Difference between revisions of "F-8 aircraft"

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=== Optimica ===
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=== jModelica ===
  
 
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Model descriptions are available in
 
Model descriptions are available in
  
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* [[:Category:AMPL | AMPL]] at [[F-8 aircraft (AMPL)]]
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* [[:Category:AMPL | AMPL code]] at [[F-8 aircraft (AMPL)]]
 
* [[:Category:Muscod | Muscod code]] at [[F-8 aircraft (Muscod)]]
 
* [[:Category:Muscod | Muscod code]] at [[F-8 aircraft (Muscod)]]
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* [[:Category:optimica | optimica]] at [[F-8 aircraft (optimica)]]
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* [[:Category:JModelica | JModelica code]] at [[F-8 aircraft (JModelica)]]
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* [[:Category:JModelica | JModelica]] at [[F-8 aircraft (JModelica)]]
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== Variants ==
 
== Variants ==

Latest revision as of 09:29, 27 July 2016

F-8 aircraft
State dimension: 1
Differential states: 3
Discrete control functions: 1
Path constraints: 2
Interior point equalities: 6


The F-8 aircraft control problem is based on a very simple aircraft model. The control problem was introduced by Kaya and Noakes and aims at controlling an aircraft in a time-optimal way from an initial state to a terminal state.

The mathematical equations form a small-scale ODE model. The interior point equality conditions fix both initial and terminal values of the differential states.

The optimal, relaxed control function shows bang bang behavior. The problem is furthermore interesting as it should be reformulated equivalently.

Mathematical formulation

For t \in [0, T] almost everywhere the mixed-integer optimal control problem is given by

\begin{array}{llcl} \displaystyle \min_{x, w, T} & T \\[1.5ex] \mbox{s.t.} & \dot{x}_0 &=& -0.877 \; x_0 + x_2 - 0.088 \; x_0 \; x_2 + 0.47 \; x_0^2 - 0.019 \; x_1^2 - x_0^2 \; x_2 + 3.846 \; x_0^3 \\ &&& - 0.215 \; w + 0.28 \; x_0^2 \; w + 0.47 \; x_0 \; w^2 + 0.63 \; w^3 \\ & \dot{x}_1 &=& x_2 \\ & \dot{x}_2 &=& -4.208 \; x_0 - 0.396 \; x_2 - 0.47 \; x_0^2 - 3.564 \; x_0^3 \\ &&& - 20.967 \; w + 6.265 \; x_0^2 \; w + 46 \; x_0 \; w^2 + 61.4 \; w^3 \\ & x(0) &=& (0.4655,0,0)^T, \\ & x(T) &=& (0,0,0)^T, \\ & w(t) &\in& \{-0.05236,0.05236\}. \end{array}

x_0 is the angle of attack in radians, x_1 is the pitch angle, x_2 is the pitch rate in rad/s, and the control function w = w(t) is the tail deflection angle in radians. This model goes back to Garrard[Garrard1977]Author: Garrard, W.L.; Jordan, J.M.
Journal: Automatica
Pages: 497--505
Title: Design of Nonlinear Automatic Control Systems
Volume: 13
Year: 1977
Link to Google Scholar.

In the control problem, both initial and terminal values of the differential states are fixed.

Reformulation

The control w(t) is restricted to take values from a finite set only. Hence, the control problem can be reformulated equivalently to

\begin{array}{llcl} \displaystyle \min_{x, w, T} & T \\[1.5ex] \mbox{s.t.} & \dot{x}_0 &=& -0.877 \; x_0 + x_2 - 0.088 \; x_0 \; x_2 + 0.47 \; x_0^2 - 0.019 \; x_1^2 - x_0^2 \; x_2 + 3.846 \; x_0^3 \\ &&& - \left( 0.215 \; \xi - 0.28 \; x_0^2 \; \xi - 0.47 \; x_0 \; \xi^2 - 0.63 \; \xi^3 \right) \; w \\ &&& - \left( - 0.215 \; \xi + 0.28 \; x_0^2 \; \xi - 0.47 \; x_0 \; \xi^2 + 0.63 \; \xi^3 \right) \; (1 - w) \\ & &=& -0.877 \; x_0 + x_2 - 0.088 \; x_0 \; x_2 + 0.47 \; x_0^2 - 0.019 \; x_1^2 - x_0^2 \; x_2 + 3.846 \; x_0^3 \\ &&& + 0.215 \; \xi - 0.28 \; x_0^2 \; \xi + 0.47 \; x_0 \; \xi^2 - 0.63 \; \xi^3 \\ &&& - \left( 0.215 \; \xi - 0.28 \; x_0^2 \; \xi - 0.63 \; \xi^3 \right) \; 2 w \\ & \dot{x}_1 &=& x_2 \\ & \dot{x}_2 &=& -4.208 \; x_0 - 0.396 \; x_2 - 0.47 \; x_0^2 - 3.564 \; x_0^3 \\ &&& - \left( 20.967 \; \xi - 6.265 \; x_0^2 \; \xi -46 \; x_0 \; \xi^2 - 61.4 \; \xi^3 \right) \; w \\ &&& - \left( - 20.967 \; \xi + 6.265 \; x_0^2 \; \xi -46 \; x_0 \; \xi^2 + 61.4 \; \xi^3 \right) \; (1 - w) \\ & &=& -4.208 \; x_0 - 0.396 \; x_2 - 0.47 \; x_0^2 - 3.564 \; x_0^3 \\ &&& + 20.967 \; \xi - 6.265 \; x_0^2 \; \xi + 46 \; x_0 \; \xi^2 - 61.4 \; \xi^3 \\ &&& - \left( 20.967 \; \xi - 6.265 \; x_0^2 \; \xi - 61.4 \; \xi^3 \right) \; 2 w \\ & x(0) &=& (0.4655,0,0)^T, \\ & x(T) &=& (0,0,0)^T, \\ & w(t) &\in& \{0,1\}, \end{array}

with \xi = 0.05236. Note that there is a bijection between optimal solutions of the two problems.

