Modeling and Robust Low Level Control of an Omnidirectional Mobile Robot

This paper presents the modeling and robust low-level control design of a redundant mobile robot with four omnidirectional wheels, the iSense Robotic (iSRob) platform, that was designed to test safe control algorithms. iSRob is a multivariable nonlinear system subject to parameter uncertainties mainly due to friction forces. A multilinear model is proposed to approximate the behavior of the system, and the parameters of these models are estimated from closed-loop experimental data applying Gauss–Newton techniques. A robust control technique, quantitative feedback theory (QFT), is applied to design a proportional–integral (PI) controller for robust low-level control of the iSRob system, being this the main contribution of the paper. The designed controller is implemented, tested, and compared with a gain-scheduling PI-controller based on pole assignment. The experimental results show that robust stability and control effort margins against system uncertainties are satisfied and demonstrate better performance than the other controllers used for comparison.

[1]  Paolo Gallina,et al.  Dynamic model with slip for wheeled omnidirectional robots , 2002, IEEE Trans. Robotics Autom..

[2]  Bin Yao,et al.  A Two-Loop Performance-Oriented Tip-Tracking Control of a Linear-Motor-Driven Flexible Beam System With Experiments , 2013, IEEE Transactions on Industrial Electronics.

[3]  M. S. Fadali,et al.  Adaptive position and trajectory control of autonomous mobile robot systems with random friction , 2010 .

[4]  Erhan Ilhan Konukseven,et al.  Improving the trajectory tracking performance of autonomous orchard vehicles using wheel slip compensation , 2016 .

[5]  Makoto Iwasaki,et al.  Observer of Nonlinear Friction Dynamics for Motion Control , 2015, IEEE Transactions on Industrial Electronics.

[6]  I. Horowitz Synthesis of feedback systems , 1963 .

[7]  N. Sepehri,et al.  Designing robust force control of hydraulic actuators despite system and environmental uncertainties , 2001 .

[8]  Kiattisin Kanjanawaniskul,et al.  Motion Control of a Wheeled Mobile Robot Using Model Predictive Control: A Survey , 2017 .

[9]  Mauro Birattari,et al.  Data-driven techniques for direct adaptive control: the lazy and the fuzzy approaches , 2002, Fuzzy Sets Syst..

[10]  Filipe Marques,et al.  A survey and comparison of several friction force models for dynamic analysis of multibody mechanical systems , 2016 .

[11]  Montserrat Gil-Martínez,et al.  Simultaneous meeting of robust control specifications in QFT , 2003 .

[12]  J. Quevedo,et al.  Low level control of an omnidirectional mobile robot , 2015, 2015 23rd Mediterranean Conference on Control and Automation (MED).

[13]  Guilin Yang,et al.  Decoupled Powered Caster Wheel for omnidirectional mobile platforms , 2014, 2014 9th IEEE Conference on Industrial Electronics and Applications.

[14]  A.P. Moreira,et al.  Practical Approach of Modeling and Parameters Estimation for Omnidirectional Mobile Robots , 2009, IEEE/ASME Transactions on Mechatronics.

[15]  Jan Swevers,et al.  Friction Compensation of an $XY$ Feed Table Using Friction-Model-Based Feedforward and an Inverse-Model-Based Disturbance Observer , 2009, IEEE Transactions on Industrial Electronics.

[16]  M. Indri,et al.  Friction Compensation in Robotics: an Overview , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[17]  Timothy W. McLain,et al.  Experimental validation of an autonomous control system on a mobile robot platform , 2007 .

[18]  Carlos Canudas de Wit,et al.  A survey of models, analysis tools and compensation methods for the control of machines with friction , 1994, Autom..

[19]  Ashitava Ghosal,et al.  Modeling of slip for wheeled mobile robots , 1995, IEEE Trans. Robotics Autom..

[20]  Ioan Doroftei,et al.  Omnidirectional Mobile Robot - Design and Implementation , 2007 .

[21]  J. M. Díaz,et al.  Interactive computer-aided control design using quantitative feedback theory: the problem of vertical movement stabilization on a high-speed ferry , 2005 .

[22]  Jouni Mattila,et al.  Time optimal path following with bounded velocities and accelerations for mobile robots with independently steerable wheels , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[23]  Yu Tian,et al.  Control of a Mobile Robot Subject to Wheel Slip , 2014, J. Intell. Robotic Syst..

[24]  Maani Ghaffari Jadidi,et al.  Trajectory planning optimization with dynamic modeling of four wheeled omni-directional mobile robots , 2009, 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA).

[25]  Gianluca Palli,et al.  Friction compensation techniques for tendon-driven robotic hands , 2014 .

[26]  Shugen Ma,et al.  Dynamic modeling and analysis of an omnidirectional mobile robot , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[27]  Brian Armstrong,et al.  New results in NPID control: Tracking, integral control, friction compensation and experimental results , 2001, IEEE Trans. Control. Syst. Technol..

[28]  Damiano Rotondo,et al.  Model Reference Switching Quasi-LPV Control of a Four Wheeled Omnidirectional Robot , 2014 .

[29]  Carlos E. T. Dorea,et al.  Design and Implementation of Model-Predictive Control With Friction Compensation on an Omnidirectional Mobile Robot , 2014, IEEE/ASME Transactions on Mechatronics.

[30]  Steven J. Rasmussen,et al.  Quantitative feedback theory: fundamentals and applications: C. H. Houpis and S. J. Rasmussen; Marcel Dekker, New York, 1999, ISBN: 0-8247-7872-3 , 2001, Autom..