Some new structural properties of the classical SF/SFO schemes are analyzed by TFR equivalent forms of LTI systems. The location of poles and zeros of the closed-loop system can only be partly designed by SFO. A two-s...
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Some new structural properties of the classical SF/SFO schemes are analyzed by TFR equivalent forms of LTI systems. The location of poles and zeros of the closed-loop system can only be partly designed by SFO. A two-step procedure is suggested to reach full zero/pole placement for SISO systems applying a TDOF scheme.
A diagnostic expert system established on model-based reasoning for on-line diagnosis and loss prevention is described in the paper. Its diagnostic "cause-effect" rules and possible actions (suggestions) are...
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Infrared (IR) and visible images are commonly used in the detection and tracking of a moving target. A novel contour extraction scheme for a moving vehicle is proposed in this paper. Firstly, a motion segmentation tec...
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This paper is concerned with the adaptive sliding-mode control of a class of nonlinear systems in nonlinear parametric-pure-feedback form with mismatched uncertainties. Backstepping design procedure is applied, which ...
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In this work the normality property of specification languages for discrete-event systems under partial observation is investigated in a modular context for large-scale systems-modelling. This is related to work on co...
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In this paper an active suspension system which guarantees passenger comfort in normal cruising and rollover prevention in emergencies is proposed. In the control design the changes in forward velocity, the normalised...
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As a prerequisite for precise trajectory tracking of a two-wheeled mobile robot, accurate control of the velocity and the curvature along a predefined trajectory is vital. After offline training, a neural network is u...
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As a prerequisite for precise trajectory tracking of a two-wheeled mobile robot, accurate control of the velocity and the curvature along a predefined trajectory is vital. After offline training, a neural network is used for nonlinear predictive control. To make the system more robust against modeling inaccuracies and other disturbance influences, the control error is integrated and used to adjust the control variables calculated by the predictor.
The paper examines the conditions for isolating the unknown input detection from the effects of the measurements noise in the important family of positional control problems. The study is motivated by the need of impr...
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A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation ...
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The shortcoming of the standard genetic algorithm is analysed. an improved genetic algorithm with modified mutation operator and adaptive probabilities of crossover and mutation is proposed. Simulation experiments hav...
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