This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learn...
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ISBN:
(纸本)9781846000386
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learning outcomes to give a coherent student experience. Finally, it uses examples to illustrate where the web and other technology can be invaluable tools for the delivery of a holistic curriculcum.
This paper presents the spectral characteristics of a multilayer thin-film dielectric-metal-dielectric reflecting structure of a varifocal membrane mirror for use in an adaptive-optical system for the correction of th...
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This paper presents the spectral characteristics of a multilayer thin-film dielectric-metal-dielectric reflecting structure of a varifocal membrane mirror for use in an adaptive-optical system for the correction of thermal distortions.
This article focuses on discussing the effects of inter-vehicular communication on the performance of platoon control. Different from the existing results established under a critical assumption that the fading channe...
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This paper presents an investigation into the development of open-loop and closed-loop control strategies for flexible manipulator systems. Shaped torque inputs, including Gaussian-shaped and low-pass (Butterworth and...
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This paper presents an investigation into the development of open-loop and closed-loop control strategies for flexible manipulator systems. Shaped torque inputs, including Gaussian-shaped and low-pass (Butterworth and elliptic) filtered input torque functions, are developed and used in an open-loop configuration and their performance studied in comparison to a bang-bang input torque through experimentation on a single-link flexible manipulator system. Closed-loop control strategies that use both collocated (hub angle and hub velocity) and non-collocated (end-point acceleration) feedback are then proposed. A collocated proportional and derivative (PD) control is first developed and its performance studied through experimentation. The collocated control is then extended to incorporate, additionally, non-collocated feedback through a proportional integral derivative (PID) configuration. The performance of the hybrid collocated and non-collocated control strategy thus developed is studied through experimentation. Experimental results verifying the performance of the developed control strategies are presented and discussed.
The optimal control of nonlinear systems has been studied for years by many researchers. However, the application of optimal control problem to nonlinear non-affine systems needs more attention. In this paper we propo...
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The optimal control of nonlinear systems has been studied for years by many researchers. However, the application of optimal control problem to nonlinear non-affine systems needs more attention. In this paper we propose an optimal control design technique for a class of nonlinear and control non-affine equations. The dynamic equations of a flexible shaft supported by a pair of active magnetic bearings (AMBs) are used as the nonlinear control non-affine equations. Mathematical model for the flexible beam is chosen to be the well known Timoshenko beam model, which takes rotary inertia and shear deformations into account, and it is assumed that the shaft is supported by two frictionless bearings at the ends. The effective control of such systems is extremely important for very high angular velocity shafts which are a feature of many modern machines. The control must be able to cope with unbalanced masses and hence be very robust. We shall approach the problem by discretising the Timoshenko beam model and using standard difference formulae to develop a finite-dimensional model of the system. Then we use a recently developed technique for controlling nonlinear systems by reducing the problem to a sequence of linear time-varying (LTV) systems. An optimal control designed for each approximating linear, time-varying system and recent results show that this method will converge uniformly on compact time intervals to the optimal solution.
In this paper, we propose a randomized accelerated method for the minimization of a strongly convex function under linear constraints. The method is of Kaczmarz-type, i.e. it only uses a single linear equation in each...
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Hybrid systems play a crucial role in modeling real-world applications where discrete and continuous dynamics interact, including autonomous vehicles, power systems, and traffic networks. Safety verification for these...
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This article illustrates that research in in-line approach to pH control is comprehensive, but is limited with regard to economical process design. The pH anti-logging approach is one potential solution to the problem...
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This article illustrates that research in in-line approach to pH control is comprehensive, but is limited with regard to economical process design. The pH anti-logging approach is one potential solution to the problem. The method is simple, removes the nonlinearity at source, and contributes to the reduction of over-design of the process.
This article presents the basic principles of operation for model predictive control (MPC), a control methodology that opens a new world of opportunities. MPC is a powerful technique that can fulfill the increased per...
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This article presents the basic principles of operation for model predictive control (MPC), a control methodology that opens a new world of opportunities. MPC is a powerful technique that can fulfill the increased performance and higher efficiency demands of power converters today. The main features of this technique are presented as well as the MPC strategy and basic elements. The two main MPC methods for power converters [continuous-control-set MPC (CCS-MPC) and finite-control-set MPC (FCS-MPC)] are described, and their application to a voltage-source inverter (VSI) is shown to illustrate their capabilities. This article tries to bridge the gap between the powerful but sometimes abstract techniques developed by researchers in the control community and the empirical approach of power electronics practitioners.
Most training algorithms for radial basis function (RBF) neural networks start with a predetermined network structure which is chosen either by using a priori knowledge or based on previous experience. The resulting n...
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Most training algorithms for radial basis function (RBF) neural networks start with a predetermined network structure which is chosen either by using a priori knowledge or based on previous experience. The resulting network is often insufficient or unnecessarily complicated and an appropriate network structure can only be obtained by trial and error. Training algorithms which incorporate structure selection mechanisms are usually based on local search methods and often suffer from a high probability of being trapped at a structural local minima. In the present study, genetic algorithms are proposed to automatically configure RBF networks. The network configuration is formed as a subset selection problem. The task is then to find an optimal subset of n(c) terms from the N-t training data samples. Each network is coded as a variable length string with distinct integers and genetic operators are proposed to evolve a population of individuals. Criteria including single objective and multiobjective functions me proposed to evaluate the fitness of individual networks. Training based on a practical data set is used to demonstrate the performance of the new algorithms.
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