This paper deals with multiobjective optimization techniques for a class of hybrid optimal control problems in mechanical systems. We deal with general nonlinear hybrid control systems described by boundary-value problems associated with hybrid-type Euler-Lagrange or Hamilton equations. The variational structure of the corresponding solutions makes it possible to reduce the original “mechanical” problem to an auxiliary multiobjective programming reformulation. This approach motivates possible applications of theoretical and computational results from multiobjective optimization related to the original dynamical optimization problem. We consider first order optimality conditions for optimal control problems governed by hybrid mechanical systems and also discuss some conceptual algorithms. 1. Introduction Hybrid and switched systems have been extensively studied in the past decade, both in theory and practice [1–10]. In particular, driven by engineering requirements, there has been increasing interest in optimal control (OC) of these dynamical systems [1–3, 6, 8, 9, 11–14]. In this paper, we investigate some specific types of hybrid systems, namely hybrid systems of mechanical nature, and the corresponding hybrid optimal control problems. The class of problems to be discussed in this work concerns hybrid systems where discrete transitions are being triggered by the continuous dynamics. The control objective is to minimize a cost functional, where the control parameters are usual control inputs. Recently, there has been considerable effort to develop theoretical and computational frameworks for complex control problems. Of particular importance is the ability to operate such systems in an optimal manner. In many real-world applications a controlled mechanical system presents the main modelling framework and is a strongly nonlinear dynamical system of high order [15–17]. Moreover, the majority of applied optimal control problems governed by sophisticated mechanical systems are problems of hybrid nature. The most real-world mechanical control problems are becoming too complex to allow analytical solution. Thus, computational algorithms are inevitable in solving these problems. There is a number of results scattered in the literature on numerical methods for optimal control problems. One can find a fairly complete review in [1, 2, 11, 12, 18–20]. The aim of our investigations is to use the variational structure of the solution to the two-point boundary-value problem for the controllable hybrid-type Euler-Lagrange or Hamilton equation and to propose a new
References
[1]
V. Azhmyakov and J. Raisch, “A gradient-based approach to a class of hybrid optimal control problems,” in Proceedings of the 2nd IFAC Conference on Analysis and Design of Hybrid Systems, pp. 89–94, Alghero, Italy, 2006.
[2]
V. Azhmyakov, S. A. Attia, and J. Raisch, “On the maximum principle for impulsive hybrid systems,” in Proceedings of the 11th International Workshop on Hybrid Systems: Computation and Control, vol. 4981 of Lecture Notes in Computer Science, pp. 30–42, Springer, 2008.
[3]
V. Azhmyakov, R. Galvan-Guerra, and M. Egerstedt, “Hybrid LQ-optimization using dynamic programming,” in Proceedings of the American Control Conference, pp. 3617–3623, St. Louis, Mo, USA, 2009.
[4]
M. S. Branicky, S. M. Phillips, and W. Zhang, “Stability of networked control systems: explicit analysis of delay,” in Proceedings of the American Control Conference, pp. 2352–2357, Chicago, Ill, USA, 2000.
[5]
P. D. Christofides and N. H. El-Farra, Control of Nonlinear and Hybrid Processes, vol. 324 of Lecture Notes in Control and Information Sciences, Springer, Berlin, Germany, 2005.
[6]
M. Egerstedt, Y. Wardi, and H. Axelsson, “Transition-time optimization for switched-mode dynamical systems,” IEEE Transactions on Automatic Control, vol. 51, no. 1, pp. 110–115, 2006.
[7]
D. Liberzon, Switching in Systems and Control, Birkh?user, Boston, Mass, USA, 2003.
[8]
M. S. Shaikh and P. E. Caines, “On the hybrid optimal control problem: theory and algorithms,” IEEE Transactions on Automatic Control, vol. 52, no. 9, pp. 1587–1603, 2007.
[9]
H. J. Sussmann, “A maximum principle for hybrid optimization,” in Proceedings of the 38th IEEE Conference on Decision and Control (CDC '99), pp. 425–430, Phoenix, Ariz, USA, 1999.
