Editorial New Developments in Mathematical Control and …downloads.hindawi.com/journals/mpe/2013/126878.pdf · 2019-07-31 · New Developments in Mathematical Control and Information

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2013, Article ID 126878, 6 pageshttp://dx.doi.org/10.1155/2013/126878

EditorialNew Developments in Mathematical Control andInformation for Fuzzy Systems

Hamid Reza Karimi,1 Mohammed Chadli,2 and Peng Shi3,4

1 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway2 Laboratory of Modeling, Information and Systems, University of Picardie Jules Verne, 80039 Amiens, France3 College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia4 School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia

Correspondence should be addressed to Hamid Reza Karimi; [email protected]

Received 14 March 2013; Accepted 14 March 2013

Copyright © 2013 Hamid Reza Karimi et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

1. Discussion and Up-To-Date Overview

Intelligence techniques, such as fuzzy logic approaches, havelong been applied to dynamical systemswithmany importanttheoretical solutions and successful applications. The overallaim of this special issue is both to promote discussion amongresearchers actively working on applied fuzzy systems andto provide an up-to-date overview of the research directionsand advance observer and controllersmethods in the field. Ofparticular interest, the papers in this special issue are devotedto the development of mathematical methodologies analysis,control and observer problems of fuzzy systems, includingnonlinear dynamics, fuzzy logic, and interdisciplinary topicswith artificial intelligence. Potential topics include, but arenot limited to (1) fuzzy controller design (robust control,adaptive control, and supervisory control), (2) fuzzy observerdesign (adaptive observers, sliding mode observers, andunknown inputs observers), (3) cascaded fuzzy systems andobservers, (4) synchronization in fuzzy systems, (5) sto-chastic fuzzy systems, (6) robust fault detection and iso-lation, fault diagnosis, and fault-tolerant control of fuzzysystems, (7) applications of fuzzy controllers and observersto complex systems (including hardware and software devel-opment environments for fuzzy systems), (8) fuzzy logics,and (9) fuzzy modeling and optimization. For this specialissue we solicit submissions from mathematicians, electri-cal/control/mechanical engineers, and computer scientists.After a rigorous peer review process, 31 papers have been

selected. These papers have covered both the theoreticaland practical aspects of fuzzy systems in the broad areasof dynamical systems, mathematics, statistics, operationalresearch, and engineering.

During the past decades, the problem of stability analysisof fuzzy systems has received significant attentions. In thepaper entitled “Delay-dependent stability analysis of uncertainfuzzy systems with state and input delays under imperfectpremise matching” by Z. Zhang et al., the robust stabilityand stabilization problems are studied for general nonlinearfuzzy systems with time-varying state and input delays.For obtaining a less conservative delay-dependent robuststability criterion, the authors introduce a novel augmentedLyapunov function with an additional triple-integral term tothe stability analysis for the systems. Moreover, for improv-ing the design flexibility and reducing the implementationcost of the fuzzy controller, they propose a new designapproach different from the traditional PDC design tech-nique, which means that the fuzzy model and the fuzzycontrollers share different membership functions. Some lessconservative stability conditions are obtained, and a newdesign approach is also proposed. The proposed stabilityconditions are less conservative in the sense of getting largerallowable time-delay and obtaining smaller feedback controlgains, and the design flexibility is enhanced by arbitrarilyselecting simple fuzzy membership functions. In the paperentitled “Stability analysis and stabilization of T-S fuzzy

2 Mathematical Problems in Engineering

delta operator systems with time-varying delay via an input-output approach” by Z. Zhong et al., the stability analysisand stabilization problems are investigated for fuzzy deltaoperator systems with time-varying delay. The delta operatormethod is introduced to transform T-S fuzzy continuous-time systems into discrete-time systems, and the input-output(IO) approach is employed to deal with the stability analysisand control design of T-S fuzzy delta operator systems withtime-varying delay.Themain contribution of the paper is thatthe stability analysis and stabilization problems for fuzzy deltaoperator systems with time-varying delay are investigatedby the IO Approach. A model approximation method isemployed to transform the original system into an equivalentinterconnected system, which is comprised of a forwardsubsystemwith constant time-delays and a feedback one withdelayed uncertainties, such that less conservative results areensured.

