A State Observer Based Methodology for Improving Control Schemes Employing Multiple Exogenous Feedforward Signals

Feedback control provides the basis of many different control schemes. However, even high gain feedback may be insufficient for processes requiring high precision or non-causal behavior such as micro additive manufacturing or metrology. Exogenous feedforward inputs can be sometimes be used to provide a solution in these circumstances. These signals are carefully trained such that they produce the desired response in their target system. However, the efficacy of these signals can be greatly diminished when the systems they are applied to have different initial conditions from the ones for which the signals were designed. This problem is magnified when multiple feedforward inputs are applied sequentially. The subtype of Iterative Learning Control, Basis Task Iterative Learning Control (BTILC) involves creation of multiple exogenous feedforward signals which correspond to various learned behaviors. These signals are then applied sequentially in order to produce more complex system outputs without explicitly applying the learning algorithm to those outputs. This makes it a prime example of a control scheme which suffers from the decreased signal efficacy discussed previously. This manuscript first generates a novel algorithmic solution to these issues leveraging state information observed in the feedforward signal training process; called an Informed State Correction (ISC). Then, it presents experimental results which demonstrate a performance increase of approximately 70% in BTILC control schemes implementing an ISC. These results represent a significant increase in the efficacy of BTILC and its applicability to real-world control scenarios. Furthermore, the ISC has been posed such that it can be applied to any control scheme employing multiple exogenous feedforward signals, where it may provide similar performance benefits.Dr. David HoelzleThe College of EngineeringNo embargoAcademic Major: Mechanical Engineerin

Modeling and H-Infinity Loop Shaping Control of a Vertical Takeoff and Landing Drone

abstract: VTOL drones were designed and built at the beginning of the 20th century for military applications due to easy take-off and landing operations. Many companies like Lockheed, Convair, NASA and Bell Labs built their own aircrafts but only a few from them came in to the market. Usually, flight automation starts from first principles modeling which helps in the controller design and dynamic analysis of the system. In this project, a VTOL drone with a shape similar to a Convair XFY-1 is studied and the primary focus is stabilizing and controlling the flight path of the drone in its hover and horizontal flying modes. The model of the plane is obtained using first principles modeling and controllers are designed to stabilize the yaw, pitch and roll rotational motions. The plane is modeled for its yaw, pitch and roll rotational motions. Subsequently, the rotational dynamics of the system are linearized about the hover flying mode, hover to horizontal flying mode, horizontal flying mode, horizontal to hover flying mode for ease of implementation of linear control design techniques. The controllers are designed based on an H∞ loop shaping procedure and the results are verified on the actual nonlinear model for the stability of the closed loop system about hover flying, hover to horizontal transition flying, horizontal flying, horizontal to hover transition flying. An experiment is conducted to study the dynamics of the motor by recording the PWM input to the electronic speed controller as input and the rotational speed of the motor as output. A theoretical study is also done to study the thrust generated by the propellers for lift, slipstream velocity analysis, torques acting on the system for various thrust profiles.Dissertation/ThesisMasters Thesis Electrical Engineering 201