he paper presents a neural net-based scheme embodying linear prediction techniques and the SVD algorithm to estiimate the parameters of exponetially damped sinusoids satisfactorly under low SNR conditions. In the method ...

This paper deseribes the control of multi-arm co-operating manipulator systems handling a common object. Inverse dynamics controllers with motive force compensation are developed for the co-operating fixed-base, free-floating, ...

In this paper a novel hybrid evolutionary algorithm (HEA) method is used to find optimal feedback gains for inverse dynamics controllers. It is shown that HEA efficiently finds the optimal feedback gains to improve the ...

This paper describes the techniques of computer control of rotary cement kiln through fuzzy logic, The automatic kiln control strategy is based on the priority management of different kiln control objectives and sub-objectives. ...

This paper describes the design and tuning of a fuzzy logic controller(FLC) for controlling the level of water on real time basis, in a laboratory scale pilot plant using genetic algorithm(GA). Selection of appropriate ...

This paper describes the kinetics and dynamics of multiple robotic arms mounted on a mobile base and co-operatively handling a common object. The presence of closed kinematic chains along with a mobile base of comparable ...

This paper proposes an alternative method for extraction of narrow band signal contaminated with varying white noise power. A three layred feedforward network with one hidden layer is suggested in this paper. The internal ...

Neural networks are analogous to biological systems, and intelligent control systems are but an attempt to emulate the logical powers of the human mind. Articles in this series are intended to demystify the various intricacies ...

This paper presents an estimation technique for amplitude, frequency, phase and damping of a signal embedded in noise. This signal considered in this paper belongs to that of a power system, where frequency deviations in ...

Recent research on self-adaptive evolutionary programming (EP) methods evidenced the problem of premature convergence. Self-adaptive evolutionary programming methods converge prematurely because their object variables ...