Acoustic oceanographic buoy telemetry system: an ‘advanced’ sonobuoy that meets acoustic rapid environmental assessment requirements

The Acoustic Oceanographic Buoy (AOB) Telemetry System has been designed to meet acoustic rapid environmental assessment requirements. It uses a standard institute of Electrical and Electronics Engineers 802.11 wireless local area network (WLAN) to integrate the air radio network (RaN) and a hydrophone array and acoustic source to integrate the underwater acoustic network (AcN). It offers advantages including local data storage, dedicated signal processing, and global positioning system (GPS) timing and localization. The AOB can also be integrated with other similar systems, due to its WLAN transceivers, to form a flexible network and perform on-line high speed data transmissions. The AOB is a reusable system that requires less maintenance and can also work as a salt-water plug-and-play system at sea as it is designed to operate in free drifting mode. The AOB is also suitable for performing distributed digital signal processing tasks due to its digital signal processor facility.

Automatic parallelization of matricial algorithms

The introduction of parallel processing architectures allowed the real time impelemtation of more sophisticated control algorithms with tighter specifications in terms of sampling time. However, to take advantage of the processing power of these architectures the control engeneer, due to the lack of appropriate tools, must spend a considerable amount of time in the parallelizaton of the control algorithm.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Implementation of an daptive generalized predictive control algorithm over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.