Egerstedt standard problem

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Egerstedt standard problem
State dimension: 1
Differential states: 3
Discrete control functions: 3
Path constraints: 1
Interior point equalities: 3

The Egerstedt standard problemm is the problem is of an academic nature and was proposed by Egerestedt to highlight the features of an Hybrid System algorithm in 2006 [Egerstedt2006]Author: M. Egerstedt; Y. Wardi; H. Axelsson
Journal: IEEE Transactions on Automatic Control
Pages: 110--115
Title: Transition-time optimization for switched-mode dynamical systems
Volume: 51
Year: 2006
Link to Google Scholar
. It has been used since then in many MIOCP research studies (e.g. [Jung2013]Author: M. Jung; C. Kirches; S. Sager
Booktitle: Facets of Combinatorial Optimization -- Festschrift for Martin Gr\"otschel
Editor: M. J\"unger and G. Reinelt
Pages: 387--417
Publisher: Springer Berlin Heidelberg
Title: On Perspective Functions and Vanishing Constraints in Mixed-Integer Nonlinear Optimal Control
Url: http://www.mathopt.de/PUBLICATIONS/Jung2013.pdf
Year: 2013
Link to Google Scholar
) for benchmarking of MIOCP algorithms.


Mathematical formulation

The mixed-integer optimal control problem after partial outer convexification is given by


\begin{array}{llclr}
 \displaystyle \min_{x, \omega} & x_3(t_f)   \\[1.5ex]
 \mbox{s.t.} 
 & \dot{x}_1 & = & -x_1\omega_1 + (x_1+x_2)\omega_2+(x_1-x_2)\omega_3, \\
 & \dot{x}_2 & = & (x_1+2x_2)\omega_1+(x_1-2x_2)\omega_2+(x_1+x_2)\omega_3, \\
 & \dot{x}_3 & = & x_1^2+x_2^2,  \\[1.5ex]
 & x(0) &=& (0.5, 0.5, 0)^T, \\
 & x_2(t) & \geq & 0.4, \\
 & 1 &=& \sum\limits_{i=1}^3\omega_i(t), \\
 & \omega(t) &\in&  \{0, 1\}, 
\end{array}

for t \in [t_0, t_f]=[0,1] .

Reference Solutions

If the problem is relaxed, i.e., we demand that w(t) be in the continuous interval [0, 1] instead of the binary choice \{0,1\}, the optimal solution can be determined by using a direct method such as collocation or Bock's direct multiple shooting method.

The optimal objective value of the relaxed problem with  n_t=6000, \, n_u=40  is x_3(t_f)=1.0.995906234. The objective value of the binary controls obtained by Combinatorial Integral Approimation (CIA) is x_3(t_f) =3.20831942. The binary control solution was evaluated in the MIOCP by using a Merit function with additional Lagrange term  100 \max\limits_{t\in[0,1]}\{0,0.4-x_2(t)\}  .


Source Code

Model description is available in


References

[Egerstedt2006]M. Egerstedt; Y. Wardi; H. Axelsson (2006): Transition-time optimization for switched-mode dynamical systems. IEEE Transactions on Automatic Control, 51, 110--115Link to Google Scholar
[Jung2013]M. Jung; C. Kirches; S. Sager (2013): On Perspective Functions and Vanishing Constraints in Mixed-Integer Nonlinear Optimal Control. Facets of Combinatorial Optimization -- Festschrift for Martin Gr\"otschelLink to Google Scholar




We present numerical results for a benchmark MIOCP from a previous study [157] with the addition of switching constraints. In its original form, the problem was:


After partial outer convexification with respect to the integer control v, the binary convexified counterpart problem reads