This paper concerns the control law design by variable structure control for a kind of uncertain discrete-time systems. Why the chattering shows up for this kind of systems by discrete reaching law is investigated, an...
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ISBN:
(纸本)9781538635247
This paper concerns the control law design by variable structure control for a kind of uncertain discrete-time systems. Why the chattering shows up for this kind of systems by discrete reaching law is investigated, and then a developed variable structure controller is designed based on grey prediction iterative algorithm. Based on the grey prediction model, the parameter values are obtained. A criterion that the system state reaches the switching hyper plane in limited time is provided. In this paper its novelty is that the arrival time can be shorten by the developed variable structure controller based on grey prediction iterative algorithm. Approaching to the equilibrium state, chattering of the system can be reduced. Extensive simulation results are presented to illustrate the effectiveness by the developed method.
A gradient-based iterative algorithm is established for solving the extended coupled Sylvester matrix equations A XB + A YB = F and C XD + C XD = F by using the hierarchical identification *** prove that the iterative...
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ISBN:
(纸本)9781509046584
A gradient-based iterative algorithm is established for solving the extended coupled Sylvester matrix equations A XB + A YB = F and C XD + C XD = F by using the hierarchical identification *** prove that the iterative solution converges fast to the exact one for any initial iterative value if the coupled matrix equations has a unique solution.A numerical example is offered to illustrate the efficiency of the proposed algorithm.
In this paper, the mixed-norm optimization is investigated for sparse signal reconstruction. Furthermore, an iterative optimization algorithm based on the projection method is presented for face recognition. From the ...
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ISBN:
(纸本)9783030228088;9783030228071
In this paper, the mixed-norm optimization is investigated for sparse signal reconstruction. Furthermore, an iterative optimization algorithm based on the projection method is presented for face recognition. From the theoretical point of view, the optimality and convergence of the proposed algorithm is strictly proved. And from the application point of view, the mixed norm combines the L-1 and L-2 norms to give a sparse and collaborative representation for pattern recognition, which has higher recognition rate than sparse representation algorithms. The algorithm is designed by combining the projection operator onto a box set with the projection matrix, which is effective to guarantee the feasibility of the optimal solution. Moreover, numerical experiments on randomly generated signals and three face image data sets are presented to show that the mixed-norm minimization is a combination of sparse representation and collaborative representation for pattern classification.
The main contribution of this study is that the applicability and convergence domain of a fifth-order convergent equation solver is extended. We use omega condition on the first Frechet derivative to study the local a...
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The main contribution of this study is that the applicability and convergence domain of a fifth-order convergent equation solver is extended. We use omega condition on the first Frechet derivative to study the local analysis, and this expands the applicability of the formula for such problems where the earlier study based on Lipschitz constants cannot be used. Also, we avoid the use of the extra assumption on boundedness of the first derivative of the nonlinear operator. Our idea can be used on other iterative methods. Numerical tests confirmed that the proposed analysis produces a larger convergence domain, in comparison to the earlier study, without using additional conditions.
This paper considers a problem of signal modeling for multi-frequency signals. Because many characteristic parameters are contained in the multi-frequency signals, it is difficult to obtain these estimates of these ch...
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ISBN:
(纸本)9781665440899
This paper considers a problem of signal modeling for multi-frequency signals. Because many characteristic parameters are contained in the multi-frequency signals, it is difficult to obtain these estimates of these characteristic parameters. According to the different relations between the signal output and the amplitude parameters and frequency parameters of the multi-frequency sine signal, the signal parameters are divided into two parameter sets. In terms of these two different parameter sets, two identification sub-models are constructed for deriving two identification sub-algorithms by means of the gradient search and iterative technique. By uniting two identification algorithms, a joint gradient-based iterative signal modeling method is presented for estimating the total parameters of the multi-frequency sine signal. The performance of the proposed signal modeling method is validated through the computer simulations.
LMJ and LIL are two French high power lasers dedicated to fusion and plasma experiments. These laser beams involve hundreds of large optical components, the clear aperture of the beams being 400x400 mm(2). In order to...
