  In this paper, a novel partial form dynamic linearization (PFDL) data-driven
model-free adaptive predictive control (MFAPC) method is proposed for a class
of discrete-time single-input single-output nonlinear systems. The main
contributions of this paper are that we combine the concept of MPC with MFAC
together to propose a novel MFAPC method. We prove the bounded-input
bounded-output stability and tracking error monotonic convergence of the
proposed method; Moreover, we discuss the possible relationship between the
current PFDL-MFAC and the proposed PFDL-MFAPC. The simulation and experiment
are carried out to verify the effectiveness of the proposed MFAPC.
