Adaptive optimal control: The thinking man's GPC : R. R. Bitmead, M. Gevers and V. Wertz

Stability of adaptive systems: Passivity and averaging analysis: B. D. O. Anderson, R. R. Bitmead, C. R. Johnson, Jr, P. V. Kokotovic, R. L. Kosut, I. M. Y. Mareels, L. Praly and B. D. Riedle

Vehicle Stabilization via a Self-Tuning Optimal Controller

Nowadays, using advanced vehicle control and safety systems in vehicles is growing rapidly. In this regard, in recent years new control systems, called VDC, have been introduced. These systems stabilize vehicle yaw motion, by yaw moment resulted from tire controlling forces. In this paper, an adaptive optimal controller applied to a vehicle to obtain a satisfactory lateral and yaw stability. To...

Friction Compensation for Dynamic and Static Models Using Nonlinear Adaptive Optimal Technique

Friction is a nonlinear phenomenon which has destructive effects on performance of control systems. To obviate these effects, friction compensation is an effectual solution. In this paper, an adaptive technique is proposed in order to eliminate limit cycles as one of the undesired behaviors due to presence of friction in control systems which happen frequently. The proposed approach works for n...

Adaptive Decision Fusion in Detection Networks

In a detection&#10 network, the final decision is made by fusing the decisions from local detectors. The objective of that decision is to minimize the final error probability. To implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. H...

Adaptive Decision Fusion in Detection Networks

In a detection network, the final decision is made by fusing the decisions from local detectors. The objective of that decision is to minimize the final error probability. To implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. How...