It's all a tradeoff of how system response vs. stability and how much overshoot is tolerable.
For the domains I've worked in, with physical components, system response isn't instantaneous, but some level of overshoot is tolerable as long as the system rapidly converges and (this is the important part) cannot end up in a positive feedback scenario. The derivative term tends to amplify noise, which is never what you want.
A little anti-windup, some generous limits around your max extents, and perhaps a gear-shift to switch bandwidths when you approach steady-state, and it's surprising how many problems can be solved with a filter and a PI controller for the closed-loop component of the system. Maybe the actuator is walking you up and down a complicated model space, maybe you've got multiple PIs driving multiple models...but there's a good chance a PI will do a decent job somewhere in the solution.
Use a PID if you want to make more work for yourself.
Specifics will depend on your exact system.
For the domains I've worked in, with physical components, system response isn't instantaneous, but some level of overshoot is tolerable as long as the system rapidly converges and (this is the important part) cannot end up in a positive feedback scenario. The derivative term tends to amplify noise, which is never what you want.
A little anti-windup, some generous limits around your max extents, and perhaps a gear-shift to switch bandwidths when you approach steady-state, and it's surprising how many problems can be solved with a filter and a PI controller for the closed-loop component of the system. Maybe the actuator is walking you up and down a complicated model space, maybe you've got multiple PIs driving multiple models...but there's a good chance a PI will do a decent job somewhere in the solution.
Use a PID if you want to make more work for yourself.
Specifics will depend on your exact system.