NDLI: Computationally efficient model predictive control for a class of linear parameter-varying systems

Content Provider	IET Digital Library
Author	Cavanini, Luca Cimini, Gionata Ippoliti, Gianluca
Abstract	The use of linear parameter varying (LPV) prediction models has been proven to be an effective solution to develop model predictive control (MPC) algorithms for linear and non-linear systems. However, the computational effort is a crucial issue for LPV-MPC, which has severely limited its application especially in embedded control. Indeed, for dynamical systems of dimension commonly found in embedded applications, the time needed to form the quadratic programming (QP) problem at each time step, can be substantially higher than the average time to solve it, making the approach infeasible in many control boards. This study presents an algorithm that drastically reduces this computational complexity for a particular class of LPV systems. They show that when the input matrix is right-invertible, the rebuild phase of the QP problem can be accelerated by means of a coordinate transformation which approximates the original formulation. Then they introduce a variant of the algorithm, able to further reduce this time, at the cost of a slightly increased sub-optimality. The presented results on vehicle dynamics and electrical motor control confirm the effectiveness of the two novel methods, especially in those applications where computational load is a key indicator for success.
Starting Page	1384
Ending Page	1392
Page Count	9
ISSN	17518644
Volume Number	12
e-ISSN	17518652
Issue Number	Issue 10, Jul (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/12/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2017.1096
Journal	IET Control Theory & Applications
Publisher Date	2018-03-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	A.C. Machine Average Time Computational Complexity Computational Effort Computational Load Computationally Efficient Model Predictive Control Control Boards Control of Electric Power System Control System Analysis Control System Synthesis Crucial Issue D.C. Machines Effective Solution Electric Motors Electrical Motor Control Embedded Application Embedded Control Linear Parameter-varying System Linear System LPV Prediction Model LPV System LPV-MPC Machine Control Model Predictive Control Algorithm Optimal Control Optimisation Technique Predictive Control QP Problem Quadratic Programming Quadratic Programming Problem Synthesis Method Time Varying Control System Time Varying System Vehicle Dynamics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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