This paper deals with the finite-time stabilization problem for discrete-time Markov jump nonlinear systems with time delays and norm-bounded exogenous disturbance. The nonlinearities in different jump modes are parameterized by neural networks. Subsequently, a linear difference inclusion state space representation for a class of neural networks is established. Based on this, sufficient conditions are derived in terms of linear matrix inequalities to guarantee stochastic finite-time boundedness and stochastic finite-time stabilization of the closed-loop system. A numerical example is illustrated to verify the efficiency of the proposed technique.
No abstract is provided for this article.
We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point (AP) equipped with multiple antennas. The main restriction is that standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is proposed to overcome restrictions imposed by the legacy terminals requirement. Simulations based on the IEEE 802.11 channel models demonstrate that a near doubling of downlink capacity can be achieved in a conference room environment.
With increasing and tightening requirements on the control and optimization performance, the traditional control and optimization strategies may not qualify in many application problems.To meet the challenges and requirements, advanced control and optimization methodologies should be employed or developed.Here, the advanced control and optimization denote the ones which, in principle, can best achieve the objectives in the presence of nonlinearities, highly interactivities, or newly emerged operating circumstances.As the advanced control and optimization will provide a basis for the design and operation of practical systems, these advanced techniques would result in substantial and sustainable benefits.The overall aims of this special issue are twofold: (1) to provide an up-to-date overview of the research directions in the advanced control and optimization; (2) to illustrate how to formulate problems from automotive systems and develop suitable theory to solve the corresponding problems.Of particular interest the papers in this special issue are devoted to the development of advanced control and optimization including network control, nonlinear model predictive control, dynamic programming, and integral programming, with applications to complex automotive systems including vehicle dynamics and control, combustion and emission control, and vehicle integration and optimization, for instance.Topics in this special issue include, but are not limited to: (1) network analysis and protocol optimization, (2) fast nonlinear model predictive control and optimization, (3) advanced vehicle
This paper considers the problem of local capacity H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control for a class of production networks of autonomous work systems with time-varying delays in the capacity changes. The system under consideration is modelled in a discrete-time singular form. Attention is focused on the design of a controller gain for the local capacity adjustments which maintains the work in progress (WIP) in each work system in the vicinity of planned levels and guarantees the asymptotic stability of the system and reduces the effect of the disturbance input on the controlled output to a prescribed level. In terms of a matrix inequality, a sufficient condition for the solvability of this problem is presented using an appropriate Lyapunov function, which depends on the size of the delay and is solved by existing convex optimization techniques. When this matrix inequality is feasible, the controller gain can be found by using LMI Toolbox Matlab. Finally, numerical results are provided to demonstrate the proposed approach.
No abstract is provided for this article.
This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy in fault detection. Therefore, there is no need to deal with original data or refer to other algorithms, making the classification problem simple to handle. In order to further illustrate the efficiency, an industrial benchmark of Tennessee Eastman (TE) process is utilized with the SVM algorithm and PLS algorithm, respectively. By comparing the indices of detection performance, the SVM technique shows superior fault detection ability to the PLS algorithm.
In this study, a model predictive control (MPC)‐based fault tolerant control (FTC) design method for air‐breathing hypersonic vehicles (AHVs) is proposed. The non‐linear model of AHVs is recalled and the FTC problem is discussed. The problem is challenging because the relationship between flight dynamics and the control input is not so clear. For the purpose of non‐linear FTC, an optimisation‐based reference reconfiguration method is given. Through the reconfiguration, a new reference command, which can be realised by the faulty system, is constructed. Actuator saturation has been take into account when constructing the new reference command. An MPC‐based controller reconfiguration method is proposed with respect to the new command and system faults. Finally, simulations are given to show the effectiveness of the proposed control method.
Compared with fixed-bottom installation, deep water floating wind turbine has to undergo more severe structural loads due to extra degrees of freedom. Aiming for effective load reduction, this paper deals with the evaluation of a passive structural control design for a spar-type floating wind turbine, and the proposed strategy is to install a tuned mass damper (TMD) into the spar platform. Firstly, a mathematical model for wind turbine surge-heave-pitch motion is established based on the D’Alembert’s principle of inertial forces. Then, parameter estimation is performed by comparing the outputs from the proposed model and the state-of-the-art simulator. Further, different optimization methods are adopted to optimize TMD parameters when considering different performance indices. Finally, high fidelity nonlinear simulations with previous optimized TMD designs are conducted under different wind and wave conditions. Simulation results demonstrate both the effectiveness and limitation of different TMD parameter choices, providing parametric analysis and design basis for future improvement on floating wind turbine load reduction with structural control methods.
