Gary Balas
Distinguished McKnight University Professor and Department Head

Current Research Projects

Development of Analysis Tools for Certification of Flight Control Laws

Analysis techniques currently being used for current military aircraft, e.g. F/A-22 and JSF aircraft, are well suited to certify flight control systems. These techniques though are complex, time consuming and require many well trained control and simulation engineers to accomplish. A high percentage of the future UAVs will be autonomous, capable of highly aggressive maneuvers using nonlinear, adaptive, reconfigurable flight control systems.  Certification of these control algorithms will be even more of a challenge than current military aircraft and will require advances in nonlinear analysis specifically tailored for the flight clearance problem. In addition, the rapid evolution of uninhabited aerial vehicles (UAVs) will require certification of the flight control law be performed with fewer resources.
The research program focuses on nonlinear robustness analysis for flight control certification. The techniques to be applied include structured singular value and worst-case analysis methods, guided Monte Carlo and worst-case simulation, Integral Quadratic Constraints (IQCs), hybrid system analysis, sum-of-squares (SOS) methods combined with nonlinear numerical optimization. The goal is to develop a flexible, comprehensive nonlinear robustness analysis package oriented towards flight control law certification. These tools will be made available to the aerospace community, practitioners and researchers alike.

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Control of Supercavitating Vehicles

An object traveling at very high speeds generates cavitation bubbles on the corner of sharp contours due to pressure gradients that result in flow separation. This is often the case if a propeller spins fast enough, the surrounding liquid is vaporized due to the decrease in pressure generating cavitation bubbles. As pressure surrounding the liquid decreases, the bubbles collapse. Even if the body is stable inside the cavity, the vehicle may not be stable when in contact with the cavity. Nonlinear interaction of the control surfaces and the body with the cavity wall is very important when calculating the fin and planing forces acting on the vehicle. The cavity wall exerts a large restoring force over the short period of time. The nature of this instability forces the vehicle back into the cavity, often resulting in limit cycle behavior. Cavity-vehicle interaction also exhibits strong memory effects and cavity shape is a function of the history of the vehicle motion. Suppression of limit cycles oscillations and disturbance attenuation require high bandwidth actuators and high sample rate real-time control algorithms.

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Past Research

DARPA Software Enabled Control

The Software-Enabled Control (SEC) program sponsored by the Defense Advanced Research Projects Agency (DARPA) of the United States represents the first large-scale, targeted effort toward integration of advances in computing and control of autonomous, uninhabited air vehicles (UAVs). The SEC vision was to enable advanced control systems that exploit information to significantly increases in the performance and reliability of these vehicles. As part of the SEC program, the University of Minnesota (UMN) | University of California, Berkeley (UCB) team developed a unified design framework to synthesize and simulate individual vehicle management systems.
On-line control customization for Uninhabited Air Vehicles (UAVs) was the focus of our efforts during the five year program. Advances in on-line control customization have enabled a dramatic increase in military effectiveness by increasing the level of autonomy in UAVs, probability of mission success and survivability, expanding the range of UAV missions while reducing air vehicle fatigue and life cycle costs. The benefits to the military include use of extremely aggressive maneuvering of UAVs to achieve mission directives, accommodation of goal changes in real-time, life-extending control, a reduced need for hardware redundancy while allowing more complex control strategies without increased software production and verification costs. A key component of our research was the integration of our algorithms into the Open Control Platform (OCP) software infrastructure. During the five year program advances were made in the areas of modeling, receding horizon control (RHC), linear parameter-varying (LPV) control, fault detection, reconfiguration, anytime control algorithms and real-time control interfaces and algorithms.

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