scholarly journals Robust predictive control for respiratory CO2 gas removal in closed-loop mechanical ventilation: An in-silico study

2020 ◽  
Vol 6 (3) ◽  
pp. 311-314
Author(s):  
Matthias Schmal ◽  
Jens Haueisen ◽  
Georg Männel ◽  
Philipp Rostalski ◽  
Michael Kircher ◽  
...  
Keyword(s):  
Gas Exchange ◽  
Partial Pressure ◽  
Closed Loop ◽  
Reference Signal ◽  
Control Variable ◽  
System Response ◽  
Breath Hold ◽  
Model Predictive Controller ◽  
Gas Removal ◽  
Predictive Controller

AbstractIn this study a physiological closed-loop system for arterial CO2 partial pressure control was designed and comprehensively tested using a set of models of the respiratory CO2 gas exchange. The underlying preclinical data were collected from 12 pigs in presence of severe changes in hemodynamic and pulmonary condition. A minimally complex nonlinear state space model of CO2 gas exchange was identified post hoc in different lung conditions. The control variable was measured noninvasively using the endtidal CO2 partial pressure. For the simulation study the output signal of the controller was defined as the alveolar minute volume set value of an underlying adaptive lung protective ventilation mode. A linearisation of the two-compartment CO2 gas exchange model was used for the design of a model predictive controller (MPC). It was augmented by a tube based controller suppressing prediction errors due to model uncertainties. The controller was subject to comparative testing in interaction with each of the CO2 gas exchange models previously identified on the preclinical study data. The performance was evaluated for the system response towards the following five tests in comparison to a PID controller: recruitment maneuver, PEEP titration maneuver, stepwise change in the CO2 production, breath-hold maneuver and a step in the reference signal. A root mean square error of 2.69 mmHg between arterial CO2 partial pressure and the reference signal was achieved throughout the trial. The reference-variable response of the model predictive controller was superior regarding overshoot and settling time.

Preliminary evaluation of a predictive controller for a rotary blood pump based on pulmonary oxygen gas exchange

2019 ◽  
Vol 233 (2) ◽  
pp. 267-278 ◽  
Author(s):  
Feng Huang ◽  
Zhe Gou ◽  
Yang Fu
Keyword(s):  
Gas Exchange ◽  
Oxygen Partial Pressure ◽  
Partial Pressure ◽  
Left Ventricular ◽  
Blood Pump ◽  
Rotary Blood Pump ◽  
Blood Pumps ◽  
Control Objective ◽  
Predictive Controller ◽  
Rotary Blood Pumps

Physiological control of rotary blood pumps is becoming increasingly necessary for clinical use. In this study, the mean oxygen partial pressure in the upper airway was first quantitatively evaluated as a control objective for a rotary blood pump. A model-free predictive controller was designed based on this control objective. Then, the quantitative evaluation of the controller was implemented with a rotary blood pump model on a complete cardiovascular model incorporated with airway mechanics and gas exchange models. The results show that the controller maintained a mean oxygen partial pressure at a normal and constant level of 138 mmHg in the left heart failure condition and restored basic haemodynamics of blood circulation. A left ventricular contractility recovery condition was also replicated to assess the response of the controller, and a stable result was obtained. This study indicates the potential use of the oxygen partial pressure index during pulmonary gas exchange when developing a multi-objective physiological controller for rotary blood pumps.

scholarly journals Model Predictive Controller based Unified Power Quality Conditioner for Voltage Regulation Studies in 33- Bus Closed Loop Distribution System

2020 ◽  
Vol 184 ◽  
pp. 01073
Author(s):  
SK. Abdul Pasha ◽  
N. Prema Kumar
Keyword(s):  
Distribution System ◽  
Closed Loop ◽  
Voltage Regulation ◽  
Open Loop ◽  
Voltage Profile ◽  
Model Predictive Controller ◽  
Recent Developments ◽  
Predictive Controller ◽  
Resonant Controller ◽  
Power Quality Conditioner

Recent developments in FACTS have produced U.P.Q.C to mitigate sag and attenuate THD. U.P.Q.C has been urbanized as a FACTS controller between feeding end & far end of distribution system .The U-P-Q-C is capable of improving the voltage profile & reducing THD of distribution system by regulating the voltage using PR (Proportional-Resonant-Controller) and MPC (Model-Predictive) controller. This work proposes U-P-Q-C for Thirty Three Bus Systems .The objective of this work is to enhance-voltage-profile of T-T-B-S. The T-T-B-S in open loop & closed loop-TTBS- U-P-Q-C using PR and MPC-controllers are-modeled,pretend & their consequences are represented. Responses are estimated as a time of settle and error in steady state. The outcomes indicate that MP Controlled T-T-B-S system has better response than PR controlled T-T-B-S system.

