbances, compared to the ABC and SMC.

Observer-Based Adaptive Backstepping Sliding-Mode Control of the Satellite Attitude with a Partially Filled Spherical Fuel Tank

Observer-Based Adaptive Backstepping Sliding-Mode Control of the Satellite Attitude with a Partially Filled Spherical Fuel Tank

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

To provide reliable position control for a permanent-magnet synchronous motor (PMSM) under conditions of lumped disturbances such as external load torque fluctuation and system parameter variation, an adaptive backstepping sliding-mode control (ABSMC) with a nonlinear disturbance observer (NDO) is proposed. An ABSMC is a non-cascade technique that employs a position-current single-loop control structure rather than a conventional cascade control structure for vector control of the PMSM. This method uses Lyapunov theory to design a control law to ensure the motor position reaches a desired value in a finite period of time and consequently achieves a rapid transient response. The proposed ABSMC incorporates an adaptive convergence gain to avoid a large overshoot under point-to-point position command. The NDO with a nonlinear observer gain is proposed to estimate unknown disturbances and provide feed-forward compensation for the ABSMC, improving robustness and reducing steady-state position error. The proposed methods are applied to an industrial motor drive to confirm their validity in real-world operating environments.

Trajectory tracking control of remotely operated vehicle based on thruster dynamics

Abstract In order to reduce the impact of thruster dead zone on remotely operated vehicle (ROV) motion performance and ensure that it can complete trajectory tracking control under external interference. In this paper, the adaptive backstepping sliding mode control(ABSMC) method based on improved rapid power-to-power approximation law is proposed. Under the influence of external interference; ABSMC can quickly reduce the position error of the system, namely, shorten the approaching time. When the position error is small, the system can smoothly enter the sliding surface to eliminate chattering. A new thrust distribution method based on the pseudo-inverse method is proposed for the dead zone of a thruster. This method uses the pseudo-inverse method when the thrust is saturated. When all thruster thrusts are unsaturated, the thrust will remain outside the dead zone for a long time. Combined with the ABSMC method, the thrust output of the thruster is more smooth and more stable with small position errors. Finally, the effectiveness of the ABSMC method and the superiority of the new thrust distribution method is verified by simulation experiments.

Adaptive Finite-Time Backstepping Sliding Mode Control for PMSM System With Backlash

The rapid tracking stabilization problem of the servo system with gear backlash and unmatched unknown disturbance is investigated. In this article, a novel finite-time sliding mode surface with a faster convergence rate is proposed to improve the anti-interference of the gear transmission servo system. This surface not only can adaptively and dynamically regulate the integral capability together with disturbances and tracking error variations, but also does not create singularity issues. An adaptive fixed-time reaching law (AFTRL) is proposed, which performs a faster convergence rate and chattering-free performances. The adaptive mechanism ensures the continuous property of the control output and dynamically regulates the fixed-time convergence rate regardless of initial states. The dSPACE platform is employed to validate the excellent tracking performance of the gear transmission servo system.

Adaptive chaos synchronization of an attitude control of satellite: A backstepping based sliding mode approach

This paper uses adaptive backstepping sliding mode control to synchronize two satellite attitude dynamics with perturbing torques. The external perturbing torques induce chaotic motion with no control inputs. The proposed control system uses Lyapunov theory and Barbalat's Lemma to guarantee the asymptotic stability of the controlled system. Simulation results confirm the effectiveness of the proposed design.

Adaptive coupled attitude-servo control for moving mass flight vehicles with high-mass-ratio

Moving mass flight vehicles (MMFVs) with high-mass-ratio suffer from a more severe nonlinear attitude-servo coupling than the traditional configurations that are under particle moving mass hypothesis. Therefore, the coupled attitude-servo control problem is investigated in this paper, and an adaptive backstepping sliding mode controller with extended state observers and neural-networks (ABSMC-ENN) is proposed. Based on the formulated control model with strict-feedback form, a sliding mode control law (SMC) with exponential reaching rate and a nonsingular terminal sliding mode control law (NTSMC) are combined to perform the fast and robust tracking of the command angle-of-attack. Considering the disturbances and uncertainties existing in the coupled dynamics, two nonlinear extended state observers (ESOs) are utilized to estimate the total disturbances online for compensation. To further enhance the adaptiveness and dynamic response performances of the controller in various flight conditions, two radial basis function neural networks (RBFNNs) are exploited to optimize the switching gains of the controller in real-time with performance indexes being the functions of tracking errors. Closed-loop stability of the whole system is proved via Lyapunov methodology. Comparison simulation studies considering multiple disturbances, various flight conditions, and different controllers successfully demonstrate the superiority of the ABSMC-ENN in robustness and adaptiveness.