No AccessJournal of Speech, Language, and Hearing ResearchErratum1 Apr 2014Erratumis erratum ofUsing Statistical Process Control Charts to Study Stuttering Frequency Variability During a Single Day Hamid Karimi, Sue O'Brian, Mark Onslow, Mark Jones, Ross Menzies, and Ann Packman Hamid Karimi Google Scholar More articles by this author , Sue O'Brian Google Scholar More articles by this author , Mark Onslow Google Scholar More articles by this author , Mark Jones Google Scholar More articles by this author , Ross Menzies Google Scholar More articles by this author and Ann Packman Google Scholar More articles by this author https://doi.org/10.1044/2014_JSLHR-S-14-0069 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In Additional Resources FiguresReferencesRelatedDetailsRelated articlesUsing Statistical Process Control Charts to Study Stuttering Frequency Variability During a Single Day Volume 57Issue 2April 2014Pages: 705-705 Get Permissions Add to your Mendeley library History Published in issue: Apr 1, 2014 Metrics Topicsasha-topicsasha-article-typesleader-topicsCopyright & PermissionsCopyright © 2014 American Speech-Language-Hearing AssociationPDF downloadLoading ...
No abstract is provided for this article.
The problem of bounded-input bounded-output (BIBO) stability is investigated for a class of delay switched systems with mixed time-varying discrete and constant neutral delays and nonlinear perturbation. Based on the Lyapunov-Krasovskii functional theory, new BIBO stabilization criteria are established in terms of delay-dependent linear matrix inequalities. The numerical simulation is carried out to demonstrate the effectiveness of the results obtained in the paper.
This paper is dealing with the problem of observer-based event-triggered sliding mode control for fractional-order uncertain switched systems with a positive order less than one. Firstly, a fractional-order state observer is designed, based on which a fractional-order integral sliding surface function is proposed. Then, utilizing the estimated observer error and sliding mode error vectors, an event-triggered condition is constructed to decide whether the current control signal should be updated or not. Besides, sufficient conditions are derived in the forms of linear matrix inequalities (LMIs) to ensure finite-time stability of the augmented closed-loop system by adopting an average dwell time approach. Thereafter, to avoid the occurrence of infinite triggers within finite time, this paper also discusses the Zeno behavior and refines the results in the previous literature. Finally, to illustrate the effectiveness and superiority of the proposed method, three numerical simulations are provided.
This paper addresses the problem of state and fault estimation for linear continuous-time systems with actuator failures. A new estimation technique is presented to deal with this design problem. In the proposed approaches, the original system is first augmented in a descriptor system, and a new sliding mode observer is introduced to obtain accurate estimations of both system states and actuator faults. A numerical example is presented to illustrate the effectiveness and applicability of the proposed technique.
In this paper, the sliding mode control (SMC) design for nonlinear stochastic semi-Markov switching systems (S-MSSs) is studied via the bound of time-varying transition rate matrix, in which semi-Markov switching parameters, stochastic disturbance, uncertainty, and nonlinearity are all considered in a unified framework. The system under consideration is more general, which covers the Markov switching system with sojourn-time-independent transition rate matrix as a special case. Many practical systems subject to unpredictable structural variations can be characterized by nonlinear stochastic S-MSSs with sojourn-time-dependent transition rate matrix. The specific information about the bound of time-varying transition rate matrix is known for the sliding mode controller design. First, by using the stochastic semi-Markov Lyapunov function, sojourn-time-dependent sufficient conditions are developed to guarantee the closed-loop sliding mode dynamics stochastically stable. Then, the SMC law is constructed to ensure the reachability of the sliding mode dynamics in a finite-time level. Finally, one joint of space robot manipulator model is described as nonlinear stochastic S-MSSs to illustrate the validity of the proposed SMC design method.
This paper is concerned with the output-feedback controller design for consensus of a class of heterogeneous linear multiagent systems with the aperiodic sampled-data measurement. Under mild assumptions that the sampling periods are taken from a given set and the agent systems are time synchronized, an equivalent switched system model is first proposed for the heterogeneous agent system with nonuniform sampling. The overall leader-following tracking control problem (LFTCP) is then formulated as the output regulation of a discrete-time switched system. By using some algebraic manipulations, the control problem under consideration is further decoupled into two control subproblems, i.e., a static output-feedback (SOF) control problem plus a simple feedback control problem related to the communication topology. Based on the Lyapunov stability theory, some sufficient conditions are obtained for the solvability of LFTCP. In our results, the SOF controller gains are determined by solving some strict linear matrix inequalities. Finally, a simulation study on the modified Caltech multivehicle wireless testbed is presented to show the effectiveness of the proposed design method.
