The motion of a multi-body autonomous robot as well as of a train-like multi-articulated transportation vehicle is characterized by the deviation of the path of each intermediate vehicle from that of the leading one (...
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The motion of a multi-body autonomous robot as well as of a train-like multi-articulated transportation vehicle is characterized by the deviation of the path of each intermediate vehicle from that of the leading one (off-tracking). In this paper, we make use of an innovative junction technique, which allows the kingpin to slide along the axis of the leading vehicle, something that proved to be very effective in reducing off-tracking. We propose two controllers for the elimination of the off-tracking phenomenon, in both robotic and transportation multi-articulated vehicles; the one is heuristically derived while the other one is based on steady-state off-tracking when an n-trailer vehicle moves on a circular trajectory. Simulation results for various cases, without and with the sliding kingpin system, showed that significant off-tracking reduction or even elimination can be achieved.
This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse r...
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A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a f...
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Recent years has seen much progress in the theory and application of iterative learning control schemes for both linear and (classes of) nonlinear dynamics. In the case of the former, many algorithms based on minimizi...
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This paper addresses the problem of implementing predictive controllers for supervisory level control systems. In this configuration the manipulated variables calculated by the Predictive controller are used as comman...
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Electro Speckle Pattern Interferometry (ESPI) and Shearography for quantitative analysis of a crack inside of pipelines are described. Shearography is used widely for non-destructive inspection because of high sensiti...
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ISBN:
(纸本)7560317685
Electro Speckle Pattern Interferometry (ESPI) and Shearography for quantitative analysis of a crack inside of pipelines are described. Shearography is used widely for non-destructive inspection because of high sensitivity and simple interferometer. However, it is difficult to determine the defect size quantitatively because there are so many effect factors- shearing distance, shearing direction, induced load, and crack dept., which is depend on operator's skill. In this paper, a crack inside of pipeline is inspected with Shearography and ESPI. Firstly, the condition of these factors in Shearography is optimized for quantitative analysis and the size of crack is determined. And also, ESPI is used for determination of crack size quantitatively also. This method is independent on information of a crack and only induced load play an important role. The deformation is measured three-dimensionally and differentiated for finding of strain concentration points, which is equal to result of Shearography so that crack size can be determined quantitatively without any information of crack.
A learning feedforward controller (LFFC) using the Bartlet window function is proposed for a better tracking control of linear system over a finite time interval. LFFC is applied as a feedforward controller to the exi...
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A learning feedforward controller (LFFC) using the Bartlet window function is proposed for a better tracking control of linear system over a finite time interval. LFFC is applied as a feedforward controller to the existing feedback controller. This paper demonstrates that using a simple window function-Bartlet (Fejer or triangular) window in signal processing, the design of a learning feedforward controller reduces to determining only two design parameters: the learning gain and the number of point in the window. Convergence analysis is presented together with a design procedure.
This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse r...
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This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse response (FIR) filters. The IIR filters use continuous time state variable filters, and discretisation is performed on the filtered derivatives. In contrast, the FIR filters are in a discrete form with carefully chosen coefficients to approximate the derivatives of the continuous time variables. The strength and weakness of each approach are discussed and demonstrated by a set of simulation examples.
Automatic acquisition of an object using model appearance from an environment is proposed in this paper. Robots directly interact with a defined environment in order to extract object shape from its scene. The robot e...
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ISBN:
(纸本)4907764197
Automatic acquisition of an object using model appearance from an environment is proposed in this paper. Robots directly interact with a defined environment in order to extract object shape from its scene. The robot extracts the targeted object's appearance, creating an eigenspace, and stores it into the memory server (or intelligent data carrier). Eigenspace is constructed every time a new object appears, and various appearances are accumulated gradually. A closed sequence of appearances is generated from the accumulated shapes, which is used for object recognition. Experimental results of object accumulation and recognition show the effectiveness of the proposed method.
Differential linear repetitive processes are a distinct class of 2D continuous-discrete linear systems of both applications and systems theoretic interest. In the latter area, they arise, for example, in the analysis ...
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Differential linear repetitive processes are a distinct class of 2D continuous-discrete linear systems of both applications and systems theoretic interest. In the latter area, they arise, for example, in the analysis of both iterative learning control schemes and iterative algorithms for computing the solutions of nonlinear dynamic optimal control algorithms based on the maximum principle. Repetitive processes cannot be analysed/controlled by direct application of existing systems theory and to date there are few results on the specification and design of control schemes for them. The paper uses an LMI setting to develop the first really significant results in this problem domain.
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