作者：
PARASKEVOPOULOS, PNSchool of Engineering
Automatic Control Systems Laboratory Department of Electrical Engineering Democritus University of Thrace Xanthi Greece
The paper describes a simple frequency-domain method for the eigenvalue assignment of linear time-invariant multivariable 2-dimensional systems by means of state and output feedback. Necessary and sufficient condition...
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The paper describes a simple frequency-domain method for the eigenvalue assignment of linear time-invariant multivariable 2-dimensional systems by means of state and output feedback. Necessary and sufficient conditions are established for single-input systems, whereas for the multi-input case, an equivalent single-input-system approach is employed to treat the problem.
Oblique photogrammetry using unmanned aerial vehicles (UAV) is crucial to 3D scene reconstruction. Nevertheless, oblique images are generally acquired with large overlaps, and sometimes with multiple views. Although t...
Oblique photogrammetry using unmanned aerial vehicles (UAV) is crucial to 3D scene reconstruction. Nevertheless, oblique images are generally acquired with large overlaps, and sometimes with multiple views. Although this increases the level of data completeness, it introduces additional and sometimes redundant computations in tie-point matching, creating overly dense camera connections in the pose graph for bundle adjustment (BA). This study optimizes the pose graph of oblique UAV images by removing redundant image connections to guide tie-point matching. Assuming a five-camera system for oblique image collection, a pose graph called a topologically connected camera network (TCN) was initially constructed using position and orientation system (POS) data to determine the spatial connectivity among oblique images. Second, five geometric meta-parameters of overlapping images were constructed, and their influence on tie-point matching was analyzed using a data-driven approach to generate a weighted pose graph. Third, the weighted pose graph was simplified to a degree-bounded skeletal camera network (D-SCN) using the proposed two-stage multi-objective graph optimization approach. Finally, the D-SCN was embedded into a structure from motion (SfM) pipeline to produce a novel D-SCN–SfM method to reduce the required computations for tie-point matching. The proposed D-SCN-SfM method was tested using data from three large sites, each containing over 5,000 images. In addition, the D-SCN-SfM method was compared with three state-of-the-art methods. The experimental results indicate that our method can significantly reduce the required computations for tie-point matching to 1/14–1/20 as compared to a method that uses only topological constraints, that is, TCN, saving 89–92% of the time expenditure. Furthermore, the accuracy and completeness of the 3D geometry produced by the proposed method were comparable to those produced by standard SfM methods. The source code of our approach
The fast implementation of the linear and of the angular velocities of the end-effector of robotic manipulators, using the distributed arithmetic technique is described. The linear and angular velocities of the end-ef...
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The fast implementation of the linear and of the angular velocities of the end-effector of robotic manipulators, using the distributed arithmetic technique is described. The linear and angular velocities of the end-effector as well as the positional and the orientational Jacobian matrices is calculated by a cascade configuration of two pipelined arrays. The building blocks of the arrays are the distributed arithmetic-based circuits that implement the matrix-vector multiplications involved in the calculations. The digit-serial configuration of the proposed implementation of the linear and angular velocities of the end-effector is described, while the serial and the parallel configurations may result as special cases of the digit-serial configuration. The proposed distributed arithmetic computer architecture may be used in the real-time operation of the robot control system that requires the on-line computation of the position, of the linear and angular velocities of the end-effector and of the Jacobian matrix.
An effective algorithm for the calculation of stability regions in the plane of two control parameters is proposed. The algorithm is suitable for small computers. In comparison with the classical technique, the derive...
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An effective algorithm for the calculation of stability regions in the plane of two control parameters is proposed. The algorithm is suitable for small computers. In comparison with the classical technique, the derived algorithm requires fewer manual calculations. The program and its short characteristic equation is included. Utilization of the program is illustrated on an example of an automatically controlled power system having a ‘forced’ excitation system.
This paper refers to the use of a modified set of moments for the development of efficient shape discrimination and classification techniques. These moments may be applied in general for the discrimination of other pa...
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This paper refers to the use of a modified set of moments for the development of efficient shape discrimination and classification techniques. These moments may be applied in general for the discrimination of other patterns as well, such as geological, medical and robotic vision signals. A new set of efficient moments is introduced, which is invariant under rotation, translation, and scale of the image. These moments are normalized with respect to standard deviation, they appear to have better classification performance over the existing sets of moments, and they are less sensitive to noise. Application of the proposed technique to the classification of silhouettes of airplanes is given. The discrimination of an unknown shape is achieved by testing a weighted least square function.