Reference solutions

We provide here a comparison of different solutions reported in the literature. The numbers show the respective lengths t_i - t_{i-1} of the switching arcs with the value of w(t) on the upper or lower bound (given in the second column). Claim denotes what is stated in the respective publication, Simulation shows values obtained by a simulation with a Runge-Kutta-Fehlberg method of 4th/5th order and an integration tolerance of 10^{-8}.

Arc w(t) Lee et al.[Lee1997a]Author: Lee, H.W.J.; Teo, K.L.; Rehbock, V.; Jennings, L.S.
Journal: Dynamic Systems and Applications
Pages: 243--262
Title: Control Parametrization Enhancing Technique for Time-Optimal Control Problems
Volume: 6
Year: 1997
Link to Google Scholar 		Kaya[Kaya2003]Author: C.Y. Kaya; J.L. Noakes
Journal: Journal of Optimization Theory and Applications
Pages: 69--92
Title: A Computational Method for Time-Optimal Control
Volume: 117
Year: 2003
Link to Google Scholar 		Sager[Sager2005]Address: Tönning, Lübeck, Marburg
Author: S. Sager
Editor: ISBN 3-89959-416-9
Publisher: Der andere Verlag
Title: Numerical methods for mixed--integer optimal control problems
Url: http://mathopt.de/PUBLICATIONS/Sager2005.pdf
Year: 2005
Link to Google Scholar 		Schlueter/ Gerdts Sager
1 1 0.00000 0.10292 0.10235 0.0 1.13492
2 0 2.18800 1.92793 1.92812 0.608750 0.34703
3 1 0.16400 0.16687 0.16645 3.136514 1.60721
4 0 2.88100 2.74338 2.73071 0.654550 0.69169
5 1 0.33000 0.32992 0.32994 0.0 0.0
6 0 0.47200 0.47116 0.47107 0.0 0.0
Claim: Infeasibility - 1.00E-10 7.30E-06 5.90E-06 3.29169e-06 2.21723e-07
Claim: Objective - 6.03500 5.74217 5.72864 4.39981 3.78086
Simulation: Infeasibility - 1.75E-03 1.64E-03 5.90E-06 3.29169e-06 2.21723e-07
Simulation: Objective - 6.03500 5.74218 5.72864 4.39981 3.78086

The best known optimal objective value of this problem given is given by T = 3.78086. The corresponding solution is shown in the rightmost plot. The solution of bang-bang type switches three times, starting with w(t) = 1.

  • Reference solution plots

  • Locally optimal relaxed control on a coarse control discretization grid and corresponding differential states.

  • Locally optimal relaxed control on a fine, adaptively chosen control discretization grid and corresponding differential states.

  • Integer control and corresponding differential states from Sager[Sager2005]Address: Tönning, Lübeck, Marburg
    Author: S. Sager
    Editor: ISBN 3-89959-416-9
    Publisher: Der andere Verlag
    Title: Numerical methods for mixed--integer optimal control problems
    Url: http://mathopt.de/PUBLICATIONS/Sager2005.pdf
    Year: 2005
    Link to Google Scholar    .

  • Integer control and corresponding differential states from Schlueter/ Gerdts solution.

  • Best known integer control and corresponding differential states from Sager solution.

jModelica

Objective  : 5.12799232 infeasibility : 6.2235588037251599e-10

  • Obtained solution plots

  • (Probably sub-)Optimal control.

  • Corresponding differential states.

Source Code

Model descriptions are available in

Variants

Miscellaneous and Further Reading

See [Kaya2003]Author: C.Y. Kaya; J.L. Noakes
Journal: Journal of Optimization Theory and Applications
Pages: 69--92
Title: A Computational Method for Time-Optimal Control
Volume: 117
Year: 2003
Link to Google Scholar and [Sager2005]Address: Tönning, Lübeck, Marburg
Author: S. Sager
Editor: ISBN 3-89959-416-9
Publisher: Der andere Verlag
Title: Numerical methods for mixed--integer optimal control problems
Url: http://mathopt.de/PUBLICATIONS/Sager2005.pdf
Year: 2005
Link to Google Scholar for details.

References

[Garrard1977]Garrard, W.L.; Jordan, J.M. (1977): Design of Nonlinear Automatic Control Systems. Automatica, 13, 497--505Link to Google Scholar
[Kaya2003]C.Y. Kaya; J.L. Noakes (2003): A Computational Method for Time-Optimal Control. Journal of Optimization Theory and Applications, 117, 69--92Link to Google Scholar
[Lee1997a]Lee, H.W.J.; Teo, K.L.; Rehbock, V.; Jennings, L.S. (1997): Control Parametrization Enhancing Technique for Time-Optimal Control Problems. Dynamic Systems and Applications, 6, 243--262Link to Google Scholar
[Sager2005]S. Sager (2005): Numerical methods for mixed--integer optimal control problems. (%edition%). Der andere Verlag, Tönning, Lübeck, Marburg, %pages%Link to Google Scholar
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