discrete-time (slew) rate limiting algorithm Consider uniformly-spaced samples of smooth, bandlimited signal observed in noise and subject to some artifacts (small jumps).  Physical restrictions impose a constraint on the maximum magnitude of the derivative of the noiseless, "artifactless" signal.  In an effort to smooth the signal and remove artifacts, I could impose this constraint by simply limiting the size of the sample-to-sample change (e.g., matlab, but this seems like it will introduce other effects to compromise the smoothness of the signal.  

The only other option I came across are nonlinear feedback loops (e.g., see this paper.  I suppose that one could also impose derivative inequality constraints on, say, some local polynomial representation of the signal as well.  Any other ideas, references, etc?

Thanks!
Like the old German saying goes:

If you give a man a filter, everything looks like a signal that needs to be low-pass filtered

or so. 

Slew rate and signal bandwidth are closely related. Simply low-pass filter your signal; usually, you'd do that with a linear filter, not an non-linear filter, and especially not a non-linear recursive one, because those are pretty hard to get stable.

By the way, if you look at FIR and IIR filters, you'll notice that we model these in z-Domain as polynomials, but by doing so, we can apply them to the signal in a linear way.