Predictive reference shaping for constrained robotic systems using evolutionary algorithms

This paper proposes a method for reducing the trajectory tracking errors of robotic systems in presence of input saturation and state constraints. Basing on a finite horizon prediction of the future evolution of the robot dynamics, the proposed device online preshapes the reference trajectory, minimizing a multi-objective cost function. The shaped reference is updated at discrete time intervals and is generated taking into account the full nonlinear robot dynamics, input and state constraints. A specialized Evolutionary Algorithm is employed as search tool for the online computation of a sub-optimal reference trajectory in the discretized space of the control alternatives. The effectiveness of the proposed method and the online computational burden are analyzed numerically in two significant robotic control problems; furthermore a comparison of the performance provided by this method and an iterative gradient-based algorithms are discussed.

[1]  Eduardo F. Camacho,et al.  Model predictive control in the process industry , 1995 .

[2]  J. Bobrow,et al.  Time-Optimal Control of Robotic Manipulators Along Specified Paths , 1985 .

[3]  V. Goggos,et al.  Evolutionary predictive control (EPC) , 1996 .

[4]  M.L. Fravolini,et al.  Improving trajectory tracking by feedforward evolutionary multivariable constrained optimization , 1999, 1999 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Cat. No.99TH8399).

[5]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[6]  William R. Cluett,et al.  Nonlinear model-based predictive control of control nonaffine systems , 1997, Autom..

[7]  Riccardo Rovatti,et al.  IJAR Special Issue dedicated to the International Summer School: Fuzzy logic control advances in methodology , 1999, Int. J. Approx. Reason..

[8]  Claudio De Persis,et al.  Proceedings of the 38th IEEE conference on decision and control , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[9]  Antti J. Koivo,et al.  Nonlinear predictive control with application to manipulator with flexible forearm , 1999, IEEE Trans. Ind. Electron..

[10]  Ali M. S. Zalzala,et al.  Near Time-Optimal Collision-Free Motion Planning of Robotic Manipulators Using an Evolutionary Algorithm , 1996, Robotica.

[11]  Lars Nielsen,et al.  Torque-limited path following by online trajectory time scaling , 1990, IEEE Trans. Robotics Autom..

[12]  Shudong Sun,et al.  Trajectory planning of multiple coordinating robots using genetic algorithms , 1996, Robotica.

[13]  Robert Babuška,et al.  Genetic algorithms for optimization in predictive control , 1997 .

[14]  D. B. Fogel,et al.  Applying evolutionary programming to selected control problems , 1994 .

[15]  William A. Sethares,et al.  Nonlinear parameter estimation via the genetic algorithm , 1994, IEEE Trans. Signal Process..

[16]  D. Kohli,et al.  Near-Minimum Time Feedback Controller for Manipulators Using On-Line Time Scaling of Trajectories , 1996 .

[17]  Der-Cherng Liaw,et al.  Contact Friction Compensation for Robots Using Genetic Learning Algorithms , 1998, J. Intell. Robotic Syst..

[18]  Kevin M. Passino,et al.  Genetic Adaptive and Supervisory Control , 2000 .

[19]  Mario Luca Fravolini,et al.  Intermittent Feedback Strategies for the Predictive Control of a Flexible Link: Experimental Results , 2000 .

[20]  Daniel R. Lewin,et al.  Automated Nonlinear Model Predictive Control using Genetic Programming , 2002 .

[21]  Xavier Blasco,et al.  Generalized predictive control using genetic algorithms (GAGPC) , 1998 .

[22]  Kevin M. Passino,et al.  Intelligent control for brake systems , 1999, IEEE Trans. Control. Syst. Technol..

[23]  Kang G. Shin,et al.  Minimum-time control of robotic manipulators with geometric path constraints , 1985 .

[24]  R. Luus.  Optimal control by dynamic programming using systematic reduction in grid size , 1990 .

[25]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[26]  Robert Babuska,et al.  Fuzzy model-based predictive control using Takagi-Sugeno models , 1999, Int. J. Approx. Reason..

[27]  P. Gawthrop,et al.  A globally valid continuous-time GPC through successive system linearisation , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).