A novel ontological approach to modelling engineering processes: A coupled tank system case study

Many modelling techniques such as Artificial Neural Network (ANN) and SIMULINK have been employed in engineering processes such as control systems. However, these techniques lack some beneficial features such as the auto-classification and self-awareness of knowledge, the dynamic knowledge discovery, validating the consistency of knowledge and the possibilities of embedding Semantic Web Rule Language (SWRL) rules into various modelling tasks. This paper presents an original and innovative ontology design that models the coupled tanks system (CTS) with additional capabilities of providing aforementioned advantages. This new approach for modelling engineering phenomena employs the Web Ontology Language (OWL) and also processes the capabilities of incorporating Description Logics (DL) and Semantic Web technologies into the ontology-based design. The results obtained in this paper show the successful demonstration and implementation of our new knowledge modelling approach.

[1]  Benjamin N. Grosof,et al.  Supporting Rule System Interoperability on the Semantic Web with SWRL , 2005, SEMWEB.

[2]  Boris Motik,et al.  OWL 2: The next step for OWL , 2008, J. Web Semant..

[3]  Stephen John Turner,et al.  A Data-Driven Crowd Simulation Model Based on Clustering and Classification , 2013, 2013 IEEE/ACM 17th International Symposium on Distributed Simulation and Real Time Applications.

[4]  Robert Sutton,et al.  A novel real-time non-linear wavelet-based model predictive controller for a coupled tank system , 2014, J. Syst. Control. Eng..

[5]  Gancho Vachkov,et al.  An integrated approach to intelligent modeling of industrial plants , 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).

[6]  Sanjay Sharma,et al.  Nonlinear model predictive control strategy based on soft computing approaches and real time implementation on a coupled-tank system , 2013 .

[7]  David J. Murray-Smith.  An Application of the Individual Channel Analysis and Design Approach to Control of a Two-input Two-output Coupled-tanks System , 2012 .

[8]  T. K. Radhakrishnan,et al.  Real-coded Genetic Algorithm for system identification and tuning of a modified Model Reference Adaptive Controller for a hybrid tank system , 2013 .

[9]  Chris A McMahon,et al.  Progress with OntoCAD: A Standardised Ontological Annotation Approach to CAD Systems , 2011 .

[10]  Sanjay Sharma,et al.  A wavelet neural network based non-linear model predictive controller for a multi-variable coupled tank system , 2015, Int. J. Autom. Comput..

[11]  Chris A McMahon,et al.  Annotation in Design Processes: Classification of Approaches , 2009 .

[12]  Zhiyong Feng,et al.  A Novel Combination of Reasoners for Ontology Classification , 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

[13]  Li Ding,et al.  Using Ontologies in the Semantic Web: A Survey , 2005, Ontologies.