Journal Article10.3390/machines11090889
Multivariable Linear Position Control Based on Active Disturbance Rejection for Two Linear Slides Coupled to a Mass
Fabio Abel Gómez Becerra,Jonathan Villanueva Tavira,Héctor Miguel Buenabad Arias,A. Blanco Ortega,Estela Sarmiento Bustos,Manuela Calixto Rodríguez,Jorge Salvador Valdez Martinez +6 more
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TL;DR: Multivariable linear position control based on active disturbance rejection for two linear slides coupled to a mass achieves synchronization between the two actuators by estimating and rejecting disturbances.
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Abstract: Active Disturbance Rejection Control (ADRC) is a promising approach that has emerged to deal with uncertainties, which has received many practical applications in motion controls. This paper presents a multivariable controller for active disturbance rejection (ADR) based on an extended state linear observer for tracking the linear position trajectory of a mass moved by two linear slides, each one driven by a DC motor. The linear extended state observer is used to estimate the endogenous and exogenous disturbances of the system, which are assumed to be unknown, but bounded. Therefore, the feedback system prevents each actuator from operating at different forward speeds, and thus a synchronization between the two actuators is achieved by moving the common mass smoothly. The simulation and the experimental results show the effectiveness and robustness of the controller proposal when moving the mass with both actuators.
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Citations
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References
•Book
Differentially Flat Systems
Hebertt Sira-Ramírez,Sunil K. Agrawal +1 more
- 26 May 2004
TL;DR: This chapter discusses linear time-Invariant SISO Systems, MIMO Systems, and Flatness and Optimal Trajectories.
917
On the Control of the Permanent Magnet Synchronous Motor: An Active Disturbance Rejection Control Approach
Hebertt Sira-Ramírez,Jesus Linares-Flores,Carlos Garcia-Rodriguez,Marco Antonio Contreras-Ordaz +3 more
TL;DR: The proposed high-gain GPI observer-based ADR controller is justified in terms of a singular perturbation approach and verified by means of realistic computer simulations, using the MATLAB/SIMULINK-PSIM package.
335
Active Disturbance Rejection Control for a Flywheel Energy Storage System
TL;DR: This paper presents the application of the Active Disturbance Rejection Control Technique (ADRCT) to improve the performance of a Flywheel Energy Storage System (FESS) and shows that the new controller is more robust and more adaptive.
205
A Practical Multivariable Control Approach Based on Inverted Decoupling and Decentralized Active Disturbance Rejection Control
TL;DR: In this article, the authors developed a practical multivariable control method, consisting of inverted decoupling and decentralized active disturbance rejection controller (ADRC), achieving strong robustness with negligible computation and simple forms of the decoupler and controller.
109
From flatness, GPI observers, GPI control and flat filters to observer-based ADRC
TL;DR: The route taken by the author, and his research group, to bring differential flatness to the realm of active disturbance rejection control (ADRC) is established, including the establishing of an equivalence of observer based ADRC with FF’s.
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