An improved two‐loop model predictive control design for nonlinear robust reference tracking with practical advantages

• Published in: Optimal control applications & methods Vol. 42; no. 2; pp. 548 - 565
• Main Authors: Farajzadeh‐D., Mohammad‐G., Sani, S. K. Hosseini
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.03.2021; Wiley Subscription Services, Inc
• Subjects: Algorithms; constraint satisfaction; Nonlinear control; nonlinear model predictive control; Predictive control; reference trajectory tracking; Robust control; terminal cost relaxation; Tracking problem
• ISSN: 0143-2087; 1099-1514
• DOI: 10.1002/oca.2691

Summary In this paper, the nonlinear robust reference tracking problem is considered and an Improved Two‐Loop Nonlinear Model Predictive Control (ITL‐NMPC) design is proposed for a pre‐controlled system with bounded uncertainties subject to input and state constraints. In the industry, this scheme leads the lower design cost and fewer implementation risks since (i) it allows the existing controller to remain unchanged without any manipulation, (ii) it does not need the open‐loop model of the pre‐controlled system, and (iii) it does not require the terminal cost and constraint definition. For the proposed ITL‐NMPC, a practical parameter tuning algorithm is introduced and its robust exponential stability, as well as recursive feasibility, are guaranteed. Simulation results are used to better illustrate the effectiveness of the proposed approach and show that the proposed method not only improves the control performance of the pre‐controlled system but also reduces the design cost while satisfying the constraints.