An Adaptive Neural Network Quadrotor Trajectory Tracking Controller Tolerant to Propeller Damage

Executing quadrotor trajectories accurately and therefore safely is a challenging task. State-of-the-art adaptive controllers achieve impressive trajectory tracking results with slight performance degradation in varying winds or payloads, but at the cost of computational...

A proof-of-concept on Adaptive Control for High-Speed Atomic Force Microscopy

High-Speed Atomic Force Microscopy is widely used for investigating biological architectures and the semiconductor industry. The main limitation comes from parachuting or the Wile E. Coyote effect. Parachuting is the phenomenon where the cantilever taps on the sample towards a steep decrease in height, but does not get adjusted for this decrease...

A Bio-inspired Sensing Approach to in-Gust Flight of Flapping Wing MAVs

Flapping wing micro aerial vehicles (FWMAVs) are known for their flight agility and maneuverability. However, their in-gust flight performance and stability is still inferior to their biological counterparts. To this end, a simplified in-gust dynamic model, which could capture the main gust effects on FWMAVs, has been identified with real in...

Adaptive Fuzzy Logic Control Applied to Socially Assistive Drones: A Case Study

With the number of diagnosed cases rising every year, Autism Spectrum Disorder (ASD) is in need of novel therapeutic approaches to counteract the social and motor impairments inflicted by it. In this research, one of such therapeutic approaches, movement therapy (in particular Dance Movement Therapy (DMT)), is combined with the concept of...

Cooperative Robot Manipulators for Parcel picking and placing

In this thesis, a control scheme for lifting parcels using two robot manipulators is presented. The robots do not have a rigid grasp on the object. Instead, they use friction to lift the parcels. First, a controller calculates the desired force to make sure the parcels do not slip. The required force, as well as a trajectory are then sent to a...

Online Reinforcement Learning for Flight Control: An Adaptive Critic Design without prior model knowledge

Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this research an Adaptive Critic Design (ACD) based on Dual Heuristic Dynamic Programming (DHP) is developed and implemented on a simulated Cessna Citation 550 aircraft. Using an online identified system model approximation, the method is independent...

Robust and Adaptive Nonlinear Attitude Control of a Spacacraft: A Comparison of Backstepping-based Designs

In the context of the initiative Formation for Atmospheric Science and Technology demonstration (FAST), this dissertation describes the design and comparison of several nonlinear attitude controllers for TU Delft’s micro-satellite. The control requirements include robustness against model uncertainties and disturbances. To this end, Backstepping...