Differential evolution techniques for the structure-control design of a five-bar parallel robot

Engineering Optimization

Volumn 42, Issue 6, 2010, Pages 535-565

  Villarreal Cervantes, Miguel G ^a   Cruz Villar, Carlos A ^a   Alvarez Gallegos, Jaime ^a   Portilla Flores, Edgar A ^b  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

^b INSTITUTO POLITÉCNICO NACIONAL   (Mexico)

Author keywords

Differential evolution; Dynamic optimization problem; Integrated design; Parallel robot

Indexed keywords

BAR PARALLEL; CONSTRAINT HANDLING; CONTROL DESIGN; CONTROL PARAMETERS; DECISION VARIABLES; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; DYNAMIC OPTIMIZATION PROBLEMS; EQUALITY CONSTRAINTS; GEOMETRIC PARAMETER; INTEGRATED DESIGNS; KINEMATIC PARAMETERS; MECHANICAL STRUCTURES; MECHATRONIC DESIGN; NON-LINEAR DYNAMICS; OPTIMAL PID CONTROL; PARALLEL ROBOTS; PERFORMANCE CRITERION; PID CONTROLLERS; REDUNDANT PARALLELS; STRUCTURAL PARAMETER;

CONTROL SYSTEM ANALYSIS; EVOLUTIONARY ALGORITHMS; FUZZY CONTROL; MACHINE DESIGN; MECHATRONICS; OPTIMIZATION; PROPORTIONAL CONTROL SYSTEMS; ROBOTS; THREE TERM CONTROL SYSTEMS; TWO TERM CONTROL SYSTEMS;

STRUCTURAL DESIGN;

EID: 77952377109     PISSN: 0305215X     EISSN: 10290273     Source Type: Journal    
DOI: 10.1080/03052150903325557     Document Type: Article

References (33)