A novel adaptive backstepping sliding mode control for a lightweight autonomous underwater vehicle with input saturation

Accurate depth and heading control play an essential role for autonomous underwater vehicles (AUVs) in near-seabed exploration and ocean surveys. This paper proposed a novel adaptive backstepping sliding mode control (ABSMC) algorithm for a lightweight autonomous underwater helicopter (AUH) subject to highly coupled nonlinearities, unknown system parameters, disturbances uncertainties, and input saturation. This algorithm adopted a conditional adaptation algorithm to govern adaptation so that gains only adapt when necessary to improve stability. Different reaching laws were selected for heading and depth control to reduce system chattering. For thruster saturation, we proposed an anti-windup compensator for auxiliary dynamic compensation based on system states; it can make the controller output change smoothly in the event of input saturation to better meet the response characteristics of the actual physical actuator. The mathematical proofs of the proposed algorithms are presented. Simulation results are presented to illustrate the effectiveness of the proposed control method. Moreover, extensive experimental results show that the proposed algorithm has better control performance than PID and sliding mode controllers and demonstrate its adaptive capability to system state changes.

Research on Position Control of an Electro–Hydraulic Servo Closed Pump Control System

A control strategy combining adaptive backstep sliding mode control and dead-zone inverse compensation control in a series was proposed to solve the problem of system parameter uncertainty and system dead-zone in the process of position control in an electro–hydraulic servo closed pump control system. Firstly, an adaptive backstepping sliding mode controller was designed by introducing the sliding mode control principle. Secondly, the smooth dead-zone inverse function was constructed by using the smooth continuous index function to design the dead-zone inverse compensation controller, which is combined with the adaptive sliding mode controller to form a series controller. Finally, the feasibility of the controller was verified by using the pump control servo system of a lithium battery pole strip mill. The experimental results show that, compared with traditional PID control, the control strategy displayed no excessive overshoot before the steady state, the steady-state control accuracy could reach ±0.002 mm, and the time required to reach the steady state was 1 s to 2 s shorter, which shows this method’s ability to effectively improve the position control accuracy of the pump control system, as well as its dynamic response performance.

Adaptive Backstepping Sliding Mode Control of Vehicle-Mounted Parallel Stabilized Platform

This paper researches an accurate and cooperative stability control method for the vehicle-mounted parallel stabilized platform to isolate the external random interference caused by rugged terrains. An adaptive backstepping sliding mode controller is designed by combining the adaptive method and backstepping design method. The position and pose of the platform are calculated in real time as feedback quantity and a closed-loop controller overall pose is designed. Simulation and experimental results show that the vehicle-mounted parallel stabilized platform can quickly and accurately adjust the pose of the upper platform to keep horizontal when the vehicle runs on rugged terrains.

Adaptive backstepping sliding mode control of permanent magnet spherical motor based on disturbance observer.

This paper proposes an adaptive backstepping sliding mode control method based on a nonlinear disturbance observer (NDO) to solve the problem that the tracking performance of the motion system of a permanent magnet spherical motor (PMSpM) is degraded due to the influence of external nonlinear disturbance. First, the dynamic model of the PMSpM under the compound interference is established. Second, an NDO and an adaptive backstepping sliding mode controller are designed to compensate for the external disturbances and modeling uncertainties, and the stability of the closed-loop system using the proposed method is confirmed through the Lyapunov theorem. Then, compared with the results of proportion differentiation control and conventional sliding mode control, the simulation results show that the proposed method can significantly reduce input signal chattering and improve the trajectory tracking performance of the PMSpM. Finally, experimental results are provided to validate the effectiveness of the proposed method.

Backstepping sliding-mode techniques in current control of polymer electrolyte membrane fuel cell

The polymer electrolyte membrane fuel cell (PEMFC) power conditioning is particularly crucial for a fuel cell vehicle to meet various load demands effectively. This paper focuses on the PEMFC current control addressing varied tracking references or disturbance injections. With control-oriented models of the PEMFC-fed DC–DC systems, two control methods integrated with sliding-mode control (SMC) are proposed to regulate the fuel cell current: a backstepping method dealing with high nonlinearity and coupled characteristics of the PEMFC power supply, and an adaptive approach counteracting parametric uncertainties or load disturbances. Simulations and experiments indicate that the proposed backstepping SMC could alleviate chattering of the conventional SMC effectively and maintain good robustness; in addition, the adaptive backstepping SMC could further reduce the fuel cells ′ settling time by 25 % during transient response experiment with the boost converter and make system parameters vary more smoothly with the buck converter.

Constrained Adaptive Backstepping Sliding Mode Control for Inertial Stable Platform

Constrained Adaptive Backstepping Sliding Mode Control for Inertial Stable Platform