For a nonlinear process with a generically singular characteristic matrix, input-output linearization is usually not achievable with a static state feedback, and one has to use a dynamic state feedback. A systematic and general approach to input-output linearizing feedback control of nonlinear processes with a generically singular or nonsingular characteristic matrix is presented. Mixed error- and state-feedback, error-feedback, and mixed error- and output-feedback control laws are derived. The derived feedback control laws reject step disturbances asymptotically and induce linear, input-output, closed-loop behavior to the process under consideration. The theoretical connections between the derived control laws and (a) model predictive control and (b) several already-available linear deadtime compensation methods are established. The application and performance of the derived control laws are illustrated and compared with those of model predictive control, by numerical simulation of a chemical reactor.