Design and experimental validation of UDE based controller--observer structure for robust input--output linearisation

Abstract

In this work, uncertainty and disturbance estimation (UDE) technique is employed to robustify an input-output linearisation (IOL) controller. An IOL controller designed for a nominal system is augmented by the UDE estimated uncertainties to achieve robustness. In doing so, state dependent nonlinearities of the system are treated as a part of the uncertainties and thus, the controller does not require system states for its implementation. The resulting controller, however, needs derivatives of the output. To address the issue, a design of an observer that employs the UDE estimated uncertainties for robustness is proposed giving rise to the UDE based controller-observer structure. Closed loop stability of the overall system is established. The notable feature of the proposed design is that it neither requires accurate plant model nor system states or derivatives of output. Also the approach does not need any information about the uncertainty. To demonstrate the effectiveness, numerical simulation results of the proposed approach as applied to the wing-rock motion control problem are presented. Lastly, hardware implementation of the UDE based controller-observer structure for motion control of Quanser's DC servo motion control platform is carried out and it is shown that the proposed strategy offers a viable approach for designing implementable robust IOL controllers.

Robust Attitude Tracking Control for a Quadrotor Based on the Uncertainty and Disturbance Estimator

“…Furthermore, it can be concluded from (17), (18) that the tracking error e i (t) also exponentially converges to zero when t tends to infinity. However, u di (t) in (19) is unknown due to uncertainties and disturbances, so the uncertainties compensation control part v di (t) in (21) should be redesigned. Substituting (20), (22) into (19) leads toė…”

“…In this paper, in order to achieve the attitude control of the quadrotor in the presence of internal uncertainties and external disturbances, a control method based on the uncertainty and disturbance estimator (UDE) is adopted. The UDE method, which was proposed in [14], has many advantages in both design and implementation respects and its excellent performance in handling the uncertainty and disturbance yet with very easy tuning and implementation has been demonstrated in recent years through both theories (including extensions to both linear [14,15] and nonlinear systems [16][17][18][19][20], systems with delays [15,17] etc.) and wide applications (covering mechatronics and robotics [21], electrical machines and drives [14,20], renewable energy [22], aerospace and automotive systems [23,24] etc).…”

Design of $$\varvec{\upalpha }$$ α -filter-based UDE controllers considering finite control bandwidth

“…The UDE-based control strategy has been further elaborated A. Kuperman (B) Hybrid Energy Sources Laboratory, Department of Electrical Engineering and Electronics, Ariel University, POB 3, 40700 Ariel, Israel e-mail: alonku@ariel.ac.il in [2,3] and successfully applied to several different control problems [4][5][6][7][8][9][10]. The two-degree-of-freedom nature of UDE controllers has been revealed in [11], greatly simplifying underlying principle and facilitating controller design [12].…”

Robust Control for a Class of Nonaffine Nonlinear Systems Based on the Uncertainty and Disturbance Estimator

“…The UDEbased control does not require a completely-known system model or a disturbance model and is robust against structured/unstructured uncertainties (e.g., modeling error, parameter variation) and external disturbances. The UDE-based robust control has demonstrated its excellent performance in handling uncertainties and disturbances yet a simple control scheme, and has been successfully applied to robust inputoutput linearization [29], [30] and combined with sliding-mode control [31], [32], and further extended to uncertain systems with state delays, for both linear systems [33] and nonlinear systems [34], recently in variable-speed wind turbines [35].…”