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Industrial process control has been dominated by closed architectures and proprietary protocols for the last three decades. In the late 1990’s, the advent of open fieldbus and middleware standards has greatly changed the process control arena. Fieldbus has pushed control closer and closer to the process itself. Middleware standards have exposed real-time process data to higher level software applications. Control systems can now be designed to minimize the reconfiguration costs associated with design changes. How can Advanced Life Support (ALS) benefit from these technologies? We consider designing the control system for the BIO-Plex and evaluate how complex it will be, the effort it will require, and how much it will it cost. Various fieldbus technologies were compared and Foundation Fieldbus was chosen for detailed evaluation. This new fieldbus was integrated with an existing ALS system.

The Advanced Integration Matrix (AIM) project at the Johnson Space Center (JSC) was chartered to study and solve systems-level integration issues for exploration missions. One of the first issues identified was an inability to conduct trade studies on control system architectures due to the absence of mature evaluation criteria. Such architectures are necessary to enable integration of regenerative life support systems. A team was formed to address issues concerning software and hardware architectures and system controls.. The team has investigated what is required to integrate controls for the types of non-linear dynamic systems encountered in advanced life support. To this end, a water processing bioreactor testbed is being developed which will enable prototyping and testing of integration strategies and technologies.

Technologies that facilitate the design and control of complex, hybrid, and resource-constrained systems are examined. This paper focuses on design methodologies, and system architectures, not on specific control methods that may be applied to life support subsystems. It has been estimated that 60–80% of the effort in developing complex control systems is software development, and only 20–40% is control system development [1]. It has also been shown that large software projects have failure rates of as high as 50–65% [2,3]. Concepts discussed include the Unified Modeling Language (UML) and design patterns with the goal of creating a self-improving, self-documenting system design process. Successful architectures for control must not only facilitate hardware to software integration, but must also reconcile continuously changing software with much less frequently changing hardware [4]. These architectures rely on software modules or components to facilitate change.