The conditions for a polynomial response and obtaining its analytical expression are considered. The responses in a forced regime of work arise from a linear input/output system of second order with varying coefficien...
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Genetic programming has rarely been applied to manufacturing optimisation problems. In this report we investigate the potential use of genetic programming for the solution of the one-machine total tardiness problem. C...
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In this paper a new observation model is presented to improve the state estimation and prediction in a target tracking problem. Comparing with conventional approaches, the following are distinguished points of the app...
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In this paper a new observation model is presented to improve the state estimation and prediction in a target tracking problem. Comparing with conventional approaches, the following are distinguished points of the approach. First, the measurement equation is set up in the polar coordinate and even combines the derivation measurement with the usual position measurements (i.e. there are 6 sensor data now: range, azimuth, elevation angle, range rate, azimuth rate, and elevation rate). Second, the observation noise of sensor data is considered as a colored one and be set up as the model of AR(1), and by means of a pseudo measurement model, the requirement of Kalman filter will be satisfied. As a result, the accuracy of both the observation and the prediction will be increased.
Concepts of the generalized left inverse, the generalized Fourier transform and the square root of matrix are defined in this the paper. Meanwhile, this paper deals with singular distributed parameter systems describe...
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Concepts of the generalized left inverse, the generalized Fourier transform and the square root of matrix are defined in this the paper. Meanwhile, this paper deals with singular distributed parameter systems described by coupled partial differential equations with singular matrix coefficients. As to the singular distributed parameter systems, the initial-value problem are considered on the basis of the generalized Fourier tranform theorem. The solution of the systems is obtained the method presented here the possibility of determining acceptable initial-value conditions.
The underactuated free floating robot in space is nonlinear systems where velocity and acceleration constraints are both nonintegrable, therefore it is a secondorder nonholonomic system. Some of the existing nonholono...
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The underactuated free floating robot in space is nonlinear systems where velocity and acceleration constraints are both nonintegrable, therefore it is a secondorder nonholonomic system. Some of the existing nonholonomic control methods will not be directly applicable to such systems as it is extremely difficult, if not impossible, to find the control Lie brackets. In this paper, by investigating the system dynamics in dept., a simple velocity-based method is proposed to control the unactuated joints and a multi-step composite strategy to implement orientation tracking tasks. The proposed algorithm is of significance in controlling of space robots when some joints fail to function, or they are intentionally set to be passive for energy efficiency and safety purposes.
control of a gas-turbine engine requires management of continuous and discrete (state-event) behaviour. A design environment- the Development Framework, is used to define both the continuous and discrete aspects of a ...
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control of a gas-turbine engine requires management of continuous and discrete (state-event) behaviour. A design environment- the Development Framework, is used to define both the continuous and discrete aspects of a turbine engine controller. The approach uses purpose-built software translation tools to capture the system's specification from commercial simulation tools. A unified design model based on a data flow notation, comprising both continuous and state-event behaviour is automatically generated. Specification and design models of selected gas-turbine engine controller subsystems are presented. The complexity of the application suggests that the approach can be used for industrial scale projects.
Pseudo-linear neural networks (PNN) based modeling and control strategy for a class of nonlinear dynamic systems is proposed. The training of the PNN is implemented by using a recursive prediction error (RPE) algorith...
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Pseudo-linear neural networks (PNN) based modeling and control strategy for a class of nonlinear dynamic systems is proposed. The training of the PNN is implemented by using a recursive prediction error (RPE) algorithm. The control strategy is based on one-step-ahead prediction, in which a direct controller design for an affine nonlinear system and the second order based optimization for a general nonlinear system are adopted. The stability of the closed loop control system is investigated, and some sufficient conditions for the local asymptotic stability are derived. The some simulated examples showed the good results of proposed control strategies in this paper.
The intelligent multisensor state information fusion based on a new stochastic, fuzzy, neural network is investigated. This network carries out the parameter and structure learning to obtain the optimal fuzzy membersh...
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The intelligent multisensor state information fusion based on a new stochastic, fuzzy, neural network is investigated. This network carries out the parameter and structure learning to obtain the optimal fuzzy membership functions and the optimal number of fuzzy rules of stochastic dynamic systems. The state information fusion with radar and infrared sensors based on the network is simulated in an uncertain environment. The numerical results show that the proposed intelligent method is effective and superior to fuzzy neural network based method
Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This me...
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Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This method has clear physical meaning, and by using the weighted least-squares estimation algorithm, the statistical parameters can be identified accurately and robustly. A sufficient condition for the identifiability of model mismatches with arbitrary phase characters in adaptive Kalman filtering is also given, by using the structure of innovations sequence and the theory of higher-order statistics.
In this paper, an adaptive decentralized controller is presented to attenuate the transversal vibration of a flexible cablestayed bridge induced by seismic excitation, in which only local sensor information has been u...
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