Design and implementation of multi-variable <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mi>∞</mml:mi></mml:msub></mml:mrow></mml:math> robust control for the underground coal gasification project Thar

Javed, Syed Bilal; Uppal, Ali Arshad; Samar, Raza; Bhatti, Aamer Iqbal

doi:10.1016/j.energy.2020.119000

Cited by 12 publications

(5 citation statements)

References 20 publications

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“…Firstly, to implement different design scenarios, as alluded to in the previous paragraph, a customised programming language or toolboxes are required, which are absent in CAVSIM. Although some design aspects, such as synthesising a classical controller, are possible, their implementation requires learning and gaining experience in FORTRAN, which is time-consuming and non-trivial considering the scant advantages it can yield, as demonstrated in our earlier works [10,11]. Thus, it is not well suited and equipped to tackle different design scenarios.…”

Section: Motivationmentioning

confidence: 99%

Development of CAVLAB—A Control-Oriented MATLAB Based Simulator for an Underground Coal Gasification Process

Ahmed

Javed²,

Uppal

et al. 2023

Mathematics

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The Cavity Simulation Model (CAVSIM) is a 3D, parameterisable simulator of the Underground Coal Gasification Process (UCG) that serves as a benchmark for UCG prediction. Despite yielding accurate outputs, CAVSIM has some limitations, which chiefly include inadequate graphical capabilities to visualise cavity geometry and gas production, time-ineffectiveness in terms of parametrisation, i.e., it involves editing, compiling multiple files and checking for errors, and lack of tools to synthesise a controller. Therefore, to compensate for these shortcomings, the services of third-party software, such as MATLAB, must be procured. CAVSIM was integrated with MATLAB to utilise its functionalities and toolboxes such as System Identification, Neural Network, and Optimization Toolbox etc. The integration was accomplished by designing C-mex files, and furthermore, the simulation results in both environments exhibit the same behaviour, demonstrating successful integration. Consequently, CAVSIM has also acquired a controllable structure, wherein parametrisation is now a single-click process; this is demonstrated by a case study outlining the implementation of Model Predictive Control (MPC) on a UCG plant. Moreover, the performance metrics, i.e., Mean Average Error (MAE) and Root Mean Square Error (RMSE) of 0.13, 0.23 for syngas heating value, and 0.012, 0.02 for flowrate quantitatively establishes the efficacy of CAVLAB in designing MPC for the UCG system. The novelty of this work lies in making the software package open-source with the aim of streamlining the research of multiple aspects of the UCG process.

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Section: Motivationmentioning

confidence: 99%

Development of CAVLAB—A Control-Oriented MATLAB Based Simulator for an Underground Coal Gasification Process

Ahmed

Javed²,

Uppal

et al. 2023

Mathematics

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“…In [28], the authors linearized the nonlinear model of [25], using Taylor series approximation around an operating point of interest and designed a linear matrix inequality (LMI) based optimal H 2 /H ∞ controller to keep the heating value on a desired level. In [29], [30], the authors have identified a linear model for the UCG process and then This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

Section: A Related Workmentioning

confidence: 99%

“…The control input is represented by u, and δ represents the external disturbance in terms of water influx from the surrounding aquifers, cf. [27], [36]. The chemical kinetics is mainly dependent on three chemical reactions which take place in-situ and are stated in Table (1).…”

Section: Mathematical Model Of Underground Coal Gasification Processmentioning

confidence: 99%

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Model Predictive Control and Adaptive Kalman Filter Design for an Underground Coal Gasification Process

Chaudhry¹,

Uppal

Bram

2021

IEEE Access

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The control of a nonlinear system such as an underground coal gasification (UCG) process is a challenging task. Several nonlinear design approaches are implemented to improve the tracking performance of the UCG process, however, the nonlinear techniques make implementation complex and computationally inefficient. In this work, a constrained linear model predictive control (MPC) is designed for the UCG process to track the desired trajectory of the heating value, while satisfying actuator constraints pertaining to UCG. The unknown states required for MPC design are reconstructed by using linear adaptive Kalman filter (AKF) and unscented Kalman filter (UKF). The design of MPC and AKF is based on the quasi-linear model of UCG process. A fair comparison is conducted between different control strategies, which include MPC-AKF, MPC-UKF, MPC-gain scheduled modified Utkin observer (GSMUO) and dynamic integral sliding mode control (DISMC)-GSMUO. The quantitative analysis and simulation results show that MPC-AKF outperforms its counterparts by yielding the least tracking error and average control energy. This conclusion holds, even in the presence of an external disturbance, parametric variations, and measurement and process noises. Moreover, MPC-AKF yields 51%, 44% and 46% improvement in absolute relative rootmean-squared error with reference to MPC-UKF, MPC-GSMUO and DISMC-GSMUO, respectively. A quantitative analysis has also been carried for AKF and UKF, which shows that the performance of AKF is more robust against the changes in the initial values of measurement and process covariances.INDEX TERMS Model predictive control (MPC); underground coal gasification (UCG); adaptive Kalman filter (AKF); unscented Kalman filter (UKF); energy conversion systems.

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“…Compared with traditional coal mining technology, UCG has significant advantages in safety, economy, and environmental protection. As an in situ coal utilization technology, UCG has been paid much attention by many countries in the development of clean and efficient coal production and utilization, and it is a new strategic industry in China 10 . UCG differs from surface gasification in that the gasification object is the entire coal seam, including partings consisting of gangue minerals.…”

Section: Introductionmentioning

confidence: 99%

Sequential transformation study of minerals during underground coal gasification: Promising to indirectly reflect the actual reaction condition

Wang

et al. 2021

Asia-Pacific J Chem Eng

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The mineralogical characteristics of underground coal gasification (UCG) residuals are closely related to the gasification conditions. The study of the mineral composition and transformation of ash and slag under different gasification conditions has important scientific significance for understanding the real gasification conditions, improving the utilization efficiency of coal, and identifying and controlling the environmental impact. In this paper, the sequential transformation of minerals under different temperature and atmosphere are studied by X‐ray diffraction (XRD) and FactSage software, and the elemental composition of the surface of the UCG ash and slag is characterized by SEM‐EDX. The results show that the main minerals in the semicoke are quartz (SiO2), illite (K1.5Al4(Si6.5Al1.5)O20(OH)4), and sanidine (KAlSi3O8). In the 900–1300°C reduction, ash, quartz, sanidine, hercynite (FeAl2O4), anorthite (CaAl2Si2O8), and mullite (Al6Si2O13) are the main minerals. The minerals in the oxidation residuals (1100–1500°C) are quartz, anorthite, hematite (Fe2O3), hercynite, cordierite (Fe2Al4Si5O18), and cristobalite. The reaction temperature has a significant effect on the changes in mineralogy. The reaction temperature is low during the pyrolysis process, and most changes involve only structural changes. With the reaction temperature increases, a series of reactions occur between different minerals. The reaction atmosphere also has a significant effect on the mineralogy. The research on the transformation of minerals in UCG residues can indirectly reflect the actual process of UCG, which can provide suggestions for the stable operation of the UCG process.

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Design and implementation of multi-variable H∞ robust control for the underground coal gasification project Thar

Cited by 12 publications

References 20 publications

Development of CAVLAB—A Control-Oriented MATLAB Based Simulator for an Underground Coal Gasification Process

Development of CAVLAB—A Control-Oriented MATLAB Based Simulator for an Underground Coal Gasification Process

Model Predictive Control and Adaptive Kalman Filter Design for an Underground Coal Gasification Process

Sequential transformation study of minerals during underground coal gasification: Promising to indirectly reflect the actual reaction condition

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