Controlled dynamic model with boundary-value problem of minimizing a sensitivity function

We formulate a controlled dynamic model with a boundary-value problem of minimizing a sensitivity function under constraints. Solution of boundary-value problem implicitly defines a terminal condition for the dynamic model. In the model, a unique trajectory corresponds to each control taken from a bounded set. The problem is to select the control such that the corresponding trajectory takes an object from an arbitrary initial state to the terminal state. In this paper, the dynamic model is treated as a problem of stabilization, and the terminal state of the object is interpreted as a state of equilibrium. If under the influence of external disturbances the object loses equilibrium then this object is returned back by selecting the appropriate control. A saddle-point method for solving problem is proposed. We prove its convergence to solution of the problem in all the variables.

[1]  Alexandre Goldsztejn,et al.  On continuation methods for non-linear bi-objective optimization: towards a certified interval-based approach , 2014, Journal of Global Optimization.

[2]  S. Fomin,et al.  Elements of the Theory of Functions and Functional Analysis , 1961 .

[3]  A. Antipin Saddle problem and optimization problem as an integrated system , 2008 .

[4]  A. Antipin,et al.  On methods of terminal control with boundary-value problems: Lagrange approach , 2016 .

[5]  P. Pardalos,et al.  Pareto optimality, game theory and equilibria , 2008 .

[6]  Anatoly S. Antipin,et al.  Two-person game with nash equilibrium in optimal control problems , 2012, Optim. Lett..

[7]  Anatoly S. Antipin,et al.  Extra-proximal methods for solving two-person nonzero-sum games , 2009, Math. Program..

[8]  A. Antipin,et al.  Sensitivity function: Properties and applications , 2011 .

[9]  Alexander S. Poznyak,et al.  Using the extraproximal method for computing the shortest-path mixed Lyapunov equilibrium in Stackelberg security games , 2017, Math. Comput. Simul..

[10]  A. Ioffe,et al.  Theory of extremal problems , 1979 .

[11]  Vimal Singh,et al.  IEEE transactions on systems, man and cybernetics. Part B, Cybernetics , 1996 .

[12]  R. Pytlak Numerical Methods for Optimal Control Problems with State Constraints , 1999 .

[13]  Dynamic method of multipliers in terminal control , 2015 .

[14]  A. Antipin Sensibility Function as Convolution of System of Optimization Problems , 2010 .

[15]  Eugene C. Freuder,et al.  Suggestion Strategies for Constraint-Based Matchmaker Agents , 2002, Int. J. Artif. Intell. Tools.

[16]  Terminal control of boundary models , 2014 .

[17]  Alexander S. Poznyak,et al.  A Stackelberg security game with random strategies based on the extraproximal theoretic approach , 2015, Eng. Appl. Artif. Intell..

[18]  Elena V. Khoroshilova,et al.  Saddle point approach to solving problem of optimal control with fixed ends , 2016, J. Glob. Optim..

[19]  Extragradient method of optimal control with terminal constraints , 2012 .

[20]  K. Glashoff Elster, K.‐H./Reinhardt, R./Schäuble, M./Donath, G., Einführung in die nichtlineare Optimierung. Leipzig. BSB B. G. Teubner Verlagsgesellschaft. 1977. 299 S., M 29, – (Mathem.‐Naturwiss. Bibliothek 63) , 1979 .

[21]  Elena V. Khoroshilova,et al.  Extragradient-type method for optimal control problem with linear constraints and convex objective function , 2013, Optim. Lett..

[22]  A. Antipin,et al.  Optimal control with connected initial and terminal conditions , 2015 .

[23]  N. Osmolovskii,et al.  Sufficient quadratic conditions of extremum for discontinuous controls in optimal control problems with mixed constraints , 2011 .