This paper is devoted to a short presentation of the use we did of nonparametric estimation theory for the estimation, filtering and control of un- certain dynamic systems. The fundamental advantage of this approach is its low dependence from any a priori modeling assumptions about uncertain dynamic com- ponents. It appears to be of great interest for the control of general discrete-time processes, and in particular biotechnological processes, which are emblematic of nonlinear uncertain and partially observed systems.