Efficiently Solving the Harmonic Model Predictive Control Formulation

نویسندگان

چکیده

Harmonic model predictive control (HMPC) is a (MPC) formulation that displays several benefits over other MPC formulations, especially when using small prediction horizon. These benefits, however, come at the expense of an optimization problem no longer typical quadratic programming derived from most linear formulations due to inclusion particular class second-order cone constraints. This article presents method for efficiently dealing with these constraints in operator splitting methods, leading computation time solving HMPC line state-of-the-art solvers MPC. We show how apply this result alternating direction multipliers algorithm, presenting solver we compare against literature, including formulations. The results proposed solver, and by extension formulation, suitable its implementation embedded systems.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficiently solving multiple objective optimal control problems

This paper discusses an improved method for solving multiple objective optimal control (MOOC) problems, and efficiently obtaining the set of Pareto optimal solutions. A general MOOC procedure has been introduced in Logist et al. [2007], to derive optimal generic temperature profiles for a steady-state tubular plug flow reactor. This procedure is based on a weighted sum of the different costs, a...

متن کامل

Robustified Nonlinear Model Predictive Control via a Min-Max Formulation

Nonlinear model predictive control (NMPC) is an appealing control method as it allows to control multi-input multi-output processes while taking constraints into account. It is based on successively solving open-loop optimal control problems. Although NMPC schemes may naturally exhibit a certain degree of inherent robustness, an explicit consideration of process uncertainties is preferable, par...

متن کامل

A Formulation of Nonlinear Model Predictive Control Using Automatic Differentiation

The computational burden, which obstacles Nonlinear Model Predictive Control techniques to be widely adopted, is mainly associated with the requirement to solve a set of nonlinear differentiation equations and a nonlinear dynamic optimisation problem in real-time online. In this work, an efficient algorithm has been developed to alleviate the computational burden. The new approach uses the auto...

متن کامل

A mixed-integer model predictive control formulation for linear systems

Most industrial model predictive controllers (MPC) use the traditional two-layer structure developed in the early 1980’s, where the upper layer defines optimal steady-state targets for inputs and outputs, while the lower layer calculates the control moves that drive the system towards these steady-state targets. Typically both layers use continuous quadratic programming (QP) formulations to der...

متن کامل

Solving Evacuation Problems Efficiently —

Earliest arrival flows capture the essence of evacuation planning. Given a network with capacities and transit times on the arcs, a subset of source nodes with supplies and a sink node, the task is to send the given supplies from the sources to the sink “as quickly as possible”. The latter requirement is made more precise by the earliest arrival property which requires that the total amount of ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Transactions on Automatic Control

سال: 2023

ISSN: ['0018-9286', '1558-2523', '2334-3303']

DOI: https://doi.org/10.1109/tac.2022.3220555