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A fuzzy controller with online learning capability is reported in this paper. The controller learns from a standard proportional plus derivative (PD) controller. It is implicitly assumed that the tuning parameters of the PD controller are already known. The learning is realized via Wang's table lookup scheme. The controllers are applied successfully to control an open-loop unstable system, i.e., the ball and plate system. Experimental studies have demonstrated the performance of the proposed controller. [ABSTRACT FROM AUTHOR]

In this paper, we present an algorithm for the online identification and adaptive control of a class of continuous-time nonlinear systems via dynamic neural networks. The plant considered is an unknown multi-input/multi-output continuous-time higher order nonlinear system. The control scheme includes two parts: a dynamic neural network is employed to perform system identification and a controller based on the proposed dynamic neural network is developed to track a reference trajectory. Stability analysis for the identification and the tracking errors is performed by means of Lyapunov stability criterion. Finally, we illustrate the effectiveness of these methods by computer simulations of the Duffing chaotic system and one-link rigid robot manipulator. The simulation results demonstrate that the model-based dynamic neural network control scheme is appropriate for control of unknown continuous-time nonlinear systems with output disturbance noise. [ABSTRACT FROM AUTHOR]

Examines the problem of optimization of fused fuzzy systems (FFS) via genetic algorithms. Use of rule-table transformation to separate a large fuzzy rule optimization problem; Application of the cart-pole systems; Characteristics of FFS.

Examines the fabrication of the high-performance of metal-semiconductor-metal photodetectors (MSM-PD) with a strained barrier enhancement layer. Information on the formation of the Schottky-barrier contact; Details on how the impulse response of the MSM-PD was obtained; Simplification of the epitaxial structure of the MSM-PD.