Guaranteed Tracking Controller for Wheeled Mobile Robot Based on Flatness and Interval Observer

This paper proposes a guaranteed tracking controller for a Wheeled Mobile Robot (WMR) based on the differential flatness theory and the interval observer. Using the flatness property, it is possible to transform the non linear WMR model into a canonical Brunovsky form, for which it is easier to create a state feedback controller. Since, in most real applications, the WMR is subjected to uncertainties such as slip, disturbance and noise, control algorithms must be modified to take into account those uncertainties. Therefore, based on the information of the upper and lower limits of the initial condition and all the uncertainties, an interval observer that generates an envelope enclosing every feasible state trajectory is developed. After that, based on the center of the obtained interval observer, a new control law is proposed to guarantee the tracking performance of the WMR despite the existence of un-measurable states and bounded uncertainties. The closed-loop stability of the system is proven analytically using the Lyapunov theorem. A lot of numerical simulation is realized in order to demonstrate the efficiency of the suggested guaranteed tracking control scheme.

[1]  Yan Wang,et al.  Interval observer design for LPV systems with parametric uncertainty , 2015, Autom..

[2]  Masayoshi Tomizuka,et al.  Flatness-Based Nonlinear Control for Position Tracking of Electrohydraulic Systems , 2015, IEEE/ASME Transactions on Mechatronics.

[3]  Hashem Ashrafiuon,et al.  Robust Tracking Control of Quadrotors Based on Differential Flatness: Simulations and Experiments , 2018, IEEE/ASME Transactions on Mechatronics.

[4]  Alain Rapaport,et al.  Parallelotopic and practical observers for non-linear uncertain systems , 2003 .

[5]  Denis V. Efimov,et al.  Design of interval observers for uncertain dynamical systems , 2016, Automation and Remote Control.

[6]  Philippe Martin,et al.  A Lie-Backlund approach to equivalence and flatness of nonlinear systems , 1999, IEEE Trans. Autom. Control..

[7]  J. Gouzé,et al.  Interval observers for uncertain biological systems , 2000 .

[8]  Amine Abadi,et al.  Optimal trajectory generation and flatness tracking control for a mobile robot , 2017, 2017 18th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).

[9]  Sunil K. Agrawal,et al.  Effects of Viscous Damping on Differential Flatness-Based Control for a Class of Under-Actuated Planar Manipulators , 2018, IEEE Control Systems Letters.

[10]  Denis V. Efimov,et al.  Interval observer for a class of uncertain nonlinear singular systems , 2016, Autom..

[11]  John Cortés-Romero,et al.  Trajectory Tracking Control of a Mobile Robot Through a Flatness-Based Exact Feedforward Linearization Scheme , 2015 .

[12]  Sara Ifqir,et al.  Interval observer for LPV systems: Application to vehicle lateral dynamics , 2017 .

[13]  Denis Efimov,et al.  Interval Observers for Secure Estimation in Cyber-Physical Systems , 2018, 2018 IEEE Conference on Decision and Control (CDC).

[14]  Tarek Raïssi,et al.  Interval observer framework for fault-tolerant control of linear parameter-varying systems , 2018, Int. J. Control.

[15]  Salah Nasr,et al.  A multi-scroll chaotic system for a higher coverage path planning of a mobile robot using flatness controller , 2019, Chaos, Solitons & Fractals.

[16]  Mario Ramirez-Neria,et al.  Trajectory Tracking for an Inverted Pendulum on a Cart: An Active Disturbance Rejection Control Approach , 2018, 2018 Annual American Control Conference (ACC).

[17]  Sunil Kumar Agrawal,et al.  Differential flatness-based robust control of mobile robots in the presence of slip , 2011, Int. J. Robotics Res..

[18]  Denis V. Efimov,et al.  Application of interval observers to estimation and control of air-fuel ratio in a direct injection engine , 2015, 2015 American Control Conference (ACC).

[19]  Denis V. Efimov,et al.  Interval State Estimation for a Class of Nonlinear Systems , 2012, IEEE Transactions on Automatic Control.

[20]  Jean-Luc Gouzé,et al.  Closed loop observers bundle for uncertain biotechnological models , 2004 .