The performance enhancement of distributed systems through decentralized control and sensor fusion

One solution to the problem of controlling distributed systems involves using decentralized control for each separate subsystem, taking into account of the relevant information from other interconnected subsystems. The adaptive control system described allows one to achieve an independent motion of plant outputs due to the elimination of interconnections between channels by local feedback, and simultaneously compensates the uncertainties of plant parameters. The desirable motion of subsystems outputs can be accomplished by using relevant reference models in each local subsystem. An information matrix, which is based on the errors between the velocity of the rotor shaft of a motor and its reference velocity, is constructed for each local subsystem. A decentralized Kalman filter is employed on each subsystem as a sensor fusion device. This allows graceful degradation of the overall performance if some local units fail or interconnection are broken. Computer simulation examples of adaptive decentralized control of electric motors with a common load are presented