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ISBN:
(纸本)9780819487957
LMJ and LIL are two French high power lasers dedicated to fusion and plasma experiments. These laser beams involve hundreds of large optical components, the clear aperture of the beams being 400x400 mm(2). In order to control the flatness requirements of its optics, the CEA has an 800 mm diameter Fizeau interferometer. Determining if optical components fulfil the very strict wavefront specifications can be difficult because these specifications can be equivalent to the defects of the reference flats of the interferometer. That is why we want to calibrate our reference flats in order to subtract their defects from the performed measurements. This absolute calibration is based on an iterative algorithm requiring three reference flats. In addition to the three basic combinations of the three flats, this method uses rotations and translations of one flat with respect to the others. First, we shall present a characterization of this method. The choice of different parameters, as the operations of translations and rotations required, will be discussed. Moreover, experimental errors have been introduced in the simulations and their limit values have been studied with regard to the other parameters. An application of this method on our three reference flats has been implemented over a 600 mm diameter. An absolute calibration requires a very precise implementation of the measurements and then we will see why data processing is necessary to reduce the residual shifts in translation but also in rotation and in zoom between the different measurements. Lastly, first uses of the absolute maps show a factor 5 to 10 improvement on the final accuracy.
It is known that supercapacitors exhibits a voltage-dependent capacitance and the capacitance varies approximately linearly with voltage in the normal operation voltage range. To solve the online supercapacitor capaci...
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ISBN:
(纸本)9781728143231;9781728143224
It is known that supercapacitors exhibits a voltage-dependent capacitance and the capacitance varies approximately linearly with voltage in the normal operation voltage range. To solve the online supercapacitor capacity identification problem, which is an important function to implement in supercapacitor management system, firstly, linear least squares (LLS) is applied to get a closed-form solution based on a sequence of sampling terminal voltage and charging current data, and in the meanwhile, the details of voltage data processing to obtain more accurate differential capacitance values are elaborated. Secondly, to overcome the difficulty that the closed-form solution involves large data set, takes calculation of matrix inverse, and hence leads to heavy computing burden, an iterative algorithm of LLS is deduced, which gets rid of calculating matrix inverse directly, decomposes the computing burden of LLS into each sampling period, and therefore makes itself more applicable in online identification situations. Lastly, the effectiveness of the algorithm is verified by experiment.
In this paper, by introducing a tuning parameter, an explicit iterative algorithm is constructed for solving the continuous Lyapunov matrix equations associated with Ito stochastic systems. A necessary and sufficient ...
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ISBN:
(纸本)9789881563958
In this paper, by introducing a tuning parameter, an explicit iterative algorithm is constructed for solving the continuous Lyapunov matrix equations associated with Ito stochastic systems. A necessary and sufficient condition is provided to guarantee the convergence of the proposed algorithm by using the Kronecker product. Moreover, some easily verifiable convergence results are developed for the proposed algorithm based on the obtained necessary and sufficient condition. In addition, a method is given for the selection of the optimal tuning parameter. Finally, an example is applied to verify the effectiveness of the presented algorithm.
In this paper, we introduce a new class of nonlinear variational inclusions with H-monotone mappings. By using the resolvent operator method associated with H-monotone mappings in Hilbert spaces. we prove the existenc...
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ISBN:
(纸本)9812700420
In this paper, we introduce a new class of nonlinear variational inclusions with H-monotone mappings. By using the resolvent operator method associated with H-monotone mappings in Hilbert spaces. we prove the existence and uniqueness of solution for this class of nonlinear variational inclusions. We also construct a new Ishikawa type iterative algorithm for finding approximate the solution of this nonlinear variational inclusion and discuss the convergence and stability of sequence of iterates generated by the algorithm. The present results improve and extend many known results in the literature.
We generate optimised phase masks by using an iterative Fourier Transform algorithm (IFTA) and use it for beam multiplexing in an experiment to generate an array of uniform spots in 1D and 2D. We quantify the efficacy...
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ISBN:
(纸本)9781510637795
We generate optimised phase masks by using an iterative Fourier Transform algorithm (IFTA) and use it for beam multiplexing in an experiment to generate an array of uniform spots in 1D and 2D. We quantify the efficacy of the iterative algorithm experimentally by computing the uniformity and the efficiency and show that the optimised phase masks yield multiplexed beamlets having high uniformity (similar to 90%). We also find that the algorithm converges within few tens of iterations requiring moderate computational budget and can be useful for almost real-time applications. We compare the performance of the iterative algorithm with global linear corrections in the look-up table (LUT) of a phase limited SLM and find that the former perform with about 20% better efficiency. Besides obtaining array of 1D/2D spots having high uniformity using IFTA, our result exemplifies the use of iterative algorithms for improving efficiency of phase limited SLMs, which is a less explored area of research.
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