Adaptive control of a two-link planar manipulator using nonlinear Model predictive control

A Model predictive control (MPC) calculates a control input for tracking the system output to a reference trajectory which is an ideal trajectory for the system output to converge on a desired value. In MPC, the parameters of controlled systems are needed for calculating of the control input, and these parameters are treated as well-known and invariable parameters. However, the parameters of system are variable in real system and that is a cause of deterioration in the control performance. Then, in this paper, an adaptive controller for a two-link planar manipulator on the horizontal space via nonlinear model predictive control (NMPC) is proposed. In proposed method, system's parameters are estimated by using past states of systems and control inputs, and the estimated parameters are used in calculating of control inputs. In order to show the effectiveness of the proposed NMPC controller, numerical simulations comparing between the proposed method and the previous method are performed.