This paper presents a sequential identification scheme for continuous nonlinear dynamical systems using neural networks. The nonlinearities of the dynamical systems are assumed to be unknown. The identification model ...
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This paper presents a sequential identification scheme for continuous nonlinear dynamical systems using neural networks. The nonlinearities of the dynamical systems are assumed to be unknown. The identification model is a gaussian radial basis function neural network that grows gradually to span the appropriate state space and of sufficient complexity to provide an approximation to the dynamical system. The sequential identification algorithm for continuous dynamical nonlinear systems is developed in the continuous-time framework instead of in discrete time. The approach, different from the conventional methods of optimizing a cost function, attempts to ensure stability of the overall system while the neural network learns the system dynamics. The stability and convergence of the overall identification scheme are guaranteed by parameter adjustment laws developed using the Lyapunov synthesis approach. To ensure that the modelling error can be reduced arbitrarily, a one-to-one mapping is proposed so that the states and inputs of the system are transferred into compact sets. The operation of the sequential identification scheme is illustrated using simulated experimental results.
A methodology is proposed to control the positioning of an overhead crane and the sway and residual oscillation of the associated payload. The MSC. Visual Nastran (Vn4D) is used to model the system where joints, force...
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ISBN:
(纸本)9812835768
A methodology is proposed to control the positioning of an overhead crane and the sway and residual oscillation of the associated payload. The MSC. Visual Nastran (Vn4D) is used to model the system where joints, forces and physical parameters such as dimensions and material type can be easily assigned. The model is integrated with Matlab-Simulink for analysis and control purposes. Investigations are carried out on mechanisms to attach the hook to the trolley for reduced the vibration in the payload. The simulation results show that good performance in the reduction of vibration and accurate positioning of the payload is achieved with a four ropes attachment mechanism.
This paper presents the design and control of a new style overhead crane. The design approach is based on a modified traditional model of the overhead crane to allow the crane to move in three dimensions. Two overhead...
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ISBN:
(纸本)9812835768
This paper presents the design and control of a new style overhead crane. The design approach is based on a modified traditional model of the overhead crane to allow the crane to move in three dimensions. Two overhead cranes acting in the same work space are designed to show the benefit of the proposed strategy. The modeling is done in the Visual Nastran (vn4d) software environment;and this is integrated with Matlab-Simulink for analysis and control purposes. The simulation results show that the proposed approach is effective with multiple cranes acting in the same work space.
The problem of developing a static and dynamic model of a single flexible manipulator link which is of sufficient accuracy for use in a multi-flexible-link system is considered. Although flexible link modelling has re...
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The problem of developing a static and dynamic model of a single flexible manipulator link which is of sufficient accuracy for use in a multi-flexible-link system is considered. Although flexible link modelling has received much attention in the past, none of the models developed have adequate accuracy for application in a multi-link system. Very high modelling accuracy is necessary because there is significant inter-link coupling in a flexible manipulator and any modelling errors are therefore cumulative. Previous work based on an assumed mode model has made some progress towards improving accuracy by including a correction factor derived from finite element analysis, and the work reported here extends this by including a shear deformation term in the equations. The significant improvements in modelling accuracy thereby achieved are demonstrated by simulations of link motion. Copyright (C) 1996 Elsevier Science Ltd.
The paper generalises approaches to predictive control based on Laguerre and Kautz functions. It is shown that La- guerre and Kautz are special cases of generalised orthonor- mal basis functions and thus one can give ...
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ISBN:
(纸本)9780889868892
The paper generalises approaches to predictive control based on Laguerre and Kautz functions. It is shown that La- guerre and Kautz are special cases of generalised orthonor- mal basis functions and thus one can give a more gen- eral parameterisation using higher order orthonormal ba- sis functions. Specifically, a simple but efficient algorithm that uses generalised functions to parameterise the degrees of freedom in an optimal predictive control is presented. The efficacy of the proposed parameterisation within exist- ing predictive control algorithms that use a similar strategy, is demonstrated by examples.
Predictive control of uncertain nonlinear systems is challenging. Existing approaches often require to find a global minima of a nonconvex optimization problem, and often are conservative, as the worst case solution i...
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Using wavelet transforms, a system that assesses depth of anaesthesia is proposed using auditory evoked potential measurements. The recorded auditory evoked potential signal is analysed by extracting its features whic...
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Using wavelet transforms, a system that assesses depth of anaesthesia is proposed using auditory evoked potential measurements. The recorded auditory evoked potential signal is analysed by extracting its features which are fed to a fuzzy logic rule-base, which in turn decides on the depth of the anaesthetic state. The fuzzy logic rule-base is based on the pharmacological knowledge provided by the anaesthetist. Copyright (C) 1997 Elsevier Science Ltd.
Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. Thi...
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Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. This problem addresses the practical needs of many applications, including industrial automation, crane control, satellite positioning and motion control within a medical stroke rehabilitation context. This paper provides a substantial generalization of this framework by providing a solution to the problem of convergence at intermediate points with simultaneous tracking of subsets of outputs to reference trajectories on subintervals. This formulation enables the NOILC paradigm to tackle tasks which mix "point to point" movements with linear tracking requirements and hence substantially broadens the application domain to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments. A solution to the problem is presented in the framework of NOILC and inherits NOILC s well-defined convergence properties. Design guidelines and supporting experimental results are included.
Root counting and stability criteria involving polynomial roots inside the unit circle are available using the Schur-Cohn-Fujiwara matrix and certain Cauchy index calculations. This note illustrates a close connection...
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Root counting and stability criteria involving polynomial roots inside the unit circle are available using the Schur-Cohn-Fujiwara matrix and certain Cauchy index calculations. This note illustrates a close connection between these criteria, including reduced versions of them.
A general orthogonal parameter estimation algorithm is derived to estimate both the structure and the parameters for a wide range of stochastic nonlinear systems which can be described by a nonlinear rational model. S...
A general orthogonal parameter estimation algorithm is derived to estimate both the structure and the parameters for a wide range of stochastic nonlinear systems which can be described by a nonlinear rational model. Simulation studies are included to demonstrate the performance of the algorithm.
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