#Gnu octave devrement for loop code#
#Gnu octave devrement for loop windows#

+++ b/ode45.m 23:31:00.GNU Octave is a high-level language, primarily intended for numerical computations. This further change to ode45 would be needed To completely get rid of the InputParser calls This shoud cut the calls to InputParser in half.

# FIXME: Add an inexact match option once it is available in inputParser. These are the changes I was suggesting to odeset.m : Inbuilt odeset 'odeset' is a function from the file /usr/share/octave/5.2.0/m/ode/odeset.mД§5 runge_kutta_45_dorpri 3.966 14.01 20000 'odeset' is a function from the file /home/user/Documents/odeset.mД§2 runge_kutta_45_dorpri 4.024 14.20 20000 modified odeset 'odeset' is a function from the file /home/user/Documents/odeset.mД§2 runge_kutta_45_dorpri 4.165 13.94 20000 But file diff shows me that the files are same except for commented lines. If there is no practical way to speed up my simulation, I may drop the ode45 all together and do a vanilla Euler integration with plant made into a C++ version for running the inner Euler loop with a small time-step. For my further studies, I would prefer a simulation where the discrete-time effects would be included in the simulation. For initial controller tuning, I have used the continuous time approximation of the controller. I think the only way to simulate a discrete-time control is a loop as shown in the original post. The proposed approach with only one ode45 call does not really simulate a discrete-time control of a continuous-time system where the control input is only updated at the sampling instances and remains constant during the sampling intervals.

So, I would prefer to have those effects also simulated. This is mostly decided by the size of the sampling interval and controller-mode switching dynamics. I need to make an assessment on the accuracy of the achieved result compared to the set-point also. So if I should simulate my controller along with the plant, I would have to use a stiff solver. But there are some вЂњ stiffвЂќ states like controller-mode status-flag, on/off relays etc. Some of those states are linear, smooth states. Second approximation is that my controller has it own states (which I didnвЂ™t show in the example code). In fact, I tuned most of my controller parameters this way. One is that the controller is discrete-time and putting my controller in ode45 makes it a continuous time controller. It involves two approximations from my real-life system. Why not just express your parameter as a function of the state and solve the whole system at once? I have posted this question to the GNU mailing list also.Д¬an you try whether using the attached version of odeset improves the timing? Profiling result # Function Attr Time (s) Time (%) CallsД§5 runge_kutta_45_dorpri 14.695 15.45 67522

% this is where the controller logic would have been written in the real application % reserve space so that it doesn't slow down the program Stepsize = 0.5 % the fixed step used by the controller

#Gnu octave devrement for loop code#

CODE clc ДЇprintf('example profiled running. ') Even for much more complicated (non linear, time varying) differential equations, I am still getting similar results. The code is a minimum working example to illustrate the problem. Is there a way to speed up my simulation ? If the functions at the top of the profile were user written, I could have attempted to convert them to C++ mkoct files.Д«elow is the code and the profiling result. The fixed-time-step part is implemented by the while loop and the continuous time part is implemented by the ode45. I am simulating a system which has both discrete time sub-system (digital control) and continuous time system (plant being controlled). Profiling indicated that most of the execution time is spent inside functions other than the differential equation functions specific to my and runge_kutta_45_dorpri are consuming most of the time. Before optimizing the differential equation I was integrating, I decided to profile the code to see if my differential equation code or the discrete-time-controller code was the bottleneck. Simulation with a loop and ode 45 inside it executed much slower in Octave (5.2 and 6.x) compared to Matlab.

#Gnu octave devrement for loop windows#

System : Debian Linux (Octave 5.2), Windows (Octave 6.x)