The Joint Forces Air Component Commander (JFACC) in military air operations controls the allocation of resources (wings, squadrons, air defense systems, AWACS) to different geographical locations in the theater of operations. The JFACC mission is to define a sequence of tasks for the aerospace systems at each location, and providing feedback control for the execution of these tasks in the presence of uncertainties and a hostile enemy. Honeywell Labs has been developing an innovative method for control of military air operations. The novel model predictive control (MPC) method extends the models and optimization algorithms utilized in traditional model predictive control systems. The enhancements include a tasking controller and, in a joint effort with USC, a probabilistic threat/survival map indicating high threat regions for aircraft and suggesting optimal routes to avoid these regions.
A simulation/modeling environment using object-oriented methodologies has been developed to serve as an aide to demonstrate the value of MPC and facilitate its development. The simulation/modeling environment is based on an open architecture that enables the integration, evaluation, and implementation of different control approaches. The simulation offers a graphical user interface displaying the battlefield, the control performance, and a probability map displaying high threat regions. This paper describes the features of the different control approaches and their integration into the simulation environment.