for more practical simulation of an optimal control problem, I need to consider the computation time which is needed for solving optimization in optimal control (regardless of discretization and optimization method I use in Matlab). For example, in MPC control, I need to consider the optimization calculation time in order to obtain a control action as the states of system evolve in time with their own dynamic speed (For example stable systems with larger negative eigenvalues have faster dynamic )
Yo can use tic-toc (tic before function call, toc after function call). An alternative way is to use the Matlab profiler
https://www.mathworks.com/help/matlab/ref/profile.html
Dear Ali,
Within the individual nodes, the controllers are often implemented as one or several tasks on a digital computer with a real-time operating system. In that case you can use tic-toc function call as suggested. Often the Matlab distributes the tasks in multi platforms to solve the optimization program according to your requirements (e.g., communication and user interfaces). The operating system typically uses multiprogramming to multiplex the execution of the various tasks. The CPU time and the communication bandwidth can hence be viewed as shared resources for which the tasks compete. In that case tic-toc may not work that smoothly.
Thanks for your answers, but I ask a different question. I know the computation time of codes can be calculated using tic toc function. But what I mean is that like a practical optimal control that the computational time should be considered inorder to establishe results on the convergence, in simulation I need to consider the delay required for computation of u(t).
For example in MPC if I calculate u(t1) with high computation time, during the time of my computation the system states evolve and become x(t4) t4>t1(4 sample time ahead of my control)
So my controller may result in an unstable closed loop system.
So I need to consider optimization computation time separate from dynamic of system.
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