Adaptive Neural Network-Based Backstepping Sliding Mode Control Approach for Dual-Arm Robots

Nguyen, Thai Van; Thai, Nguyen Huu; Pham, Hai Tuan; Phan, Tuan Anh; Nguyen, Linh; Le, Hai Xuan; Nguyen, Hiep Dinh

doi:10.1007/s40313-019-00472-z

Cited by 27 publications

(15 citation statements)

References 30 publications

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“…Due to its fundamentality, researchers, engineers and practitioners who design a control law for a underactuated crane system always concern about robustness in the system response due to its parameter uncertainties and actuator nonlinearities. To address the concern, sliding mode control (SMC) method has then been favoured for those systems [8][9][10][11][12][13][14][15][16]. For instance, the authors in [17][18][19] proposed the robust SMC controllers for a gantry crane, which allow the system with uncertain parameters and nonlinear actuators to robustly work under external disturbances in a working environment.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane

Nguyen¹

2022

Preprint

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<pre>The paper proposes a new approach to efficiently control a three-dimensional overhead crane with six degrees of freedom (DoF). In addition to five usual output variables including three positions of the trolley, bridge and pulley and two swing angles of the hoisting cable, it is proposed to consider elasticity of the hoisting cable, which causes oscillation in the cable direction. That is, there exists $6^{th}$ under-actuated output in the crane system. To design an efficient controller for the six-DoF crane, it first employs the hierarchical sliding mode control approach, which not only guarantees stability but also minimizes sway and oscillation of the overhead crane when it transports a payload to desired location. Moreover, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by utilizing the fuzzy inference rule mechanism, which results in efficient operations of the crane in real time. More importantly, stabilization of the crane controlled by the proposed algorithm is theoretically proved by the use of the Lyapunov function. The proposed control approach was implemented in the synthetic environment for the extensive evaluation, where the obtained results demonstrate its effectiveness.</pre>

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Section: Introductionmentioning

confidence: 99%

An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane

Nguyen¹

2022

Preprint

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“…In the control theory, sliding model control is widely used in systems highly requiring robustness [2], [3]. Nevertheless, the sliding model control assumes that a dynamic model of a system is deterministic and known, which is impractical [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

Nguyen¹

2021

Preprint

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<div>The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown</div><div>and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic</div><div>two-wheel robot where the obtained results demonstrate its</div><div>effectiveness.</div>

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“…The basic idea of SMC is to force the system state trajectories (by applying a designed control law to the system) to slide onto the sliding surface (specific switching manifold) and to define a sliding surface such that tracking errors reach zero along with the sliding surface. SMC scheme has also been employed for different applications to ensure the robustness feature of the controllers (Tchinda et al 2019;Taheri et al 2019;Van Nguyen et al 2019;Zaihidee et al 2019;Eaton et al 2009;Shafiei and Binazadeh 2013;Yousefi and Binazadeh 2018;Elsayed et al 2015). On the other hand, SMC individually merely guarantees asymptotic stability of the system to which it is applied.…”

Section: Introductionmentioning

confidence: 99%

Chattering-Free Trajectory Tracking Robust Predefined-Time Sliding Mode Control for a Remotely Operated Vehicle

Hosseinabadi

Abadi

Mekhilef

et al. 2020

J Control Autom Electr Syst

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This study investigates a new chattering-free robust predefined-time sliding mode control (CFRPSMC) scheme for the trajectory tracking control problem of a three-degree-of-freedom (3-DOF) remotely operated vehicle (ROV) in the presence of matched uncertainties. The advanced notion of predefined-time stability is used to provide a maximum convergence time as desired that can be set during the control design and independently of the initial conditions. Based on defining a new form of sliding surfaces, a new control law is designed to ease the undesirable chattering phenomenon without damaging the robustness properties and tracking precision. The proposed control scheme can not only solve the predefined-time tracking controller design problem, but also provide the robustness to various uncertainties. The Lyapunov stability theory is used to establish the stability analysis of the closed-loop system in both the reaching phase and the sliding phase. The performance of the proposed CFRPSMC scheme is evaluated for the 3-DOF ROV through two comparative simulation cases using Simulink/MATLAB. The comparative simulation results and analytical comparisons demonstrate the efficacy and superiority of the proposed method compared with other relevant conventional methods.

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Adaptive Neural Network-Based Backstepping Sliding Mode Control Approach for Dual-Arm Robots

Cited by 27 publications

References 30 publications

An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane

An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane

Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

Chattering-Free Trajectory Tracking Robust Predefined-Time Sliding Mode Control for a Remotely Operated Vehicle

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