An output feedback structured model reference adaptive control law has been developed for spacecraft rendezvous and docking problems. The effect of bounded output errors on controller performance is studied in detail. Output errors can represent an aggregation of sensor calibration errors, systematic bias, or some stochastic disturbances present in any real sensor measurements or state estimates. The performance of the control laws for stable, bounded tracking of the relative position and attitude trajectories is evaluated, considering unmodeled external as well as parametric disturbances and realistic position and attitude measurement errors. Essential ideas and results from computer simulations are presented to illustrate the performance of the algorithm developed in the paper.

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Reinforced concrete is subjected to deterioration due to aging, increased load, and natural hazards. To minimize the maintenance costs and to increase the operation lifetime, researchers and practitioners are increasingly interested in improving current nondestructive evaluation technologies or building advanced structural health monitoring strategies. Acoustic emission methods offer an attractive solution for nondestructive evaluation/structural health monitoring of reinforced concrete structures. In particular, monitoring the development of cracks is of large interest because their properties reflect not only the condition of concrete as material but also the condition of the entire system at structural level. This article presents a new probabilistic approach based on Gaussian mixture modeling of acoustic emission to classify crack modes in reinforced concrete structures. Experimental results obtained in a full-scale reinforced concrete shear wall subjected to reversed cyclic loading are used to demonstrate and validate the proposed approach.