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A novel design of triple-band monopole antenna for multi-input multi-output communication

MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2013年第6期55卷 1258-1262页

作者： Ojaroudi, Nasser Ojaroudi, Mohammad Islamic Azad Univ Dept Elect Engn Ardabil Branch Ardebil Iran Islamic Azad Univ Young Res Club Ardebil Iran

In this article, a novel wireless local area network (WLAN) frequency range monopole antenna is designed and manufactured for multi-input multi-output (MIMO) applications. The proposed antenna consists of two L-shaped slots in the S-shaped radiating patch. In this structure, the S-shaped monopole antenna can create dual resonances within the WLAN range. Placement of two L-shaped slots within the S-shaped monopole antenna creates an extra resonance;the desired resonant frequencies are obtained by adjusting the dimension of the S-shaped and the L-shaped structures. The operating frequencies of the proposed antenna are 2.4/5.2/5.8 GHz, which covers WLAN system. Various configurations of array of this S-shaped monopole antenna for MIMO application are also studied. Prototypes of the proposed antenna have been constructed and studied experimentally. Good return loss and radiation pattern characteristics are obtained in the frequency band of interest. Simulated and measured results are presented to validate the usefulness of this small proposed antenna structure for MIMO applications. (c) 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:12581262, 2013;View this article online at ***. DOI 10.1002/mop.27579

关键词： S-shaped monopole antenna L-shaped slot wireless local area network multi-input multi-output systems

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An algebraic method for designing controllers for multi-input multi-output linear systems via s-domain input-output decoupling

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF systems AND CONTROL ENGINEERING 2009年第I2期223卷 263-274页

作者： Ozgoren, M. K. Middle E Tech Univ Dept Mech Engn TR-06531 Ankara Turkey

The method introduced here is applicable for multi-input multi-output, linear, and time-invariant systems. The state and output equations of the system, which are originally expressed in the t-domain, are first transformed into the s-domain. Then, input-output decoupling is achieved by generating the actual control variables as combinations of virtual control variables in such a way that each output is controlled by only the dedicated one of the virtual control variables. As the next stage, appropriate linear controllers are designed to generate the virtual control variables with feedback, feedforward, and disturbance rejection features. The design method is algebraic and involves the assignment of not only the closed-loop poles but also the type numbers associated with the reference and disturbance inputs. The multivariable transformation filter that converts the virtual control variables into actual ones is formed properly to prevent any possibility of internal instability.

关键词： multivariable systems multi-input multi-output systems linear time-invariant systems input-output decoupling non-interacting controls decoupling transformation filter

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Identification of nonlinear MIMO block-oriented systems with moving average noises using gradient based and least squares based iterative algorithms

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NEUROCOMPUTING 2012年 94卷 22-31页

作者： Salimifard, Maryam Jafari, Masoumeh Dehghani, Maryam Shiraz Univ Dept Power & Control Sch Elect & Comp Engn Shiraz Iran

Nonlinear multi-input multi-output (MIMO) models seem quite suitable to represent most industrial systems and many control problems. Furthermore, the outputs of the real systems are usually corrupted with noises which might not satisfy the assumption of white noises. This paper presents simple and efficient identification methods for nonlinear MIMO systems in the presence of colored noises. In the proposed approaches, three classes of MIMO block-oriented structures including Hammerstein, Wiener, and Hammerstein-Wiener models are studied. Appropriate and flexible representations of these models lead to a pseudo-linear-in-the-parameter problem that contains some terms related to the colored noises which are not known a priori. In this paper, gradient based and least squares based iterative learning algorithms are invoked which can successfully estimate the matrix of unknown parameters as well as the colored noises. The efficiency of the proposed identification schemes is investigated through two simulated and a real process as case studies. As the results show, these approaches are quite efficient for identification of nonlinear colored MIMO systems. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Basis functions Block-oriented models Colored noises multi-input multi-output systems Nonlinear system identification

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Online neural identification of multi-input multi-output systems

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IET CONTROL THEORY AND APPLICATIONS 2007年第1期1卷 44-50页

