State-space Control for Disturbance Rejection with Multiple Actuators

I am working on designing a controller for an optical beam tracking system with multiple actuators. I can sense the angle of an incoming light beam that moves based on two sources. The first is the movement of the target, which causes a slow movement of the incoming angle of the beam, and the second is the local platform angular jitter, which has both low and high-frequency content.

I have a single detector which detects the sum of these disturbances. I also have two actuators which effectively reject these disturbances. The first actuator has a first-order linear response, with a relatively slow response, and the second actuator has a fast, lowly-damped second order linear response. The first actuator has a large range and the second actuator has a small range.

I have designed a state-space regulator using a kalman estimator and a lqr controller designed in MATLAB with one input (the measured angle) and two outputs (the two actuator commands). However, because the second actuator is range-limited, I would like to pass the low- frequency angular movement to the first actuator, and the high- frequency angular movement to the second actuator. Unfortunately, there seems to be no straightforward way to make this happen. Does anyone have any suggestions on how I can force the regulator to pass the low-frequency components to the first actuator and the high- frequency components to the second? Should I try a different approach to generating the regulator?

thanks, Susheem

Reply to
susheemg
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State space design can be a great method for unifying a large complex system design, but sometimes it can obscure essential features of a design with nonlinear elements such as this one. I suggest you draw out a block diagram for understanding, even if you reduce the design to state space for linear analysis.

You can drive the fast actuator with your beam error, and drive the slow actuator with your fast actuator's position. This will tend to put the 'primary' control on your fast actuator, and if you put an integrator in the path of your slow actuator you'll insure that the fast actuator is centered around zero. Depending on your actuators and your input (especially if your input has an appreciable ramp input) you may need to put double integrators into one or both loop, making them type II.

If you have trouble with the slow actuator not moving out of the way fast enough and you're not saturating it's drive then you aren't giving it enough high-speed content in its drive. You can correct this by giving it some of the error signal from the fast actuator's loop, suitably conditioned. Done right this shouldn't change the stability properties of the system (or may improve them), but should goose the slow actuator into faster motion.

Reply to
Tim Wescott

schrieb im Newsbeitrag news: snipped-for-privacy@q75g2000hsh.googlegroups.com...

I have discussed a similar problem before. The first step is compensating process and controller transfer functions [F1(s)*F2(s)=K]. In practice you have to limit the speed as well as the acceleration of your equipment using jerk filter (3rd order) if you move the set point (target).

First try modeling just one control loop (2nd order). If you succeed then consider trying the next simpler loop.

You can only approach control theory! But this is the only way to get good results.

Compensation: process transfer function: Kp/(1+A1*s^1+A2*s^2) controller transfer function: Kc*(1+B1*s^1+B2*s^2)

F1(s)*F2(s)=K=Kp*Kc

You will have the correct 1st and 2nd derivatives in your model.

I consider a DC amplifier as almost time-compensated. What happens if K is jittering? A DC amplifier or a computer is capable of moving an 'actuator' with very high speed internally.

But you must also filter your real actuator input if you move from theory to practice. This makes things worse but it can't be done better otherwise your actuator will be destroyd.

Yor model output should show speed and acceleration. It's most important!

See similar Problem:

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Remark: v2 may be regarded as actuator input that must be filtered (2. or 3. order) because of jittering.

Reply to
JCH

"JCH" schrieb im Newsbeitrag news:46370c93$0$10194$ snipped-for-privacy@newsspool4.arcor-online.net...

FOR DEMONSTRATION

Using F1(s)*F2(s)=K (K=1) and in series F3(s) I get an open loop

F(s)_open = F1(s)*F2(s)*F3(s)=K*F3(s)

In closed loop F(s)_closed = 1/[1 + 1/F(s)_open]

The solution can be improved using additional

- integral action

- increasing K as high as possible

in real closed loop.

I used process and controller transfer functions

F1(s) = Kp/(1 + A1*s + A2*s^2) F2(s) = Kc*(1 + B1*s + B2*s^2)

A1 = B1 = 0.333 A2 = B2 = 0.00106

compensating.

F3(s) = 1 + 0.1*s + 0.003*s2 + 0.00003*s3

MATLAB should give you the same result.

See also for F1(s)*F2(s)*F3(s) open loop:

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Closed Loop e.g. K=100

1/[1 + 1/(100*F3(s))] will result in staedy state error ~ 1%

That can be corrected using integral action.

Reply to
JCH

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