1. Affi, Z., El-Kribi, B., and Romdhane, L., 2007. Advanced mechatronic design using a multi-objective genetic algorithm optimization of a motor-driven four-bar system. Mechatronics, 17 (9), 489-500.
2. Alvarez-Gallegos, J., Cruz-Villar, C.A., and Portilla-Flores, E.A., 2005. Evolutionary dynamic optimization of a continuously variable transmission for mechanical efficiency maximization. In: Advances in Artificial Intelligence (MICAI 2005) Proceedings of the 4th Mexican International Conference on Artificial Intelligence,Monterrey, Mexico, 14-18 November 2005, Lectures Notes in Artificial Intelligence Vol. 3789. Heidelberg: Springer-Verlag, 1093-1102.
3. Betts, J.T., 2001. Practical methods for optimal control using nonlinear programming. In: Advances in Design and Control. Philadelphia, PA: SIAM.
4. Bryson, A.E., Jr., 1999. Dynamic Optimization. Menlo Park, CA: Addison-Wesley Longman.
5. Cruz-Villar, C.A., Alvarez-Gallegos, J., and Villarreal-Cervantes, M.G., 2009. Concurrent redesign of an underactuated robot manipulator. Mechatronics, 19 (2), 178-183.
6. Deb, K. and Kain, S., 2003. Multi-speed gearbox design using multi-objective evolutionary algorithms. Journal of Mechanical Design, 125 (3), 609-619.
7. Ghorbel, F.H., et al., 2000. Modeling and set point control of closed-chain mechanisms: theory and experiment. IEEE Transactions on Control Systems Technology, 8 (5), 801-815.
8. Hibbeler, R.C., 2003. Engineering Mechanics: Statics & Dynamics. Englewood Cliffs, NJ: Prentice-Hall.
9. Hunt, K.H., 1983. Structural kinematics of in-parallel-actuated robot-arms. Journal of Mechanism, Transmissions and Automation in Design, 105 (4), 705-712.
10. Kameswaran, S. and Biegler, L.T., 2006. Simultaneous dynamic optimization strategies: recent advances and challenges. Computers and Chemical Engineering, 20 (10-12), 1560-1575.
11. Kim, J.Y., 2006. Task based kinematic design of a two DOF manipulator with a parallelogram five-bar link mechanism. Mechatronics, 16 (6), 323-329.
12. Klein, C.A. and Blaho, B.E., 1987. Dexterity measures for the design and control of kinematically redundant manipulators. International Journal of Robotic Research, 6 (2), 72-83.
13. Li, Q., Zhang,W.J., and Chen, L., 2001. Design for control - a concurrent engineering approach for mechatronics systems design. IEEE/ASME Transactions on Mechatronics, 6 (2), 161-169.
14. Liu, X.J., Wang, J., and Pritschow, G., 2006. Kinematics, singularity and workspace of planar 5R symmetrical parallel mechanisms. Mechanism and Machine Theory, 41 (2), 145-169. (Pubitemid 41689850)
15. Lung-Wen, T., 1999. Robot Analysis: The Mechanics of Serial and Parallel Manipulators. NewYork:Wiley & Sons.
16. Mayorga, R.V. and Carrera, J., 2006. A manipulator performance index based on the Jacobian rate of change: a motion planning analysis. In: IEEE International Conference on Robotics and Automation (ICRA 2006), Orlando, FL, 15-19 May 2006. Piscataway, NJ: IEEE Press, 4220-4226.
17. Mezura-Montes, E., Coello-Coello, C.A., and Tun-Morales, E.I., 2004. Simple feasibility rules and differential evolution for constrained optimization. In: Advances in Artificial Intelligence (MICAI 2004) Proceedings of the 3rd International Conference on Artificial Intelligence, Mexico City, 26-30 April 2004, Lecture Notes in Computer Science Vol. 2972, Heidelberg: Springer-Verlag, 707-716.
18. Mezura-Montes, E., Velázquez-Reyes, J., and Coello-Coello, C.A., 2006. A comparative study of differential evolution variants for global optimization. In: M. Cattolico, ed. Proceedings of the Eighth Annual Genetic and Evolutionary Computation Conference (GECCO), Seattle,WA, 8-12 July 2006. NewYork: ACM, 485-492.
19. Osyczka, A., 1984. Multicriterion Optimization in Engineering with Fortran Programmes. NewYork: Halsted Press.
20. Ouyang, P.R., Li, Q., and Zhang,W.J., 2003. Integrated design of robotic mechanisms for force balancing and trajectory tracking. Mechatronics, 13 (8-9), 887-905.
21. Portilla-Flores, E.A., et al., 2007. Integration of structure and control using an evolutionary approach: an application to the optimal concurrent design of a CVT. International Journal for Numerical Methods in Engineering, 71 (8), 883-890.
22. Price, K., 1999. An Introduction to Differential Evolution. Maidenhead, UK: McGraw-Hill.
23. Price, K.V., Storn, R.M., and Lampinen, J.A., 2005. Differential Evolution: A Practical Approach to Global Optimization. NewYork: Springer-Verlag.
24. Runarsson, T. and Yao, X., 2000. Stochastic ranking for constrained evolutionary optimization. IEEE Transactions on Evolutionary Computation, 4 (3), 284-294.
25. Sadegh, N. and Driessen, B., 1999. Minimum time trajectory optimization and learning. ASME Journal of Dynamic Systems, Measurement, and Control, 121 (2), 213-217.
26. Saravanan, R. and Ramabalan, S., 2008. Evolutionary minimum cost trajectory planning for industrial robots. Journal of Intelligent and Robotic Systems, 52 (1), 45-77.
27. Shiakolas, P., Koladiya, D., and Kebrle, J., 2005. On the optimum synthesis of six bar linkages using differential evolution and the geometric centroid of precision positions technique. Mechanism and Machine Theory, 40 (3), 319-335.
28. Spong, M.W. and Vidyasagar, M., 2004. Robot Dynamics and Control. NewYork:Wiley & Sons.
29. Storn, R.M. and Price, K.V., 1997. Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. Journal of Global Optimization, 11 (4), 341-359.
30. Ting, K.L., 1986. Five-bar Grashof criteria. ASME Journal of Mechanisms, Transmission, and Automation in Design, 108 (4), 533-537.
31. Vesterstrom, J. and Thomsen, R., 2004. A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems. Congress on Evolutionary Computation, 2 (1), 1980-1987.
32. Yoshikawa, T., 1990. Foundations of Robotics. Cambridge, MA: MIT Press.
33. Youcef-Toumi, K., 1996. Modeling, design, and control integration: a necessary step in mechatronics. IEEE/ASME Transactions on Mecatronics, 1 (1), 29-38.