additional_exercises_sol-homework_57-58.pptx -...

This preview shows page 1 - 2 out of 2 pages.

−6 −4 −2 2 4 6 −6 0 x xlabel(’x’); ylabel(’y’); title(’suboptimal’); a xi s ( [ -6 6 -6 6 ] ) ; This script returns 4 randomly-generated nearly optimal trajectories. suboptimal 6 −4 −2 0 2 4 y −6 −4 −2 2 4 6 −6 0 x −4 −2 0 2 4 6 y suboptimal −6 −4 −2 2 4 6 −6 0 x 5 7 −4 −2 0 2 4 6 y suboptimal
−6 −4 −2 2 4 6 −6 0 x −4 −2 0 2 4 6 y suboptimal We see that these nearly optimal trajectories are very, very different. So in this problem there is a weak minimum, i.e. , a very large 1%-suboptimal set. 3.17 Minimum fuel optimal control. Solve the minimum fuel optimal control problem described in exercise 4.16 of Convex Optimization , for the instance with problem data 1 0 . 4 0 . 8 A = 1 0 0 , 0 1 0 1 b = 0 , 0 . 3 x des = 7 6 2 , N = 30 . You can do this by forming the LP you found in your solution of exercise 4.16, or more

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture