There are PIDs but usually only the Proportional part of the PID algorithm is usually used

Mapping systems, as used in diesel engines

But make a several layer PIDs is difficult.

Map based systems (as example used in turbines or diesel engines) needs a lot of testing and works usually with new machines in controlled conditions

It would be better using an algorithm that adapt and slow increases or decreases control signal in order to obtain maximum performance.

Also some algorithm should advise of modifications out of expected values to advise about problems, making an efficient diagnosys of the system

I should need to use this kind of algorithm to control my simulations to reduce number of simulations but also to control my Miranda and Fusion Reactors

Perhaps some of the algorithms can be: Neural Networks, MultiLayer Perceptrons (MLP) and Radial Basis Function (RBF) networks. Also the new Support Vector Regression (SVR)