In situ adaptive tabulation (ISAT) is applied to store and retrieve solutions of nonlinear model predictive control (NMPC) problems. ISAT controls approximation error by adaptively building the database of NMPC solutions with piecewise linear local approximations. Unlike initial state or constraint parameterized constrained quadratic programming (QP) solutions, ISAT approximates NMPC solutions within a specified tolerance, thereby easing the dimensionality difficulties of these other techniques. In the limit, as the specified tolerance is reduced to zero and for linear models with quadratic objective functions, ISAT becomes an adaptive version of state parameterized storage and retrieval of mp-QP problems. (C) 2007 Elsevier Ltd. All rights reserved.