I am working on a dyamic control of a mobile robot. I have developed a nonlinear dynamic model. What I am not sure is how accurate the dynamic model is needed in order to have a stable optimal control output?

If the robot is stable by itself, set all your gains to zero.

If you want more than just a stable robot you may need to use more information than what you've shared with us.

I've got a pretty jaundiced view of "optimal control". It works great, as long as you jigger the process by putting a cost on the control variables. This is almost never done because the control variables are expensive -- it's done to fake the algorithm into making a 'safer' controller, and the margins are hard to figure out.

I suggest you try the high-control-variable-cost approach, but go back and check your system for stability as you vary the parameters of of your plant. If you want to do this in a formal manner, study up on robust control.

Thanks for your suggestions. Yes, I have picked a control cost and control variable and obtained a two point boundary value problem, which is solved by using relaxtion method. The process requires iteration. But it is not too bad for a P3 machine. What is the high-control-variable-cost approach? I have not studied robust control. What is the main difference between optimal control and robust control? Can you tell me the pros and cons of the two methods?

Thanks a lot and have a nice weekend,

Everett ps. You have given me quite a few suggestions already on the selection of brushless vs. step motor, optimal control etc before. Thanks a lot.

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It is a matter of means that you use. The following refers to linear and nonlinear systems:

The transfer function should be as accurate as possible.

Then you can find best feedforward use.

In addition disturbances should also be best compensated.

What I mean can be seen in an example with 2 disturbances:

Page 1: Definitions Page 2: PID control Page 3: PID and feedforward Page 4: PID and feedforward and disturbance compensations

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The examples are based on a linear system. The linear ODEs can be replaced by nonlinear ODEs if known. The process transfer function can be preferably found via measurements.

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