A FIRST APPROACH TO AN ARTIFICIAL NETWORKED COGNITIVE CONTROL SYSTEM BASED ON THE SHARED CIRCUITS MODEL OF SOCIOCOGNITIVE CAPACITIES

Abstract

The top priority in high-performance manufacturing processes is the development of a new generation of control systems to enable faster, more efficient manufacturing by means of cooperative, self-organized, self-optimized behaviour. Some natural cognitive systems display effective behaviour through perception, action, deliberation, communication, and interaction with other individuals and with the environment. An artificial cognitive control architecture is presented which is based on the shared circuits model (SCM) of sociocognitive skills proposed by Hurley.1 The proposal consists of a five-layer architecture in which the SCM approach is used to emulate such sociocognitive skills as imitation, deliberation, and mindreading. In Hurley’s approach, these capacities can be enabled by mechanisms of control, mirroring the actions of others, and simulation. A control system thus designed should be capable of responding efficiently and robustly to the problems it is set. In the present implementation, the original SCM approach was enriched and modified in the light of constructive suggestions and evaluations in the literature. With these modifications, SCM served as the foundation for the design of a networked control architecture for application to an industrial case study – a high-performance drilling process. Experiments demonstrated that the proposed artificial cognitive control system can deal with nonlinearities and uncertainties in the drilling process, providing a good transient response and good error-based performance indices.