Real time closed loop data based estimation and explicit model based control of an air conditioning system implemented in hardware in loop scheme

2015 ◽  
Author(s):  
Chinmay Sahu ◽  
Radhakrishnan T K ◽  
Sivakumaran N
Keyword(s):  
Real Time ◽  
Air Conditioning ◽  
Closed Loop ◽  
Explicit Model ◽  
Air Conditioning System ◽  
Model Based Control ◽  
Model Based ◽  
Hardware In Loop ◽  
Loop Scheme

Energy optimization using metaheuristic bat algorithm assisted controller tuning for industrial and residential applications

2017 ◽  
Vol 40 (7) ◽  
pp. 2310-2321 ◽  
Author(s):  
VR Divyesh ◽  
Chinmay Sahu ◽  
Velswamy Kirubakaran ◽  
TK Radhakrishnan ◽  
Muralidharan Guruprasath
Keyword(s):  
Predictive Control ◽  
Air Conditioning ◽  
Bat Algorithm ◽  
Constrained Control ◽  
Explicit Model ◽  
Controller Tuning ◽  
Air Conditioning System ◽  
Model Based Control ◽  
Explicit Model Predictive Control ◽  
Plant Data

The advent of model based control provides optimization and constrained control capabilities that can be tailored to specific goals. Metaheuristic algorithms are being researched in various fields owing to their efficiency in providing global optimization. In this paper, both model regression and energy efficiency based controller tuning are attempted using the chaotic bat algorithm (CBA). Two sets of plant data, one from an industrial precalciner temperature loop (PTL) and another from a domestic heating ventilation and air conditioning system (HVAC) are considered. Explicit model predictive control is designed. Minimizing the energy consumption (HVAC) and coal feed rate (PTL) by tuning the controllers is attempted. Results indicate that CBA can be successfully deployed in both regression and achieving control objectives as observed from the case studies.

Closed Loop Control of Resin Flow in VARTM Using a Multi-Segment Injection Line and Real-Time Adaptive, Model-Based Control

Materials ◽  
2005 ◽  
Author(s):  
Ajit R. Nalla ◽  
James L. Glancey
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Performance Metrics ◽  
Void Formation ◽  
Resin Flow ◽  
Time Model ◽  
Loop Control ◽  
Model Based Control ◽  
Model Based ◽  
Injection Line

To improve process controllability during VARTM, a new resin injection line was designed and tested. The injection line, which consists of multiple segments each independently operated, allows for the control of resin flow to different locations within the mold. Simulation of different injection line configurations for various mold geometries is studied. Performance of a prototype line is quantified with a laboratory size mold used to demonstrate the potential value and benefits of this approach. Specific performance metrics, including resin flow front controllability, total injection time and void formation are used to compare this new approach to conventional VARTM injection methods. Computer-based closed loop controller strategies are designed that use point sensor feedback of resin location. In addition, an adaptive control algorithm that uses a finite element model to provide real-time updates of the injection line configuration is presented. Experimental validation of two different control strategies is presented, and demonstrates that real-time, model-based control is possible in VARTM.

Autoregressive modeling of cycle-to-cycle correlations in homogeneous charge compression ignition combustion

2017 ◽  
Vol 19 (7) ◽  
pp. 790-802 ◽  
Author(s):  
Jakob Andert ◽  
Maximilian Wick ◽  
Bastian Lehrheuer ◽  
Christian Sohn ◽  
Thivaharan Albin ◽  
...  
Keyword(s):  
Steady State ◽  
Real Time ◽  
Autoregressive Model ◽  
Closed Loop ◽  
Homogeneous Charge Compression Ignition ◽  
Compression Ignition ◽  
Model Based Control ◽  
Model Based ◽  
Auto Ignition ◽  
Steady State Operation

Homogeneous charge compression ignition or gasoline controlled auto-ignition combustion is characterized by a strong coupling of consecutive cycles, which is caused by residuals from the predecessor cycle. Closed-loop combustion control is considered a promising technology to actively stabilize the process. Model-based control algorithms require precise prediction models that are calculated in real time. In this article, a new approach for the transient measurement of the auto-ignition process and the data-driven modeling of combustion phasing and load is presented. Gasoline controlled auto-ignition combustion is modeled as an autoregressive process to represent the cycle-to-cycle coupling effects. The process order was estimated by partial autocorrelation analysis of steady-state operation measurements. No significant correlations are found for lags that are greater than one. This observation is consistent with the assumption that cycle coupling is mainly caused by the amount of exhaust gas that is directly transferred to the consecutive combustion. Because steady-state operation results in a hard coupling of actuation and feedback variables, only minor variations of the test data can be achieved. The steady-state tests delivered insufficient data for the generalized modeling of the transient autoregressive effects. A new transient testing and measurement approach is required, which maximizes the variation of the predecessor cycle’s characteristics. Dynamic measurements were performed with the individual actuation of the injection strategy for each combustion cycle. A polynomial model is proposed to predict the combustion phasing and load. The regression analysis shows no overfitting for higher polynomial orders; nevertheless, a first-order polynomial was selected because of the good extrapolation capabilities of extreme outliers. The prediction algorithm was implemented in MATLAB/Simulink and transferred to a real-time-capable engine control unit. The verification of the approach was performed by test bench measurements in dynamic operation. The combustion phasing was precisely predicted using the autoregressive model. The combustion phasing prediction error could be reduced by 53% in comparison to a state-of-the-art mean value-based prediction. This work provides the basis for the development of a closed-loop autoregressive model-based control for gasoline controlled auto-ignition combustion.

Hybrid model based refrigerant charge fault estimation for the data centre air conditioning system

2019 ◽  
Vol 106 ◽  
pp. 392-406 ◽  
Author(s):  
Xu Zhu ◽  
Zhimin Du ◽  
Zhijie Chen ◽  
Xinqiao Jin ◽  
Xiaoqing Huang
Keyword(s):  
Hybrid Model ◽  
Air Conditioning ◽  
Fault Estimation ◽  
Air Conditioning System ◽  
Data Centre ◽  
Model Based

Projected Phase-Plane Switching Curves for Vibration Reduction Filters With Negative Amplitudes

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Abhishek Dhanda
Keyword(s):  
Closed Form ◽  
Real Time ◽  
Phase Plane ◽  
Closed Loop ◽  
Vibration Reduction ◽  
Shaping Filter ◽  
Negative Impulse ◽  
Acceleration And Deceleration ◽  
Analytical Expressions ◽  
Loop Scheme

In this paper, we extend the phase-plane based closed-loop scheme of implementing commands shaped with vibration-reduction filters. A generalized shaping filter is considered in this work which can have negative impulse intensities and different acceleration and deceleration limits. Switching conditions are derived in terms of the filter parameters for both convolution-based and closed-form based shaping techniques. Analytical expressions are provided for the switching curves and various schemes are discussed for selecting appropriate phase-planes and implementing shaped-commands on real-time servomechanisms.

Model Based Control for Closed Loop Testing of 1-D Engine Simulation Models*

2012 ◽  
Vol 45 (30) ◽  
pp. 482-489 ◽  
Author(s):  
Dariusz Cieslar ◽  
Alex Darlington ◽  
Keith Glover ◽  
Nick Collings
Keyword(s):  
Closed Loop ◽  
Simulation Models ◽  
Model Based Control ◽  
Engine Simulation ◽  
Model Based
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