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Highlights • A robust dynamic integral sliding mode control (DISMC) is designed for the approximated model to track the desired heating value. • The unknown states required for the model-based control are reconstructed using a gain-scheduled modified Utkin observer (GSMUO). • To guarantee the stability of the overall system, the boundedness of the internal dynamics is also proved. • To make a fair comparison the performance of the proposed controller is compared with an integral sliding mode and a classical PI controllers. Abstract In this paper, a model-based control and state reconstruction of an underground coal gasification (UCG) process is elaborated. In order to deploy model-based control strategies, a sophisticated model of the UCG process based on partial differential equations is approximated with a nonlinear control-oriented model that adequately preserves the fundamental dynamic characteristics of the process. A robust dynamic integral sliding mode control (DISMC) is designed based on the control-oriented model to track the desired heating value, which is one of the key indicators for evaluating the performance of an UCG process. Unknown states required for the model-based control are reconstructed using a gain-scheduled modified Utkin observer (GSMUO). In order to assess the robustness of the nonlinear control and estimation techniques, the water influx phenomenon is considered as an input disturbance. Moreover, the underlying UCG plant model is subjected to parametric variations as well as measurement noise. In order to guarantee the stability of the overall system, the boundedness of the internal dynamics is also proved. To make a fair comparison, the performance of the proposed controller is compared with an integral sliding mode control (ISMC) and a classical proportional-integral (PI) controller. Simulation results highlight the effectiveness of the proposed control scheme in terms of minimum control energy and improved tracking error. Moreover, the simulation study shows that the combination of DISMC and GSMUO exhibit robustness against an input disturbance, parametric uncertainties and measurement noise. [ABSTRACT FROM AUTHOR]

This paper discusses the optimization and control of the one dimensional (1-D) packed bed model of underground coal gasification (UCG) process for an actual UCG site. The optimization is performed to compensate for the uncertainty in coal and char ultimate analysis (caused by repeated measurements of different samples) and in steam to oxygen (O 2 ) ratio at the reaction front. The constrained nonlinear optimization problem is solved by using state of the art sequential quadratic programing (SQP) algorithm to minimize the error between experimental and simulated heating values. The results of the optimized model are validated with actual filed trials which show a good match for heating value of the product gases. The super twisting controller, a second order sliding mode control (SOSMC) algorithm is successfully implemented on the process model, which keeps the heating value of the product gas at the desired level in the presence of the matched disturbance: steam produced from water influx from surrounding aquifers and due to the moisture content of the coal. [ABSTRACT FROM AUTHOR]