People

Back Row (left to right): Cary, Mindy, Spencer, Chris, Professor Alleyne.
Front Row: Pamela, Oyuna, Ashely. (Not pictured: Nate)

 

 

 

 

 

Postdoctoral

Position Open

We are currently looking for someone to join our lab as a Postdoctoral Scholar. Contact us if you are interested!

 

Ph.D. Students

Nathan Weir: Precision Motion Control
My research focuses on the development of precision motion control strategies for inertially stabilized pointing systems. Precision pointing systems are used to aim and stabilize sensitive instrument or sensor payloads for a variety of applications including photography, videography, astronomy, remote sensing, and communications. The jitter requirements for future systems grow more demanding as higher resolution sensors become available. Pointing systems that require a large field of regard and high precision are often limited in performance with conventional bearing technologies. This research seeks to advance the state of the art of precision stabilization systems through the design, analysis, and experimental evaluation of a novel hybrid flexure bearing concept to minimize the effects of nonlinear friction that typically degrade jitter performance in systems with conventional ball bearing joints.

Oyuna Angatkina: Soft Robotics
headshot The inherent ease of manufacturing has made origami structures more popular in robotic systems. However, the increasing complexity of these systems has made them difficult to model and control. Oyuna focuses on the design and control of an autonomous caterpillar crawling robot that can locomote in the 2D plane by using the two origami towers driven by the servomotors. A servomotor can expand and contract the origami towers, allowing the robot body to move forward.

Ashley Armstrong: Dynamic Modeling and Control of a Micro Robotic Deposition System
Dynamic modeling and control of a Micro Robotic Deposition System, with bone scaffold manufacturing as the target application. In this research, precision motion control techniques will be explored to achieve the high levels of precision and response time demanded by microscale applications. Movement coordination between two additive manufacturing extrusion heads will be used to print bone scaffolds with advanced architecture.
Spencer Igram: Additive Manufacturing and Optimization of Superparamagnetic Electronics Components
Profile - Spencer Igram

    Iterative learning control (ILC) is a control strategy utilized when target applications are repetitive in nature – manufacturing and tooling practice are prime examples. Precision motion control of manufacturing systems is a target application of this research. Previous work has focused on the additive manufacturing of ferrite cores for pulsed power applications. This work resulted in reducing the size of inductors and increased power density of electronic systems.

Christopher Aksland: Control and Optimization of Electro-Thermal Power Systems
Improved power management techniques are required to enhance the operating behavior of hybridized and electrified vehicles. However, the complex, multi-domain, and multi-timescale dynamics for this class of systems create challenges for real-time capable control design. Additionally, these vehicles have strict electrical and thermal operating constraints to maintain reliable operation. Chris’ latest work has focused on the application of model predictive control for the multi-timescale coordination of the electro-mechanical dynamics of a hybrid electric UAV powertrain. Simulated and hardware demonstrations of the predictive control designs showed improvements in the overall system performance, reliability, and efficiency in comparison to a well designed baseline controller. Chris’ ongoing work considers the control design and validation for a full aircraft power system.

Cary Laird: Control and Design Optimization of Electro-Thermal Energy Storage Systems
Vehicle power systems commonly experience load profiles with high peak-to-average power levels, necessitating power-dense electrical energy storage systems. Due to the inherent coupling of electrical and thermal domains, these electrical loads generate high peak power thermal loads which are often too burdensome for traditional cooling systems. For these types of loads, hybrid energy storage systems have been utilized, which combine dissimilar energy storage elements into a single system with improved power and energy density. My research focuses on hybrid electro-thermal energy storage systems and the development of control and design strategies thereof in order to improve the power density and high peak power performance of vehicle systems. 
 

M.S. Students

Philip Renkert: Design and Control Optimization of Advanced Electrified Mobility

Phil’s graduate work aims to develop a framework and toolset for simultaneous plant and controller optimization of complex, multi-domain, dynamic systems. Typically, controller design is considered only after electrical, mechanical, and other subsystems have been defined. Excluding control blinds the design process to dynamic subsystem interactions and often prevents the final design from reaching a system-level optimum. An approach referred to as control co-design (CCD) has emerged in response to these limitations, though existing CCD tools are difficult to scale to complex systems and are limited to continuous sizing variables. Phil will develop tools that aid engineers in the search for optimal system topologies early in the design process. Once a CCD optimization framework is developed, the techniques will be applied to the design of a hybrid eVTOL powertrain to demonstrate their practicality.

 

Reid Smith: Modeling and Control Optimization for Hybrid-Electric Vehicles

Hybrid-electric vehicles for high payload, long-range applications introduce new challenges into electro-thermal control due to a dramatic increase in power requirements when compared to short-range electric and hybrid-electric vehicles. As these vehicles utilize turbomachinery, drive motors, cooling cycles, and energy storage systems, the corresponding control optimization presents multi-domain, multi-timescale challenges. Reid’s current work focuses on modeling the electrical and thermal dynamics of each subsystem, while his future work will be to design and validate a control architecture for this hybrid-electric vehicle power management system.


Chris Urbanski: Real-Time Process Monitoring and Control for Additive Manufacturing Systems

Extrusion based additive manufacturing (AM) often lacks any process monitoring with regards to material deposition, relying on position control of the machine to achieve accurate material placement instead. However, accurate machine position does not guarantee accurate material placement due to the material dynamics during extrusion. This can lead to defects in material placement and part geometry, especially when working in the micro/nano scale. My current research is focused on improving material placement during the AM process. Developing process monitoring techniques for the deposition task space utilizes computer vision to construct 3D maps of the deposited material in real-time. This allows material placement errors to be identified and corrected using feedback control during the deposition process.
 

Kayla Russell: Modeling and Control Optimization for Aircraft

With the increase of on-board electronics and avionics implemented on aircraft, the electrical power demand from aircraft drastically increases which results in excess heat generation and a need for more advanced thermal management systems. My current research is to create a control-oriented models of a vapor compression system, a common refrigeration system on aircraft. These models will be used to help improve the existing hierarchical model predictive control framework for aircraft, resulting in safer and more efficient air travel.

 

Frank Andujar Lugo: Distributed Optimization and Control of Thermal Storage Resources for Complex Grid Networks

Improving energy storage is the critical to ensuring a more responsive, resilient and sustainable energy grid.One of the biggest challenges of this future will be the effective management of the distributed storage. My research focuses on how hierarchical model predictive control (MPC) can be used as a tool to coordinate thermal storage systems with the requirements of the individual buildings and the grid they form a part of. My current efforts revolve around creating control friendly models that connect buildings, thermal storage, and the HVAC systems within the building and the broader network. This model will be used to learn about the system performance when controlled through hierarchical MPC.

 

Kurtis Kuipers: Control of Large-Scale Additive Manufacturing 

Since the introduction of large-scale additive manufacturing with concrete based materials, there has been a need to develop robust control systems that manage the modern manufacturing method. Due to remote locations and inconsistent printing conditions, manual intervention is often required during the printing process. My research will be focusing on improving accuracy, defect mitigation, and increasing the automation capabilities of large-scale concrete additive manufacturing.

 

 

Dylan Charter: Unmanned Aircraft Systems

From use cases such as aerial photography,  archaeological surveying, and commercial delivery, unmanned aircraft systems (UAS’s) have become increasingly popular in both the home and commercial market. Common designs vary including the multirotor, traditional fixed-wing, and fixed-wing vertical take-off and landing (VTOL) aircraft. My research area focuses on the optimization of both the physical design as well as the control systems of a UAS.