作者： Bazaei, A. Moallem, M. Univ Western Ontario Dept Elect & Comp Engn London ON N6A 5B9 Canada

A feedforward neural network tuning algorithm is developed, which is suitable for identification of multi-input multi-output nonlinear functions, by utilising the learning method of a conventional neuro-adaptive control technique. Using Lyapunov functions, it is shown that not only the approximation error converges to values that have arbitrarily reducible upper bounds, but also the weights of the neural network remain bounded. The effectiveness of the identification method and its application in force-control of an uncertain robot interacting with an unknown flexible environment are investigated as an application example.

关键词： identification robots learning systems learning method force control online neural identification arbitrarily reducible upper bounds Lyapunov methods Lyapunov functions adaptive control feedforward neural network tuning algorithm uncertain robot MIMO systems uncertain systems multi-input multi-output systems conventional neuro-adaptive control technique feedforward neural nets unknown flexible environment

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multi-innovation Generalized Extended Stochastic Gradient Algorithm for multi-input multi-output Nonlinear Box-Jenkins systems Based on the Auxiliary Model

Multi-innovation Generalized Extended Stochastic Gradient Al...

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International Conference on Life System Modeling and Simulation / International Conference on Intelligent Computing for Sustainable Energy and Environment (LSMS-ICSEE)

作者： Chen, Jing Wang, Xiuping Jiangnan Univ Control Sci & Engn Res Ctr Wuxi 214122 Peoples R China Wuxi Professional Coll Sci & Technol Wuxi 214028 Peoples R China

ISBN: (纸本)9783642156205

An auxiliary model based multi-innovation generalized extended stochastic gradient algorithm is developed for multivariable nonlinear Box-Jenkins systems. The basic idea is to construct an auxiliary model using the measured data and to replace the unknown terms in the information vector with their estimates, i.e., the outputs of the auxiliary model. The proposed algorithm can give high accurate parameter estimation compared with existing stochastic gradient algorithms. A simulation example is given.

关键词： Stochastic gradient multi-input multi-output systems multi-innovation identification Box-Jenkins systems Recursive identification

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An Auxiliary Model Based multi-innovation Recursive Least Squares Estimation Algorithms for MIMO Hammerstein System

An Auxiliary Model Based Multi-innovation Recursive Least Sq...

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第三十届中国控制会议

作者： WANG Xiuping~1,CHEN Jing~(1,2) 1.Wuxi Professional College of Science and Technology,Wuxi,214028,P.R.China 2.school of IoT Engineering,Jiangnan University,Wuxi,214122,P.R.China

An auxiliary model based multi-innovation recursive least squares estimation algorithms is proposed in this *** unknown variables in the information vector can be estimated by using the auxiliary *** proposed recursive least squares algorithm uses not only the current innovation but also the past innovations at each recursion and thus the parameter estimation accuracy can be ***,the simulation results indicate that the proposed algorithm has good performances.

关键词： Parameter estimation Least squares Auxiliary model identification multi-innovation identification multi-input multi-output systems

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Auxiliary model based multi-innovation algorithms for multivariable nonlinear systems

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MATHEMATICAL AND COMPUTER MODELLING 2010年第9-10期52卷 1428-1434页

作者： Chen, Jing Zhang, Yan Ding, Ruifeng Jiangnan Univ Sch Commun & Control Engn Wuxi 214122 Peoples R China Wuxi Profess Coll Sci & Technol Wuxi 214028 Peoples R China Wuxi Inst Technol Wuxi 214121 Peoples R China Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Peoples R China

This paper considers the identification problem for multi-input multi-output nonlinear systems. The difficulty of the parameter identification of such systems is that the information vector in the identification model contains unknown variables. The solution is using the auxiliary model identification idea to overcome the difficulty. An auxiliary model based multi-innovation extended stochastic gradient algorithm is presented by expanding the innovation vector to an innovation matrix. The proposed algorithm uses not only the current innovation but also the past innovations at each recursion and thus the parameter estimation accuracy can be improved. The numerical example shows that the proposed algorithm is effective. (C) 2010 Elsevier Ltd. All rights reserved