[10]
W. Zhang, M. S. Branicky, and S. M. Phillips, “Stability of networked control systems,” IEEE Control Systems Magazine, vol. 21, no. 1, pp. 84–99, 2001.
[11]
V. Azhmyakov, R. Galvan-Guerra, and A. E. Polyakov, “On the method of Dynamic Programming for linear-quadratic problems of optimal control in hybrid systems,” Automation and Remote Control, vol. 70, no. 5, pp. 787–799, 2009.
[12]
A. Bressan, “Impulsive control systems,” in Nonsmooth Analysis and Geometric Methods in Deterministic Optimal Control, B. Mordukhovich and H. J. Sussmann, Eds., pp. 1–22, Springer, New York, NY, USA, 1996.
[13]
C. G. Cassandras, D. L. Pepyne, and Y. Wardi, “Optimal control of a class of hybrid systems,” IEEE Transactions on Automatic Control, vol. 46, no. 3, pp. 398–415, 2001.
[14]
B. Piccoli, “Hybrid systems and optimal control,” in Proceedings of the 37th IEEE Conference on Decision and Control (CDC '98), pp. 13–18, Tampa, Fla, USA, December 1998.
[15]
J. Baillieul, “The geometry of controlled mechanical systems,” in Mathematical Control Theory, J. Baillieul and J. C. Willems, Eds., pp. 322–354, Springer, New York, NY, USA, 1999.
[16]
A. M. Bloch and P. E. Crouch, “Optimal control, optimization, and analytical mechanics,” in Mathematical Control Theory, J. Baillieul and J. C. Willems, Eds., pp. 268–321, Springer, New York, NY, USA, 1999.
[17]
H. Nijmeijer and A. van der Schaft, Nonlinear Dynamical Control Systems, Springer, New York, NY, USA, 1990.
[18]
E. Polak, Optimization, vol. 124 of Applied Mathematical Sciences, Springer, New York, NY, USA, 1997.
[19]
R. Pytlak, Numerical Methods for Optimal Control Problems with State Constraints, vol. 1707 of Lecture Notes in Mathematics, Springer, Berlin, Germany, 1999.
[20]
K. L. Teo, C. J. Goh, and K. H. Wong, A Unifed Computational Approach to Optimal Control Problems, Wiley, New York, NY, USA, 1991.
[21]
R. Abraham, Foundations of Mechanics, WA Benjamin, New York, NY, USA, 1967.
[22]
F. R. Gantmakher, Lectures on Analytical Mechanics, Nauka, Moscow, Russia, 1966.
[23]
C. D. Aliprantis and K. C. Border, Infinite-Dimensional Analysis, Springer, Berlin, Germany, 2nd edition, 1999.
[24]
V. Azhmyakov, V. G. Boltyanski, and A. Poznyak, “Optimal control of impulsive hybrid systems,” Nonlinear Analysis: Hybrid Systems, vol. 2, no. 4, pp. 1089–1097, 2008.
[25]
V. Azhmyakov, “An approach to controlled mechanical systems based on the multiobjective optimization technique,” Journal of Industrial and Management Optimization, vol. 4, no. 4, pp. 697–712, 2008.
[26]
G. P. Crespi, I. Ginchev, and M. Rocca, “Two approaches toward constrained vector optimization and identity of the solutions,” Journal of Industrial and Management Optimization, vol. 1, no. 4, pp. 549–563, 2005.
[27]
Y. Sawaragi, H. Nakayama, and T. Tanino, Theory of Multiobjective Optimization, vol. 176 of Mathematics in Science and Engineering, Academic Press, Orlando, Fla, USA, 1985.
[28]
B. S. Mordukhovich, Variational Analysis and Generalized Differentiation. I: Basic Theory, II Applications, Springer, Berlin, Germany, 2006.
[29]
F. H. Clarke, Optimization and Nonsmooth Analysis, vol. 5 of Classics in Applied Mathematics, SIAM, Philadelphia, Pa, USA, 2nd edition, 1990.
[30]
B. S. Mordukhovich, Approximation Methods in Problems of Optimization and Optimal Control, Nauka, Moscow, Russia, 1988.