Efficient move blocking strategy for multiple shooting‐based non‐linear model predictive control

Abstract

Move blocking (MB) is a widely used strategy to reduce the degrees of freedom of the Optimal Control Problem (OCP) arising in receding horizon control. The size of the OCP is reduced by forcing the input variables to be constant over multiple discretization steps. In this paper, we focus on developing computationally efficient MB schemes for multiple shooting based nonlinear model predictive control (NMPC). The degrees of freedom of the OCP is reduced by introducing MB in the shooting step, resulting in a smaller but sparse OCP. Therefore, the discretization accuracy and level of sparsity is maintained. A condensing algorithm that exploits the sparsity structure of the OCP is proposed, that allows to reduce the computation complexity of condensing from quadratic to linear in the number of discretization nodes. As a result, active-set methods with warm-start strategy can be efficiently employed, thus allowing the use of a longer prediction horizon. A detailed comparison between the proposed scheme and the nonuniform grid NMPC is given. Effectiveness of the algorithm in reducing computational burden while maintaining optimization accuracy and constraints fulfillment is shown by means of simulations with two different problems.

Dynamic Process Operation Under Demand Response – A Review of Methods and Tools

“…Apart from that, inexact schemes have been suggested in [80] allowing for offline computation of sensitivity. In addition to those, numerous alternative formulations such as move blocking [81], efficient input parametrization [82], or successive linearization [11] have been investigated.…”

Suboptimal nonlinear model predictive control with input move-blocking

“…Thus, with this approach, input move-blocking is another source of suboptimality. Chen et al [15] also notice this relationship, however, do not elaborate on this connection. By introducing some buffer in which the manually generated warm-starts can be stored between two consecutive closed-loop steps, important closed-loop properties of suboptimal MPC hold for MBMPC without further adjustment.…”

Investigation on the Model-Based Control Performance in Vehicle Safety Critical Scenarios with Varying Tyre Limits

“…The real-time iteration scheme (RTI) [ 47 ] is employed to reduce the time required to solve the ( 9 ) problem. Moreover, a non-uniform grid strategy [ 48 ] has been used for lowering the computational burden and let the controller predict a sufficiently long horizon (chosen 400 m in advance for the specific vehicle).…”