Actuators

The Cyber-Physical Systems (CPSs) and Internet of Things (IoT) have become emerging and essential technologies of the past few decades that connect various heterogeneous systems and devices. Sensors and actuators are fundamental units in most CPS and IoT systems, they are used extensively in vehicle systems, smart health care systems, smart buildings and cities, and many other types of applications. The extensive use of sensors and actuators, coupled with their increasing connectivity, exposes them to a wide range of threats. Given their integration into various systems and the use of multiple technologies, it is very useful to characterize their functions abstractly. For concreteness, we study them here in the context of autonomous cars. An autonomous car is an example of a CPS, which includes IoT applications. For instance, IoT units allow an autonomous car to be connected wirelessly to roadside units, other vehicles, and fog and cloud systems. Also, the IoT allows them to collect and share information on traffic, navigation, roads, and other aspects. An autonomous car is a complex system, not only due to its intricate design but also because it operates in a dynamic environment, interacting with other vehicles and the surrounding infrastructure. To manage these functions, it must integrate various technologies from different sources. Specifically, a diverse array of sensors and actuators is essential for the functionality of autonomous vehicles.

This thesis presents the development a sliding mode controller and vehicle allocation to control a surface vessel platform within a high degree of accuracy. This is part of ongoing development on the WAMV platform at Florida Atlantic University to improve autonomy in marine systems. By developing models for the untested thrusters currently used, the efficacy of a Sliding Mode Controller is evaluated, and a new control allocation developed based on the gradient descent optimization method is developed to manage the thrusters’ constrained angles of thrust generation. The official simulation for the WAMV platform was then modified to include these aspects and the system was tested under wind conditions and was successful in achieving control to waypoints. The gradient descent optimization used for the control allocation did manage to increase the accuracy of both heading and position of the system at convergence. The sliding mode controller navigated to the desired waypoint however maintained oscillations of cross track that were less then 2m and heading error less 20 degrees.

This thesis presents the work done to deliver a robotic system that provides assistance to operators at nuclear waste cleaning facilities. The work done to deliver such system was focused on robotic control and tactile sensing abilities. Haptic feedback mechanism was also added to the system to convey information for the operator. First chapter of the thesis introduces the goals and objectives of this project as well as a detailed literature review on the subsystems used. Second chapter presents previous work done in the area of soft robotics. Such work proved important as the haptic feedback mechanism utilizes a soft robotic armband. Third chapter introduces phase one of the main project. This chapter justifies the use of the selected robots and introduces the concept of adding tactile abilities to the robotic hand used. Chapter four introduces phase two of the project that focused on improving phase one system via a new tactile sensor.