According to "On Electrohydraulic Pressure Control for Power Steering Applications:" it was shown that state feedback works good at hydraulic systems. Most of the time, PID controllers are used to control hydraulic systems, but even LQG/LQR controllers works very good to. Especially for MIMO hydraulic systems.
Page 125:
The linear controller is much simpler and easier to implement and its performance is good over the entire working region
But according to the article on page 124:
One way to improve the performance of the linear controller could be to use gain scheduling in order to meet the variable plant dynamics
It's because hydraulic system is nonlinear system. So then I was thinking which controller can do a better control?
Adaptive controllers may not fit hydraulic systems because adaptive controllers requires that the dynamic system varies over time. Adaptive controllers is very good for stochastic systems e.g air plane.
Predictive controllers may not fit hydraulic systems either, because predictive controllers want to have a very slow system with delays e.g chemical plant.
So then I have to choose fast controllers: LQR, PID or $H_{\infty}$ controller.
PID controllers are all ready excluded because the question is "a better PID".
$H_{\infty}$ is to difficult to implement in real processes, according to control engineers with experience. $H_{\infty}$ is only good for laboratory or system which don't need to be re-tuned once it has been tuned in, e.g hard disk drive.
Now it's only one option left - state feedback, which is LQR/LQG (Predictive control can also be state feedback).
But the problem with LQR and LQG is they both has static gains such as control law and kalman filter gain. LQR/LQG control is just a matrix with real constants. They don't change.
Question:
My question is if it's possible to implement gain scheduling with fuzzy controller for a LQG/LQG controller? The user choose some parameter scheduling by life experience. Then the fuzzy controller changing the control law and the kalman filter gain depending on the plant dynamics.
Would this work, or will it be a very bad implementation?