检索结果-南通市图书馆

Efficient iterative adaptive pole placement algorithm

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2004年第4期15卷 636-642页

作者： LiJunmin LiJing YangLei DepartmentofAppliedMathematics XidianUniversityXi'an710071P.R.China

An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithmare respectively established. Since one-step iterative formulation in computing controller's parameters is used, the on-line computation cost is greatly reduced with respected to the traditional algorithm. The algorithm with the feed-forward can follow arbitrarily bounded output. The algorithm is also extended to multivariate case. Simulation examples show the efficiency and robustness of the algorithm.

关键词： Mathematical model Iterative algorithms Convergence Adaptive control adaptation models Stability analysis Robustness

Decentralized Adaptive Filtering for Multi-agent Systems with Uncertain Couplings

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 101-112页

作者： Hongbin Ma Yini Lv Chenguang Yang Mengyin Fu the School of Automation Beijing Institute of Technology the Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology the School of Computing and Mathematics Plymouth University

In this paper, the problem of decentralized adaptive filtering for multi-agent systems with uncertain couplings is formulated and investigated. This problem is challenging due to the mutual dependency of state estimation and coupling estimation. First, the problem is divided into four typical types based on the origin of coupling relations and linearity of the agent dynamics. Then models of the four types are given and the corresponding decentralized adaptive filtering algorithms are designed for the purpose of estimation of the unknown states and couplings which denotes the relations between agents and their neighbor agents in terms of states or outputs simultaneously,with preliminary stability analysis and discussions. For testing the effects of algorithm, with the so-called certainty-equivalence principle, control signals are designed based on the results of state estimation and coupling estimation got by the proposed decentralized adaptive filtering algorithms. Extensive simulations are conducted to verify the effectiveness of considered algorithms..

关键词： Couplings Covariance matrices Multi-agent systems adaptation models Kalman filters Mathematical model

Robust Adaptive Model Tracking for Distributed Parameter Control of Linear Infinite-dimensional Systems in Hilbert Space

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 294-301页

作者： Mark J.Balas Susan A.Frost the Embry-Riddle Aeronautical University the NASA Ames Research Center

This paper is focused on adaptively controlling a linear infinite-dimensional system to track a finite-dimensional reference *** a linear continuous-time infinite-dimensional plant on a Hilbert space with disturbances of known waveform but unknown amplitude and phase,we show that there exists a stabilizing direct model reference adaptive control law with the properties of certain disturbance rejection and *** plant is described by a closed,densely defined linear operator that generates a continuous semigroup of bounded operators on the Hilbert space of *** central result will show that all errors will converge to a prescribed neighborhood of zero in an infinitedimensional Hilbert *** result will not require the use of the standard Barbalat’s lemma which requires certain signals to be uniformly *** result is used to determine conditions under which a linear infinite-dimensional system can be directly adaptively controlled to follow a reference *** particular,we examine conditions for a set of ideal trajectories to exist for the tracking *** results are applied to adaptive control of general linear diffusion systems described by self-adjoint operators with compact resolvent.

关键词： Robustness adaptation models Adaptive control Hilbert space Trajectory Learning (artificial intelligence)

Reinforcement Learning Based Controller Synthesis for Flexible Aircraft Wings

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2014年第4期1卷 435-448页

作者： Manoj Kumar Karthikeyan Rajagopal Sivasubramanya Nadar Balakrishnan Nhan T.Nguyen the Missouri University of Science&Technology the NASA Ames Research Center Moffet Field

Aeroelastic study of flight vehicles has been a subject of great interest and research in the last several years. Aileron reversal and flutter related problems are due in part to the elasticity of a typical airplane. Structural dynamics of an aircraft wing due to its aeroelastic nature are characterized by partial differential equations. Controller design for these systems is very complex as compared to lumped parameter systems defined by ordinary differential equations. In this paper, a stabilizing statefeedback controller design approach is presented for the heave dynamics of a wing-fuselage model. In this study, a continuous actuator in the spatial domain is assumed. A control methodology is developed by combining the technique of “proper orthogonal decomposition” and approximate dynamic programming. The proper orthogonal decomposition technique is used to obtain a low-order nonlinear lumped parameter model of the infinite dimensional system. Then a near optimal controller is designed using the single-network-adaptive-critic technique. Furthermore,to add robustness to the nominal single-network-adaptive-critic controller against matched uncertainties, an identifier based adaptive controller is proposed. Simulation results demonstrate the effectiveness of the single-network-adaptive-critic controller augmented with adaptive controller for infinite dimensional systems.

关键词： adaptation models Optimal control Aircraft Cost function Method of moments Atmospheric modeling Adaptive control Learning (artificial intelligence)

An Improved Result of Multiple Model Iterative Learning Control

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 315-322页

作者： Xiaoli Li Kang Wang Dexin Liu the School of Automation and Electrical Engineering University of Science and Technology Beijing

For system operating repetitively,iterative learning control(ILC) has been tested as an effective method even with estimated ***,the control performance may deteriorate due to sudden system failure or the adoption of imprecise *** multiple model iterative learning control(MMILC) method shows great potential to improve the transient response and control ***,in existed MMILC,the stability can be guaranteed only by finite switching or very strict conditions about coefficient matrix,which make the application of MMILC a little *** this paper,an improved MMILC method is *** procedure is simplified and the ceasing condition is *** with infinite times of model switching,system output is proved convergent to the desired *** studies are carried out to show the effectiveness of the proposed method.

关键词： Learning (artificial intelligence) adaptation models Trajectory Stability analysis Transient response Nonlinear systems

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2014年第4期1卷 423-434页

作者： Nhan T.Nguyen Sivasubramanya N.Balakrishnan the NASA Ames Research Center Moffett Field the Missouri University of Science and Technology

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and the predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and the predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

关键词： Optimal control Adaptive control Uncertainty adaptation models Robustness Cost function NASA Learning (artificial intelligence)

Flexible Bearing-Only Rendezvous Control of Mobile Robots

在线全文

学校读者我要写书评

暂无评论

Flexible Bearing-Only Rendezvous Control of Mobile Robots

Adaptive target scheme for learning control of post-field alignment

第36届中国控制会议

作者： Shiyu Zhao Ronghao Zheng

ISBN: (纸本)9781538629185

In this paper we study rendezvous control of multiple mobile *** propose a control law that merely requires each robot to measure the relative bearings of their neighbors in their local coordinate *** measurement or relative position estimation is not *** theory,the proposed control law verifies that distance information is redundant in rendezvous control tasks though the objective of rendezvous is to decrease the inter-robot *** practice,the control law provides a simple solution to vision-based rendezvous tasks where bearings can be measured by visual ***,we generalize the proposed control law by introducing an additional heading vector into the control *** heading vector may preserve the system convergence and,in the meantime,provides great flexibility to adapt the control law for nonholonomic robot models or obstacle avoidance.

关键词： Robot kinematics Robot sensing systems Convergence adaptation models Position measurement

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Adaptive target scheme for learning control of post-field al...