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Purpose: This paper is to describe development of the features and functions of Repast Simphony, the widely used, free, and open source agent-based modeling environment that builds on the Repast 3 library. Repast Simphony was designed from the ground up with a focus on well-factored abstractions. The resulting code has a modular architecture that allows(More)
Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for(More)
A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were(More)
Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. The lack of accurate and computationally efficient model-based techniques for large, spatially distributed systems leads to challenges in controlling the system. Agent-based control structures provide a powerful tool to(More)
Large-scale spatially distributed systems provide a unique and difficult control challenge because of their nonlinearity, spatial distribution and generally high order. The control structure for these systems tend to be both discrete and distributed as well and contain discrete and continuous elements. A layered control structure interfaced with complex(More)
Agent-based control structures provide flexible and emergent solutions to complex nonlinear problems benefiting from properties such as modularity, adaptability, scalability and robustness. One such problem is product grade transitions in distributed process. The framework proposed earlier (Tetiker, 2006a) is extended by adding several layers of agents to(More)
From a control system perspective, spatially distributed systems offer challenges because of their distributed nature, nonlinearity, and high order. In addition, the control structure for these spatially distributed networks combine discrete and distributed components, in the form of complex arrays of sensors and actuators. Manipulation of the network(More)