Adaptive Integral Sliding Mode Control Using Fully Connected Recurrent Neural Network for Position and Attitude Control of Quadrotor

Yogi, Subhash Chand; Tripathi, Vibhu Kumar; Behera, Laxmidhar

doi:10.1109/tnnls.2021.3071020

Cited by 72 publications

(30 citation statements)

References 41 publications

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“…Model-free PID control strategies is utilized by early researchers, but their control parameters count mainly on empirical methods of trial and error, leading to poor system anti-disturbance capability [12]. With the continuous advancement of control theory, methods such as ILC, SMC, adaptive control and impedance control have attracted great attention [13][14][15][16]. In [17], an iterative learning algorithm is applied to dynamically estimate the non-modeled parameters and time-varying disturbances in the dynamic model, on the basis of which a back-stepping controller is designed to achieve impedance control of the elbow joint in the upper limb.…”

Section: Introductionmentioning

confidence: 99%

Impedance Iterative Learning Sliding Mode Control for Robot-Assisted Bathing with Non-repetitive Trajectory

Guo

zhang

et al. 2022

Preprint

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In this paper, an impedance iterative learning sliding mode control (IILSMC) scheme for robot-assisted bathing with unknown model parameters is investigated. Firstly, impedance control is not only applied to adjust the desired trajectory, but also implemented to ensure the active compliance control of the robot-assisted bathing. Furthermore, iterative learning control is designed to dynamically estimate the unknown model parameters. To release the identical initial condition of iterative learning control (ILC), the trajectory reconstruction method is proposed, such that the convergence of tracking errors can be guaranteed with random initial status. Moreover, adaptive sliding mode control (SMC) is proposed where non-parametric, external disturbances and the human-machine interaction (HMI) torque generated during the bathing process is suppressed by adaptive method. Based on the composite energy function (CEF) method, the convergence of the double closed-loop system in the time domain and iterative domain is proved. Finally, through co-simulation of MATLAB/Simulink and ADAMS, the effectiveness and superiority of the control strategy proposed in this paper is jointly verified.

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Section: Introductionmentioning

confidence: 99%

Impedance Iterative Learning Sliding Mode Control for Robot-Assisted Bathing with Non-repetitive Trajectory

Guo

zhang

et al. 2022

Preprint

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“…With the requirement of strong disturbance rejection as well as precise control performance, some attempts have been made by adding feedforward compensation based on the controller. To guarantee the improvement of feedforward perfor-mance, the disturbance observer and corresponding theory have been investigated for quadrotors in traditional techniques, such as sliding mode observers (SMO) [6][7][8][9], function approximators by neural networks (NN) [10][11][12][13], fuzzy logistic system (FLS) [14,15], and extended state observers (ESO) [16,17]. In [8], a first-order SMO equipped with high gain observer is designed to estimate unknown disturbance.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], a robust and adaptive controller-based NN is conducted for quadrotor by introducing the generalized regression neural network. To realize the finite-time convergence, an adaptive integral sliding mode control is proposed with a novel fully connected recurrent neural networks with finite time learning process in [13]. In [14], an adaptive backstepping control is proposed with the command filtering technique for quadrotor trajectory tracking, where FLS is employed to estimate the uncertainty dynamics in the quadrotor model.…”

Section: Introductionmentioning

confidence: 99%

“…(i) Unlike the above stating SMO-based controller [6][7][8][9] and controller with function approximators [10][11][12][13][14][15], where chattering and heavy computational burden with adjusting parameters always arise, we adopt the unknown system dynamic estimator (USDE) with an invariant manifold for quadrotor attitude regulation to confirm the uncertainty in quadrotor model. In comparison with the ESObased controller [16,17], due to state in quadrotor calculated with simple filter, a perspicuous framework consisting of USDE with low computation is conducted (ii) A novel USDE-based funnel control is proposed for quadrotor attitude regulation to enable preassigned convergence with existence of estimation error.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Nonlinear Quadrotor Attitude Regulation with Disturbances and Preassigned Convergences

Gao

Zhen

Zhang

et al. 2022

International Journal of Aerospace Engineering

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This article develops a novel unknown system dynamic estimator-based funnel control scheme for nonlinear quadrotor attitude regulation with preassigned convergence subject to parametric uncertainties and external perturbations. An invariant manifold equipped with first-order filtering is established. To online identify the lump disturbances, an unknown system dynamic estimator is employed with a simple formula, which need a lower computation burden. Based on aforementioned estimator, a novel funnel control via utilizing funnel variable is investigated, where an exponentially decaying funnel function is preset with a prior preassigned convergence for regulation angle error. The angle tracking errors are proved to be ultimately uniformly bounded, and angle regulation error can evolve within the preset funnel boundary. Simulation results demonstrate the effectiveness of the developed control scheme.

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“…In contrast to the conventional controllers [23,24], where the error decaying process of the quadrotors is governed by some unknown terms and only ultimately uniformly bounded (UUB) results are delivered, here, by predefining the funnel bound-based funnel variables, an FC was constructed to govern the transient and steady-state profiles as a priority, such that the overshoot, convergence time and steady-state errors could be regulated within the appropriate range. Significant efforts were devoted to entire system stability and error convergence analysis, which is more challenging than the existing FC-based controllers without considering uncertainties and USDErelated outcomes with no performance constraints.…”

mentioning

confidence: 99%

Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

Zhen

Zhang

2022

Electronics

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In the article, an unknown system dynamics estimator-based anti-disturbance attitude funnel control technique is considered for quadrotors to ensure tracking performance when experiencing parametric uncertainties and external perturbations. To reinforce the anti-disturbance ability, an unknown system dynamics estimator was established by constructing the filtering operation-based invariant manifold, resulting in a more concise design framework, lower computational consumption and an asymptotic error convergence. Additionally, a funnel control policy was employed to regulate angle-tracking errors within a minor overshoot, a faster convergence time and a lower steady-state error by devising the funnel variables, where an exponential decaying function was used to construct the funnel boundary. The great improvements beyond the available quadrotor control policies are related to satisfied disturbance mitigation and performance guarantees as a priority despite uncertainties. The error arguments comprising of angle and angular rate for quadrotors were ultimately uniformly bounded and the angles controlling the deviations were restricted to the funnel boundary. Finally, the simulations and experiments verified the superiority of the proposed control technique in terms of reduced control actions and higher precision, as well as shorter settling time.

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Adaptive Integral Sliding Mode Control Using Fully Connected Recurrent Neural Network for Position and Attitude Control of Quadrotor

Cited by 72 publications

References 41 publications

Impedance Iterative Learning Sliding Mode Control for Robot-Assisted Bathing with Non-repetitive Trajectory

Impedance Iterative Learning Sliding Mode Control for Robot-Assisted Bathing with Non-repetitive Trajectory

A Novel Nonlinear Quadrotor Attitude Regulation with Disturbances and Preassigned Convergences

Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

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