This technical note presents an output feedback controller and observer design approach for linear time-invariant systems with unknown dynamics. The presented method uses an open-loop reference model to generate the desired trajectory and a closed-loop reference model as an observer. The controller only uses the observer states. Lyapunov-based stability proofs show that the error states converge asymptotically to zero and that all other signals are uniformly stable. Furthermore, bounds are proven on the transient behavior.

No abstract

Aquaculture net cage inspection and maintenance is a central issue in fish farming. Inspection using autonomous underwater vehicles is a promising solution. This paper proposes laser-camera triangulation for pose estimation to enable autonomous net following for an autonomous vehicle. The laser triangulation 3D data is experimentally compared to a doppler velocity log (DVL) in an active fish farm. We show that our system is comparable in performance to a DVL for distance and angular pose measurements. Laser triangulation is promising as a short distance ranging sensor for autonomous vehicles at a low cost compared to acoustic sensors.

Aquaculture robotics is receiving increased attention and is subject to unique challenges and opportunities for research and development. Guidance, navigation and control are all important aspects for realizing aquaculture robotics solutions that can greatly benefit the industry in the future. Sensor technologies, navigation methods, motion planners and state control all have a role to play, and this paper introduces some technologies and methods that are currently being applied in research and industry before providing some examples of challenges that can be targeted in the future.

The design of controllers and observers often relies on first order models of the system in question. These models are often obtained either through step-response tests, through on-line or off-line identification or through development of a mathematical model. When the system in question has unknown or uncertain parameters, the developed model also contains uncertainties and the controller/observer design may result in bad performance or even instability. In this paper we present a combined design of a controller and an observer for scalar linear time-invariant systems with unknown parameters. We combine a model reference adaptive controller, which does not require a model of the system, with a Luenberger observer which uses the desired closed-loop dynamics as its model. We show through Lyapunov theory and by application of Barbǎlat's lemma that all error states in the closed-loop system converge to zero and that all signals are bounded. CCS CONCEPTS • Computing methodologies → Control methods; Modeling and simulation; • Applied computing → Engineering;