Increasing levels of automation and rising costs of manpower are pushing the DoD towards a supervisory control paradigm for future unmanned aerial vehicle (UAV) missions. Using the Supervisory Control Operations User Testbed, a group of 20 participants completed two twenty minute supervisory control missions where eye tracking and performance data were collected. Each mission had 3 levels of ta...

Ab.macl The dimension of tbe guard lOne along with its bounds for the Generalised Learning Algorithm (P"thak and Pal. 1986) is determined 1'01' optimum learning. The dimension is found to be dynamic dependlllg on the input sequence and tbe current estimates of classification parameters. Incorporation of tbis higher-order knowledge in a supervisory program improves the system performance. The pe...

Objective: We develop a method for enabling human-like, flexible supervisory control via delegation to automation. Background: Real time supervisory relationships with automation are rarely as

In this paper, a novel scheme of incorporating a learning mechanism into previous step supervisory controllers for adaptive fuzzy control is proposed to relax bounds required in the control process. In traditional supervisory adaptive fuzzy control approaches, the use of fuzzy estimators for approximating system functions and a robust supervisory control law are necessary to deal with any possi...

Hybrid dynamic systems are of major research interest nowadays due to their use as models in many applications in computer science and systems control. One of the major problems in hybrid dynamic systems is establishing their key property of stability, which also is important in controller design. The use of communication networks in supervisory control of distributed control systems introduces...

Much research has been addressed to nonblocking supervisory control of Discrete-Event Systems (DES) such as Flexible Manufacturing Systems (FMS), and a variety of approaches have been developed. One especially powerful approach, due to Chuan Ma, is based on DES representation by means of State Tree Structures (STS). Using STS, this chapter develops nonblocking supervisory control of a well-know...