Nonlinear and Adaptive Control for Bioinspired Microrobots

Francisco Maria Ferreira Rodrigues Gonçalves

We envision the deployment of swarms of bioinspired microrobots to assist humans in criticalapplications such as search and rescue, wildlife monitoring and investigation, inspecting vessels and marine infrastructures, and research on shallow-water reefs, just to mention a few examples. However, due to their size, these robots have challenges associated with actuation, sensing, electronics, and energy-storage capacity. To help overcome the inherent energy limitations of these robots, this dissertation presents novel control methodologies that significantly reduce power requirements during operation. Specifically, we introduce new attitude nonlinear switching control frameworks for selecting the most cost-efficient direction of the torque input and new types of axis–angle attitude control laws that are particularly well-suited for the proposed switching control methods. The suitability, functionality, and performance of all these approaches are validated through real-time experiments using a 31-gram small quadrotor. However, the successful implementation of these control strategies on microrobots remains dependent upon further improvements to the existing control frameworks for these platforms. Therefore, in this dissertation, we also lay the groundwork for the implementation of these methods on two different types of bioinspired microrobots—flying and swimming. In the case of flying microrobots—because motion-capture systems are still necessary to measure their attitude—the efficacy of these control strategies also depends on the vehicle’s ability to maintain its desired position during high-speed rotational maneuvers to prevent it from flying out of the small motion-capture area. Therefore, for this type of robot, we introduce a model-reference adaptive control (MRAC) architecture to enhance positional tracking and validate its suitability through real-time experiments on the Bee++, a 95-mg insect-scale flapping-wing aerial vehicle. In the case of surface swimming microrobots, because they operate on the water surface and can be driven by SMA-based actuators, they have the capability to carry the energy and power electronics required for control. However, several challenges regarding estimation and control still remain to be addressed before the proposed switching methodologies can be implemented. To help mitigate these challenges, we introduce a simple estimation and control strategy and validate its functionality by presenting the first feedback-control experiments of two autonomous insect-scale surface robotic swimmers weighing less than 1 gram.

Nonlinear and Adaptive Control for Bioinspired Microrobots

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