A novel method is presented capable of constructing rule-bases via self-learning for the use of fuzzy controllers. The controlled process is assumed to be a multivariable system with strong interaction within variable...
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A novel method is presented capable of constructing rule-bases via self-learning for the use of fuzzy controllers. The controlled process is assumed to be a multivariable system with strong interaction within variables and with pure time delays in control. The objective of the proposed system is to build, in the case of two-input two-output systems, two separated and decoupled rule-bases for two control loops with some design requirements. The paper is divided into two parts. In the first part, a system structure comprising four functional modules is proposed. Then, the paper focuses on the issues concerning the learning algorithm. By introducing learning errors, three learning update laws are suggested. Furthermore, the convergence property of the learning algorithms is analysed in the sense of some defined norms. In addition, some comments and remarks about the proposed algorithms are given. The second part of the paper deals mainly with the issues of the methodology for rule-base formation and the application to the problem of multivariable control of blood pressure.
作者：
Y. Y. Yang M. Mahfouf D.A.LinkensDepartment of Automatic Control and Systems Engineering
University of Sheffield Mappin St. Sheffield S1 3JD UK Department of Automatic Control and Systems Engineering University of Sheffield Mappin St. Sheffield S1 3JD UK Department of Automatic Control and Systems Engineering University of Sheffield Mappin St. Sheffield S1 3JD UK
The accuracy of numerical simulations and many other material design calculations, such as the rolling force, rollingtorque, etc., depends on the description of stress-strain relationship of the deformed materials. On...
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The accuracy of numerical simulations and many other material design calculations, such as the rolling force, rollingtorque, etc., depends on the description of stress-strain relationship of the deformed materials. One common methodof describing the stress-strain relationship is using constitutive equations, with the unknown parameters fitted byexperimental data obtained via plane strain compression (PSC). Due to the highly nonlinear behaviour of the constitutive equations and the noise included in the PSC data, determination of the model parameters is difficult. Inthis paper, genetic algorithms were exploited to optimise parameters for the constitutive equations based on thePSC data. The original PSC data were processed to generate the stress-strain data, and data pre-processing wascarried out to remove the noise contained in the original PSC data. Several genetic optimisation schemes have beeninvestigated, with different coding schemes and different genetic operators for selection, crossover and *** was found that the real value coded genetic algorithms converged much faster and were more efficient for theparameter optimisation problem.
It is shown that when examining the controlability of the continuous-flow stirred-tank reactor the dynamics of the cooling coil, the thermometer and other additional loop elements must not be neglected. A first-order ...
It is shown that when examining the controlability of the continuous-flow stirred-tank reactor the dynamics of the cooling coil, the thermometer and other additional loop elements must not be neglected. A first-order approximation of the cooling system is determined and combined with the linearized heat and mass balances of the reactor, this giving the transfer function between the velocity of the cooling water and the temperature of the reactor. The temperature control system is analysed by means of the root locus method. It is shown how a simple root locus may be found which approximates that of the temperature control loop at high natural frequencies.
In the present study, the Volterra series theory is adopted to theoretically investigate the force transmissibility of multiple degrees of freedom （MDOF） structures, in which an isolator with nonlinear anti-symmetri...
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In the present study, the Volterra series theory is adopted to theoretically investigate the force transmissibility of multiple degrees of freedom （MDOF） structures, in which an isolator with nonlinear anti-symmetric viscous damping is assembled. The results reveal that the anti-symmetric nonlinear viscous damping can significantly reduce the force trans- missibility over all resonance regions for MDOF structures with little effect on the transmissibility over non-resonant and isolation regions. The results indicate that the vibration isolators with an anti-symmetric damping characteristic have great potential to solve the dilemma occurring in the design of linear viscously damped vibration isolators where an increase of the damping level reduces the force transmissibility over resonant frequencies but increases the transmissibility over non-resonant frequency regions. This work is an extension of a previous study in which MDOF structures installed on the mount through an isolator with cubic nonlinear damping are considered. The theoretical analysis results are also verified by simulation studies.
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