关键词： Parameter estimation Stochastic gradient Auxiliary model identification multi-innovation identification multi-input multi-output systems

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On Low-Complexity Simulation of multichannel Room Impulse Responses

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IEEE SIGNAL PROCESSING LETTERS 2010年第7期17卷 667-670页

作者： Martinez, Jorge Heusdens, Richard Delft Univ Technol NL-2628 CD Delft Netherlands

In this letter, we present a method for low-complexity simulation of multichannel room impulse responses (RIRs). Low-complexity RIR methods will become inevitable in next generation communication systems having massive amounts of microphones/loudspeakers. For a room with rigid boundaries, we show that proper sampling of the free-field plenacoustic spectrum results in the solution of the wave equation at any position in the room. We show that the spatial aliasing introduced by spectral sampling represents the wall reflections. These wall reflections are usually modelled, at least in low-complexity simulation algorithms, by the creation of virtual free-field sources outside the room, an image source model commonly referred to as the image method. The image method requires O(N(3)) operations per receiver position, whereas the newly proposed method requires only O(N log N) operations per receiver position.

关键词： multi-input multi-output systems plenacoustic function plenacoustic spectrum room impulse response

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Application of Ant Colony Optimization based algorithm in MIMO Detection

Application of Ant Colony Optimization based algorithm in MI...

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2010 IEEE World Congress on Computational Intelligence

作者： Khurshid, Kiran Irteza, Safwat Khan, Adnan Ahmed Natl Univ Sci & Technol Dept Elect Engn Islamabad Pakistan Natl Univ Sci & Technol Mil Coll Signals Islamabad Pakistan Natl Univ Sci & Technol Islamabad Pakistan

ISBN: (纸本)9781424481262

Ant colony optimization (ACO), inspired by the ants' foraging behavior, is one of the most recent techniques for solving optimization problems. We present an ACO based algorithm for symbol detection in multi-input multi-output (MIMO) system. Since symbol detection is an NP-hard problem so ACO is particularly attractive as ACO algorithms are one of the most successful strands of swarm intelligence and are suitable for applications where low complexity and fast convergence is of absolute importance. Maximum Likelihood (ML) detector gives optimal results but it uses exhaustive search technique. We show that ACO based detector can give near-optimal bit error rate (BER) at a much lower complexity level. The simulation results suggest that the proposed detector gives an acceptable performance complexity trade-off in comparison with ML and VBLAST detectors.

关键词： Spatial multiplexing System ACO multi-input multi-output systems symbol detection

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A novel neural internal model control for multi-input multi-output nonlinear discrete-time processes

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JOURNAL OF PROCESS CONTROL 2009年第8期19卷 1392-1400页

作者： Deng, Hua Xu, Zhen Li, Han-Xiong Minist Educ Key Lab Modern Complex Equipment Design & Extreme Changsha 410083 Peoples R China Cent S Univ Sch Mech & Elect Engn Changsha 410083 Peoples R China City Univ Hong Kong Dept Mfg Eng & Eng Management Hong Kong Hong Kong Peoples R China

An internal model-based neural network control is proposed for unknown non-affine discrete-time multi-input multi-output (MIMO) processes in nonlinear state space form under model mismatch and disturbances. Based on the neural state-space model built for an unknown nonlinear MIMO state space process, an approximate internal model and approximate decoupling controllers are derived simultaneously. Thus, the learning of the inverse process dynamics is not required. A neural network model-based extended Kalman observer is used to estimate the states of a nonlinear process as not all states are accessible. The proposed neural internal model control can work for open-loop unstable processes with its closed-loop stability derived analytically. The application to a distributed thermal process shows the effectiveness of the proposed approach for suppressing nonlinear coupling and external disturbances and its feasibility for the control of unknown non-affine nonlinear discrete-time MIMO state space processes. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Nonlinear discrete-time state space systems multi-input multi-output systems Internal model control Neural networks

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