Probably the first step would be to see how well the controller is performing. The easy way to do this is to see how well the measurements are following the setpoints, but this doesn't really tell you how well your controller is doing as the usual reason why a measurement isn't on setpoint is because there's disturbances entering the process (and if there weren't disturbance, you wouldn't really need a controller). But of course you don't know the size of the disturbance as it changes with time, which means the error variance doesn't really tell you if you need a new controller.
To answer one of your questions above, you cannot use the closed loop data for validation of your models - many have tried, all have failed, more or less. And it's because generally the only reason the plant is moving is because of the disturbances, and you don't know what these are. If you did, they'd be feedforward variables. And don't think you can just wait for a setpoint change - they're done by a higher level controls or operators, and these guys are often making their changes in response to a disturbance.
What to do? There are packages available that do measure controller performance without plant tests - all you need is an estimate of the deadtime, but you probably have that from the previous plant tests. The number given by these packages is scaled from 0 to 1, and just indicates how close you are to an "optimal" controller. So if your current control is bad, as indicated by these packages, then it's time to remodel (assuming the economics are there as well). And to answer your last question, they will tell you how much improvement you can expect to get with better models.
Ok, I should point out the I work for a company that sells this stuff. You can find more info at
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