Distributed Intelligent Learning and Decision Model Based on Logic Predictive Control
Algorithm 1
Overview of nonlinear model predictive control algorithm.
Offline: determine the parameters Q, P, R, S of the nonlinear model predictive control scheme.
Online: time k = 0, 1, 2.
(1)
The initial state x(k) measured at the initial moment k = 0 and the reference trajectory of a given period, wherein the period T of the reference trajectory of a given period is known.
(2)
The time-varying matrix is obtained by solving the linear matrix inequality.
(3)
By solving the optimization problem, an artificial reference trajectory and an optimization control sequence can be obtained.
(4)
For all I, the controlled object adopts control input.
