Stability analysis of a linear model predictive control and its application in a water recovery process

Research output: Journal contributionsJournal articlesResearchpeer-review

Standard

Stability analysis of a linear model predictive control and its application in a water recovery process. / Mercorelli, Paolo.
In: Advances in Science, Technology and Engineering Systems, Vol. 4, No. 5, 01.01.2019, p. 314-320.

Research output: Journal contributionsJournal articlesResearchpeer-review

Harvard

APA

Vancouver

Bibtex

@article{0612e0f6316742cbbc5cc2945b8ab0ce,
title = "Stability analysis of a linear model predictive control and its application in a water recovery process",
abstract = "This paper examines application of linear general model predictive control (LGMPC). The stability of the LGMPC is proven by means of a demonstration of a theorem stating a sufficient and constructive condition. Lower bounds conditions are found for one of these matrices and then a system with saturation is taken into consideration. The conditions can be interpreted through physical aspects. The results obtained were tested by means of computer simulations and an example with a water recovery process is considered.",
keywords = "Applications, Model Predictive Control, Stability Analysis, Engineering",
author = "Paolo Mercorelli",
year = "2019",
month = jan,
day = "1",
doi = "10.25046/aj040540",
language = "English",
volume = "4",
pages = "314--320",
journal = "Advances in Science, Technology and Engineering Systems",
issn = "2415-6698",
publisher = "ASTES Publishers",
number = "5",

}

RIS

TY - JOUR

T1 - Stability analysis of a linear model predictive control and its application in a water recovery process

AU - Mercorelli, Paolo

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper examines application of linear general model predictive control (LGMPC). The stability of the LGMPC is proven by means of a demonstration of a theorem stating a sufficient and constructive condition. Lower bounds conditions are found for one of these matrices and then a system with saturation is taken into consideration. The conditions can be interpreted through physical aspects. The results obtained were tested by means of computer simulations and an example with a water recovery process is considered.

AB - This paper examines application of linear general model predictive control (LGMPC). The stability of the LGMPC is proven by means of a demonstration of a theorem stating a sufficient and constructive condition. Lower bounds conditions are found for one of these matrices and then a system with saturation is taken into consideration. The conditions can be interpreted through physical aspects. The results obtained were tested by means of computer simulations and an example with a water recovery process is considered.

KW - Applications

KW - Model Predictive Control

KW - Stability Analysis

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85079287169&partnerID=8YFLogxK

U2 - 10.25046/aj040540

DO - 10.25046/aj040540

M3 - Journal articles

AN - SCOPUS:85079287169

VL - 4

SP - 314

EP - 320

JO - Advances in Science, Technology and Engineering Systems

JF - Advances in Science, Technology and Engineering Systems

SN - 2415-6698

IS - 5

ER -

Documents

DOI

Recently viewed

Publications

  1. Dynamic Lot Size Optimization with Reinforcement Learning
  2. Constraint breeds creativity
  3. Introducing parametric uncertainty into a nonlinear friction model
  4. Need Satisfaction and Optimal Functioning at Leisure and Work: A Longitudinal Validation Study of the DRAMMA Model
  5. Switching Dispatching Rules with Gaussian Processes
  6. A computational study of a model of single-crystal strain-gradient viscoplasticity with an interactive hardening relation
  7. A Wavelet Packet Algorithm for Online Detection of Pantograph Vibrations
  8. Comparison of different FEM codes approach for extrusion process analysis
  9. Active and semi-supervised data domain description
  10. Faulty Process Detection Using Machine Learning Techniques
  11. Contextual movement models based on normalizing flows
  12. Lyapunov Convergence Analysis for Asymptotic Tracking Using Forward and Backward Euler Approximation of Discrete Differential Equations
  13. A Lean Convolutional Neural Network for Vehicle Classification
  14. Analyzing User Journey Data In Digital Health: Predicting Dropout From A Digital CBT-I Intervention
  15. Recognition and approach responses toward threatening objects
  16. Effectiveness of a guided multicomponent internet and mobile gratitude training program - A pragmatic randomized controlled trial
  17. Formative Perspectives on the Relation Between CSR Communication and CSR Practices
  18. Global Finite-Time Stabilization of Planar Linear Systems With Actuator Saturation
  19. Sensitivity to complexity - an important prerequisite of problem solving mathematics teaching
  20. Towards a spatial understanding of identity play
  21. Supporting the Development and Implementation of a Digitalization Strategy in SMEs through a Lightweight Architecture-based Method
  22. Dispatching rule selection with Gaussian processes
  23. Web-scale extension of RDF knowledge bases from templated websites
  24. Interpreting Strings, Weaving Threads
  25. Constraints are the solution, not the problem
  26. An extended analytical approach to evaluating monotonic functions of fuzzy numbers
  27. Advantages and disadvantages of different text coding procedures for research and practice in a school context
  28. Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units
  29. Robust Flatness Based Control of an Electromagnetic Linear Actuator Using Adaptive PID Controller
  30. Segment Introduction
  31. Empowering materials processing and performance from data and AI
  32. Changes in the Complexity of Limb Movements during the First Year of Life across Different Tasks
  33. Comparison of Bio-Inspired Algorithms in a Case Study for Optimizing Capacitor Bank Allocation in Electrical Power Distribution