William Gressick

Multi-Probe Micro-Assembly

This paper describes the algorithm development and experimental results of a multi-probe micro-assembly system. The experimental testbed consists of two actuated probes, an actuated die stage, and vision feedback. The kinematics relationships for the probes, die stage, and part manipulation are derived and used for calibration and kinematics-based planning and control. Particular attention has been focused on the effect of adhesion forces in probe-part and part-stage contacts in order to achieve grasp stability and robust part manipulation. By combining pre-planned manipulation sequences and vision based manipulation, repeatable spatial (in contrast to planar) manipulation and insertion of a sub-millimeter part has been demonstrated. The insertion process only requires the operator to identify two features to initialize the calibration, and the remaining tasks involving part pick-up, manipulation, and insertion are all performed autonomously.

Active Enhancement of Wind Turbine Blades Performance

The feasibility of using synthetic jet actuators to enhance the performance of wind turbine blades was explored in wind tunnel experiments. Using this technique, the global flow field over the blade was altered such that flow separation was mitigated. This, in turn, resulted in a significant decrease in the vibration of the blade. Global flow measurements were conducted, where the moments and forces on the blade were measured using a six component wall-mounted load cell. The effect of the actuation was also examined on the surface static pressure at two spanwise locations; near the blade’s root and near the tip. In addition, Particle Image Velocimetry (PIV) technique was used to quantify the flow field over the blade. Using synthetic jets, the flow over the blade was either fully or partially reattached, depending on the angle of attack and the Reynolds number. Furthermore, the changes induced on the moments and forces, as well as on the blades vibrations were found to be proportionally controlled by either changing the momentum coefficient, the number of synthetic jets used, or by the driving waveform. Finally, a proof-of-concept closed-loop control system was developed to test the ability of using synthetic jet actuators to restore and maintain flow attachment and reduce the vibrations in the blade during dynamic pitch. The synthetic jets were switched on when the root strain vibration spectrum exceeds a predetermined threshold at a given frequency. While the control system implementation used is simplistic, it demonstrated the ability of synthetic jet actuators to reduce blade’s vibrations (by restoring and maintaining attached flow) during the dynamic motion, analogous to the wind gusts seen in wind turbine operation.

Active Yaw Control of a Ducted Fan-Based MAV using Synthetic Jets

The feasibility of using active flow control to stabilize a micro ducted fan unmanned aerial vehicle in a yaw motion was investigated experimentally. Flow control was implemented using synthetic jet actuators to manipulate the flow around the vehicles stator vanes. As a result, this mechanically simplified control approach can be used to generate a yaw moment on the vehicle instead of moving control surfaces and articulated rotor blades. The rotational control of the MAV (165.5mm in diameter and 177.8mm in height) was obtained by activating surface-mounted synthetic jets that were mounted on a set of four fixed stators downstream of the duct. The synthetic jets were located downstream of a deliberately formed local separation to enable controlled flow reattachment. The flow field around the stators and in the wake was studied using particle image velocimetry (PIV) where the geometrical angle of attack of the stators was either 0° or 6° and the propeller rotational speed was either 4,200RPM or 9,000RPM (g...

Low-order nonlinear models for active flow control of a low L/D inlet duct

This paper investigates the methodology to develop low-order nonlinear state space models for flow response along the centerline of a very aggressive (length to exit diameter ratio, L/D, of 1.5) inlet duct. Reduced order models are constructed by using Numerical Algorithms for State Space Subspace System Identification (N4SID), based on 2D numerical flow simulation data. The identified models successfully predict the spatially-averaged pressure recovery along the centerline at the Aerodynamic Interface Plane (AIP) for different levels of actuation of the control jets. Based on the identified models, estimator design and sensor placement are performed.

Investigation of a Low L/D Inlet Duct: Modeling, Estimator Design and Sensor Placement

In this paper , we investigate a very aggressive (length to exit diameter ratio, L/D, of 1.5) inlet duct. We identify a low-order nonlinear model by using Numerical Algorithms for State Space Subspace System Identification (N4SID), based on 2D numerical flow simulation data, at an inlet Mach number of 0.43. The identified model successfully predicts the spatially-averaged pressure recovery along the centerline at the Aerodynamic Interface Plane (AIP) for di erent levels of actuation of the control jets. Based on the model, we design a dynamic estimator to estimate the AIP pressure recovery from given input profile and wall pressure sensor measurements. We use the dynamic estimator for optimal sensor placement, and compare the results with those obtained through a static estimator. Our next step is to apply the reduced-order model and estimator to the AIP pressure recovery control.

Model-based control of a high-temperature crystal growth process

This paper describes a modeling and control approach for the thermal aspects of a high-temperature semiconductor crystal growth process. From a thermal perspective, each crystal growth cycle is composed of three distinct phases, heat up, growth, and cool down, each with specific control challenges and objectives. This paper focuses on the heat up and growth phases. A simulation model is first developed based on the induction furnace geometry and known material properties. This model is calibrated using the experimental process data by minimizing the weighted error between the predicted and actual temperature measurements. The two critical temperatures for the process are the temperature of the source material and the temperature of the crystal seed. For the heat up phase, the input profile is generated to rapidly ramp up the source and crystal temperature while avoiding damaging temperature spikes. In the crystal growth phase, the objective is to maintain the source temperature above sublimation while keeping the crystal temperature sufficiently low to allow condensation. These temperatures cannot be directly measured. Instead, an observer-based controller achieves the temperature control objective. Simulation results with FEM-in-the-loop validation are presented.