Input Shaping is a widely used method of suppressing residual vibrations in point-to-point motion of flexible bodies. It is easy to implement and gives good results if the dynamics of the system are known accurately. However, it is not very robust to system parameter variations. Early methods of increasing the robustness incurred a large time penalty. Hence attempts were made to apply adaptive control to increase the robustness of the shaper. These methods met with varying degrees of success. In this paper, we propose a new adaptive control scheme which is effective in increasing the robustness of the shaper, even in the presence of additive noise in the system output. It is also able to handle sudden changes in the plant parameters. The performance of the system in the presence of high-order unmodelled dynamics is also studied and found to be satisfactory.

This paper proposes communication architecture to support data and command communication for future space missions to moon, Mars and beyond. It postulates a set of satellites placed in halo orbits at Earth-Moon, Sun-Earth and Sun-Mars Lagrangian points and a couple of relay satellites in a heliocentric earth orbit as the base of this architecture. This arrangement is robust to loss of service problems because of the redundancy built into the system. Also, the system significantly reduces the distances over which communication has to be achieved and thus lessens the demands on the communication hardware to be employed. This also results in power saving. The architecture is scalable and can be extended to missions farther out into space. As in the development of any infrastructure, some initial investment has to be made which however will provide returns in the form of simplifying communication procedures and protocols for the many space missions to come.

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Robot Localization is an issue of vital importance for the functioning of autonomous mobile robots. Location information, allows a robot to navigate complex environments and perform local tasks successfully. In mobile sensor networks, this information facilitates important functions like topology control, collision avoidance and development and security of routing protocols. This issue can be divided into the problems of global position estimation, and once that is achieved, of local position tracking. To tackle these, two distinct methods have been used in the past. One is the use of specialized hardware and another is the use of probabilistic Bayesian estimation methods. This paper proposes the use of Fuzzy Logic to tackle this problem. Fuzzy Logic allows us to do away with strict probabilistic rules and to set up heuristic fuzzy rules. It also reduces computation time. A grid-based map is used to describe the environment of the robot and the robot’s confidence in it’s position at each grid-point is determined using sensor measurements. In case the robot is receiving information from multiple sensors, this paper demonstrates the robustness of the scheme to inaccurate sensor information or robot confidence within practical limits. This paper also applies the fuzzy rules to track the robot’s position as it moves. In order to reduce computational cost, this paper proposes limiting the computation of confidences to significant grid-points only.

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