Adaptive Robust Neural-Network-Based Backstepping Control of Tethered Satellites With Additive Stochastic Noise

Vafamand, Navid

doi:10.1109/taes.2020.2985276

Cited by 24 publications

(7 citation statements)

References 31 publications

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“…To assure closed-loop stability, in this paper, a novel backstepping controller is proposed such that it does not require the timederivatives of loads. Moreover, to avoid the complex calculation of derivative terms and the need to know the dynamics of the loads, in this paper a command filter approach [34], [35], [38] is developed. By using the command filter in the design procedure, instead of computing their time derivatives, the virtual inputs are filtered by a first-order stable filter and its outputs will be used.…”

Section: A Command Filter Approachmentioning

confidence: 99%

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

Vafamand

Arefi

Anvari‐Moghaddam

2023

IEEE Systems Journal

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The stability of alternating current microgrids (AC MGs) is significantly affected by the procedure of collecting precise and sufficient information of the system and tightly controlling power inverters. Whereas using many sensors increases AC MG ripples and cost, integrating cost-effective and low number of sensors is preferred. Further, assuring the stability and tracking issue of AC MGs in different operating modes and in the presence of unknown time-varying loads is a hard task. Aiming at these issues, this paper proposes an improved augmented-Kalman filter to estimate the state vector and disturbance inputs and a nonlinear backstepping controller with a command filter to design the control law. Compared to the conventional Kalman filters, the developed approach is able to estimate the external disturbances, which improves the state estimation performance and provides extra information about the power system. The proposed command filter-based backstepping has the key feature of avoiding the calculation of time-derivatives of desired references of virtual inputs, which is a common drawback of conventional approaches. Whereas the dynamics of the disturbance time-varying load are not available, the command filter is utilized to avoid the time derivatives terms of the disturbance inputs. Simulation results illustrate the estimation performance of the augmented Kalman filter and the tracking performance of the command filter-based backstepping controller.

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Section: A Command Filter Approachmentioning

confidence: 99%

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

Vafamand

Arefi

Anvari‐Moghaddam

2023

IEEE Systems Journal

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“…The stabilization of the coordinate  is possible if the angular velocities take zero values, and the equality const 2 = u is ensured, where  (t) =  = const. We introduce restrictions on the moments and after substitution of expressions ( 23) into (20), (21), we obtain…”

Section: System Modelmentioning

confidence: 99%

“…However, the proposed computational scheme is time-consuming. Recent publications on the applications of the backstepping procedure for providing satellite navigation and control of the UAV network have been presented in papers [20]- [23], respectively. Therefore, the use of advanced control methods is in the interest of future use such as space and UAV network control.…”

Section: Introductionmentioning

confidence: 99%

Stabilizing the spatial position of a quadrotor by the backstepping procedure

Kucherov

Kozub²,

Sushchenko

et al. 2021

IJEECS

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<div>The paper considers the problem of synthesizing a control law that stabilizes the spatial position of an airborne object. The control object is a quadrotor with nonlinear dynamics. To solve the stabilization problem, a mathematical model of the quadrotor has been developed, taking into account its positionin the Cartesian and Euler coordinate systems. The new control law has been synthesized using the backstepping procedure. This control law is based on the Lyapunov-type stabilization criterion. New results analysis of the quadrotor dynamics, where has been showing the dependence of the control accuracy on the parameter of the stabilization criterion also presented. An algorithm for the directed search of the procedure parameter also has been proposed. It ensures the desired quality of the transient process. Simulation results confirming the results of the oretical research have been presented as well.</div>

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“…Some examples of noisy measurements are wave and wind profiles, and random variations of system parameters due to temperature changes. It is shown that, if the stochastic noises are not compensated, the performance may be worsened or closed‐loop stability may be destroyed 14,15 . On the other hand, by emerging the concept of stochastic system stability, the topic of stochastic nonlinear systems control has been at the center of attention 16–18 .…”

Section: Introductionmentioning

confidence: 99%

Robust neural network‐based backstepping landing control of quadrotor on moving platform with stochastic noise

Vafamand

Arefi

2021

Intl J Robust & Nonlinear

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This article introduces a novel nonlinear control approach for quadrotor landing on a moving ship. The dynamics of the relative position and attitude dynamics with uncertainties, unmodeled dynamics, external disturbances, and control input saturation is derived. Then, a novel robust adaptive constrained backstepping control law for the propeller and torques of the quadrotor is designed. To deal with uncertainties and un‐modeled dynamics, radial basis function is employed. The bounded‐in‐probability stability is used to alleviate the destructive influence of the stochastic Wiener process on the system positions and attitudes. Whereas the quadrotor is under‐actuated, a redundant control input technique, which affects the attitude commands, is presented. The actual control input saturation limits are turned into unknown saturation limits of the redundant control inputs. Also, since two phases for the landing problem are considered, a smooth switching mechanism between the control inputs is developed. Simulation results show the merits and applicability of the developed robust adaptive nonlinear controller.

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Adaptive Robust Neural-Network-Based Backstepping Control of Tethered Satellites With Additive Stochastic Noise

Cited by 24 publications

References 31 publications

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

Stabilizing the spatial position of a quadrotor by the backstepping procedure

Robust neural network‐based backstepping landing control of quadrotor on moving platform with stochastic noise

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