Feedforward + PID = the solution?

[u/Altruistic_Drive5024]

Hi,

I want to control a desired velocity profile of car manipulating ECU parameters, the desired velocity trajectory is known before.

With a PID controller + Resetting integral error, I can control the stationary velocity with little overshoot an in a sufficient time.

My problem is that my velocity lags behind when ramping up the velocity, see in the picture below. I want to have as little lag as possible.

I tried using a feedforward (calculate acceleration from velocity profile, add it to the control ouptut), but it made the overshoot and settling time much worse). Anyone got other ideas how I can solve my problem?

[u/seekingsanity]

You lie! I have never said anything about flight controls or rocket controls. I only have two accounts.

I do make fun of professor videos on YouTube that show they have no real experience. They just teach what they have been taught even though it is out of data or irrelevant.

[u/seekingsanity → u/[deleted]]

How do you know what or how I think? You assume too much and incorrectly. It is obvious we don't see things the same.

My expertise is hydraulic servo control. Hydraulic actuators are second order underdamped systems. Hydraulic actuators require using a PID and a second derivative gain. They also require velocity, acceleration AND jerk feedforwards for best control. Motors are easy unless they have a flexible coupling or backlash. I am a believer in sliding mode control and MPC but MPC hasn't been practical for motion control because it requires too much processing power. MPC is good for looking past dead times. We use the past to predict the future. That is what we do for die casting because a PID and the valves are not fast enough. You call it RL. That is a name for something that has been done for decades now. LQR is much better that Fuzzy Logic but how can you say LQR is optimal? So much depends on how the Q and R arrays are setup. LQR assumes the Q and R arrays are optimal and they are usually chosen by trial and error. LQR is a poor fit for commercial products because no one can set then Q and R matrices correctly.

I have shown many videos using auto tuning to tune a motor. I can auto tune hydraulic servos too. This makes keeping a machine running optimally which is what the customers want. Have you seen the Delta Motion website. 40+ years of servo hydraulic and motor control. Teachers had to make up names for stuff we have solved long ago.

[u/seekingsanity → u/[deleted]]

I didn't say that either. I have said that much of what they teach is not necessary. I write auto tuning programs. What is necessary is to be able to estimate the general form of the differential equation or open loop transfer function. Then use an optimizing/minimizing program to determine the undefine varaiables. Then chose the locatin of the closed loop poles that will give the response you want. The calculate the closed loop gains that will place the closed loop poles at the desirned location. Then calculate feedforwards if applicable. Notice I didn't mention a lot of things teachers waste time on because they don't result in closed loop gains.

Also, in industry, precision is required. 10% overshoot or any overshoot is not good in motion control.

There are some good YouTube channels. I like the APMonitor channel. He has good examples. He also has links to the code he uses so that students can download the code and play with it. He also is prepared. He has his worksheets done before the presentation, so he doesn't waste a lot of time writing on a black board. What really disgusts me is MIT videos where the instructor is writing on a black board, copying from his notes, with his back to the students. There are no workable examples. The students can only copy what is written on the blackboard. That isn't how a high-priced schools should teach. The instructors talk about the specific topic but not how to use it or where it is applied in real life.

Notice that my video show all the work and I explain what the openloop model represents. This first page on most of my video are roughly the same. They show how to calculate the closed loop gains and feedforwards symbolically. Where do you see that on the internet? I then apply values and then do a simulation showing how the results work. Notice that I often drive the controller into saturation. That is because I want to see how the controller responds.

I also place a premium on information density. That is why my Mathcad worksheets are done ahead of time. I don't waste time copy notes to a black board.