An Infinite Model Predictive Controller for Multi Input Nonlinear Processes

2017 ◽  
Author(s):  
Ma’moun Abu-Ayyad ◽  
Abdelkader Abdessameud ◽  
Issam Abu-Mahfouz
Keyword(s):  
Closed Loop ◽  
Nonlinear Functions ◽  
Model Predictive Controller ◽  
Nonlinear Characteristics ◽  
Loop Control ◽  
Dynamic Matrix ◽  
New Strategy ◽  
Predictive Controller ◽  
Process Gain ◽  
Infinite Model

This paper presents a novel algorithm of an infinite model predictive controller for controlling nonlinear multi-input multi-output (MIMO) processes. The new strategy uses a set of continuous nonlinear functions that captures the nonlinear characteristics of the MIMO plant over a wide operating range resulting in a more accurate prediction of the controlled variables. The method formulates a nonlinear dynamic matrix that is manipulated variable dependent during closed-loop control. The proposed algorithm was implemented on a nonlinear MIMO thermal system comprising of three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. The MIMO process has nonlinear parameters such as process gain and time constant that are dependent on the size of the control actions. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.

scholarly journals Linear Model Predictive Control for a Coupled CSTR and Axial Dispersion Tubular Reactor with Recycle

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 711
Author(s):  
Seyedhamidreza Khatibi ◽  
Guilherme Ozorio Cassol ◽  
Stevan Dubljevic
Keyword(s):  
Closed Loop ◽  
Controller Design ◽  
Tubular Reactor ◽  
Coupled System ◽  
Axial Dispersion ◽  
Continuous Stirred Tank Reactor ◽  
Model Predictive Controller ◽  
Luenberger Observer ◽  
In Series ◽  
Predictive Controller

This manuscript addresses a novel output model predictive controller design for a representative model of continuous stirred-tank reactor (CSTR) and axial dispersion reactor with recycle. The underlying model takes the form of ODE-PDE in series and it is operated at an unstable point. The model predictive controller (MPC) design is explored to achieve optimal closed-loop system stabilization and to account for naturally present input and state constraints. The discrete representation of the system is obtained by application of the structure properties (stability, controllability and observability) preserving Cayley-Tustin discretization to the coupled system. The design of a discrete Luenberger observer is also considered to accomplish the output feedback MPC realization. Finally, the simulations demonstrate the performance of the controller, indicating proper stabilization and constraints satisfaction in the closed loop.

Position Control of a 2D Nonlinear Gantry Crane System Using Model Predictive Controller

2015 ◽  
Vol 735 ◽  
pp. 282-288
Author(s):  
Najib K. Dankadai ◽  
Ahmad Athif Mohd Faudzi ◽  
Amir Bature ◽  
Suleiman Babani ◽  
Muhammad I. Faruk
Keyword(s):  
Closed Loop ◽  
Position Control ◽  
Lagrange Equation ◽  
Input Voltage ◽  
Gantry Crane ◽  
Closed Loop System ◽  
Model Predictive Controller ◽  
Loop Control ◽  
Predictive Controller ◽  
Payload Mass

This paper presents the application of model predictive controller for controlling a nonlinear 2D gantry crane system with a DC motor as an actuator. The gantry crane system (GCS) dynamics is derived using Lagrange equation method. A model predictive controller is designed based on the linearised GCS and prediction cost function to ensure accurate positioning and oscillation reduction. Simulation via MATLAB and Simulink was performed to investigate the performance of the model predictive controller on the GCS. The controller test was done under several elements altering the behaviour of the system. The closed loop system was analysed considering different cable length, payload mass and trolley position. It was found that the closed loop control meets the main goal of this work, trolley positioning as fast as possible with minimum payload swinging all within a robust input voltage.

Enlarging the region of stability in robust model predictive controller based on dual-mode control

2021 ◽  
pp. 014233122110123
Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri
Keyword(s):  
Stability Region ◽  
Linear Matrix ◽  
Input State ◽  
Dual Mode ◽  
Model Predictive Controller ◽  
Mode Control ◽  
Robust Model ◽  
Output Constraints ◽  
Predictive Controller ◽  
The Stability

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.

Sign in / Sign up

Export Citation Format

Share Document