Teaching Interests Dr. Carroll helped found and has advised Clarkson's FIRST Robotics Student Projects for Engineering Experience and Design (SPEED) team, Number 229: Division by Zero, since its inception in 1998. He has instructed the Robotics Module of the Horizons Program administered by Clarkson's Institutional Diversity Initiatives and Pipeline Programs for two weeks during each summer since 2000. He was the PI on a 1994 National Science Foundation Course, Curriculum, and Laboratory Improvement (CCLI) grant funded for three years at $96,402 entitled "An Integrated Modular Design Laboratory for Electrical Engineers," that utilized Matlab/Simulink and Digital Signal Processing (DSP) technology to enhance the senior Electrical Engineering design experience. He is a Co-PI of the Clarkson Inventor's Institute, initially funded by a three year NCIIA grant in 2001, to promote and support innovative ideas and help spark job growth/creation in the North Country by allowing Clarkson University students to take on engineering design projects proposed by local residents, businesses, or community groups. He is currently a Co-PI on a 2003 National Science Foundation Course, Curriculum, and Laboratory Improvement (CCLI) grant (DUE-0311075) funded for three years at $133,602 entitled "Hands-on Learning in Engineering, " designed to create a common Freshman year engineering laboratory experience within Clarkson's Wallace H. Coulter School of Engineering. He is also the PI of a 2005 P&G Fund curriculum development grant funded for three years at $150,000 entitled "Multidisciplinary Projects Course in Virtual Product Development," which involve the use of Virtual Reality technology to experience products and packaging as a means of test marketing without having to produce actual prototypes and concurrent to the overall engineering design process.

"Dr. Carroll is associated with the Mechatronic Systems Laboratory which conducts research in areas such as adaptive signal processing, nonlinear system identification, active noise control, RBF neural networks, real-time computing software and hardware systems, advanced modeling and control techniques, computer vision and image processing, system virtualization/prototyping and virtual environments, high-performance motion control and robotics that combines state-of-the-art computer hardware and software with recent advances in control theory and signal processing. In addition, he founded the Advanced Visualization Laboratory in summer 2002 which conducts research in visualization, immersive virtual reality/virtual environments, and information fusion conducted with a core theme of enhancing human-computer interaction and enabling information technology as an assistive partner in human activities. Research conducted in this laboratory currently targets two broad areas: rehabilitation engineering and homeland security. Research and Development projects worked on include several contracts with GE Global Research and Development for work in ultrasonic NDE of plastics; ONR contract work in modeling and control of shipboard power systems; AFOSR contract work to develop an active dynamometer for testing electric actuators; ARO contract work to develop an auxiliary ground power unit for starting helicopters; subcontract from US ARMY-TACOM for capturing human motion in virtual environments. All of these projects involved some form of instrumentation and signal processing, data acquisition and control, computer modeling and simulation, visualization and/or system prototyping. Current research interests include the following: Study of advanced control techniques used to compensate for the detrimental effects of electrical actuator dynamics on the high-performance control of electromechanical and electrohydrolic system.Typical applications include direct-drive robotics, rolling mills, flying shears, and industrial processes, such as plastic injection molding. Model-based nonlinear control techniques such as feedback linearization, singular perturbation, and integrator backstepping, are applied to these systems. Control algorithms requiring either full-state feedback or partial state feedback are applied to these systems. Control algorithms are also developed for systems given exact model knowledge and modeling uncertainty (e.g. adaptive, robust, neural-network, fuzzy controllers. In addition, I study basic electric and electro hydraulic motors. Controllers which ensure accurate position, velocity, and torque trajectory tracking are examined from both a theoretical and experimental perspective. The controllers are simulated using digital computers and implemented on actual machines in the motion control laboratory. Other areas of study include the development of improved motor models using system identification techniques, such as neural networks. This research has obvious relevance to many motor control applications, and indirectly benefits many others, such as the control of electric vehicles."