The problems of modeling and identification have longbeen the main stream of research topics, and much efforthas been made for fuzzy systems. In order to approximateany nonlinear systems, not just affine nonlinear systems,generalized T-S fuzzy systemswhere the control variables andthe state variables are all premise variables are introducedin the paper entitled “A novel identification method forgeneralized T-S fuzzy systems” by L. Huang et al.. In order toimproving the identification effect, a new method combinedcolony algorithm and genetic algorithm is proposed. Firstly,fuzzy spaces and rules are determined by using ant colonycluster algorithm to get the best one, and colony clusteralgorithm has general optimizing capability, which is betterthan general cluster algorithm. Secondly, the state-spacemodel parameters are optimized by genetic algorithm basedon the least square method, which provided the betterconsequence parameters. In the paper entitled “Approximateanalytic and numerical solutions to Lane-Emden equationvia fuzzy modeling method” by D. Wang et al., a novelalgorithm, called variable weight fuzzymarginal linearization(VWFML) method, is proposed to obtain the approximateanalytic and numerical solutions to Lane-Emden equations.Themain ideas of the VWFMLmethod are as follows. Firstly,the authors need to transfer a group of data into fuzzy rules.Then, they, respectively, use two partition methods to dividethe input universes and utilize fuzzy marginal linearizationmethod to obtain the corresponding fuzzy system. By trans-ferring initial value technology, the authors can solve thesetwo fuzzy systems. Finally, they take weighted sum of thesetwo solutions and obtain the approximate solutions of theLane-Emden equations. When the Lane-Emden equation isunknown and only data information can obtained, many tra-ditional numerical approximationmethods could not solve it.The main contribution of this paper is that the authors canonly use some data information to obtain the approximateanalytic and numerical solutions to Lane-Emden equationwith high accuracy. And this method is easy to be imple-mented and extended for solving other nonlinear differentialequations. In the paper entitled “Bi-objective optimizationmethod and application of mechanism design based on pigs’payoff game behavior” by L. Wang et al., a new bi-objectiveoptimization game method is proposed. Two design goals

can be regarded as two game players, the design variablesset can be regarded as strategy subsets named 𝑆

1and 𝑆2, and

the constraints in multiobjective problems can be regardedas constraints in the game method. Through the specifictechnological means, the design variables can be dividedinto each game players strategy subsets (𝑆

1and 𝑆2), and two

payoff functions u are constructed based on pigs’ payoff gamebehavior. For optimization problems with preferred target,the designers need to emphasize one design goal. For thisproblem, there exist traditional methods such as weightingmethod (by adjusting the weight of each goal), hierarchicalsequence method (by adjusting the objective optimizationorder), and goal programming method. In this paper, onenew bi-objective optimization game method is proposedbased on pigs’ payoff game behavior for solving optimizationproblemswith preferred target. It takes bi-objective optimiza-tion of luffing mechanism of compensative shave block; forexample, the results show that the method can effectivelysolve the bi-objective optimization problems with preferredtarget (designers need to take the preferred target as the smallpig side and take another target as the big pig side), theefficiency and accuracy are well, and the solution is obtainedonly through fewer game rounds. Although the Markowitzmean-variance (MV) portfolio optimization theory has beenwidely used, which leads the investment theory to a newera, in the paper entitled “Fuzzy investment portfolio selectionmodels based on interval analysis approach” by H. Guo et al.,the authors found that this model has unintuitive problemin investment portfolio selection in economic decision. Thusthis paper employs fuzzy set theory and extends it to a fuzzyinvestment portfolio selection model to solve this problem.Our model establishes intervals for expected returns and riskpreference, which can take into account investors’ differentinvestment appetite and thus can find the optimal resolutionfor each interval. In the empirical part, we test this modelin Chinese stocks investment and find that this model canfulfill different kinds of investors’ objectives. Furthermore,investment risk can be decreased when we add investmentlimit to each stock in our model. The results indicate thatfuzzy set theory is useful to avoid the problems of Markowitzmean-variance portfolio model and takes into account dif-ferent expected return levels and risk preference levels. In thepaper entitled “On interval valued supra fuzzy syntopogenousstructure” by F. Sleim and H. Mustafa, the authors generalizethe concept of supra fuzzy syntopogenous space by using thenotion of interval valued set. Topology and its generalizationproximity and syntopogenous are branches of mathematicswhich have many real life applications. They believe thatthe generalized topological structure suggested in this paperwill be important base for modification of medical diagnosis,decision making, and knowledge discovery.

In the past decades, the issue of control design for fuzzysystems has received considerable research interests and hasfound successful applications in a variety of areas. An adap-tive fuzzy slidingmode controller for a class of uncertain non-linear systems is proposed in the paper entitled “Fuzzy slidingmode controller design using Takagi-Sugeno modelled nonlin-ear systems” by S. Bououden et al.. The unknown systemdynamics and upper bounds of the minimum approximation

Mathematical Problems in Engineering 3

errors are adaptively updated with stabilizing adaptive laws.The closed-loop system driven by the proposed controllers isshown to be stable with all the adaptation parameters beingbounded. The performance and stability of the proposedcontrol system is achieved analytically using the Lyapunovstability theory. In the paper entitled “Fuzzy variable structurecontrol for uncertain systems with disturbance” by B. Wang etal., the authors focus on the fuzzy variable structure controlfor uncertain systems with disturbance. Specifically, the fuzzycontrol is introduced to estimate the control disturbance,and the switching control is included to compensate theapproximation error and possess the characteristic of sim-pleness in design and effectiveness in attenuating the controlchattering. In the paper entitled “Robust 𝐻

∞control for a

class of uncertain switched fuzzy time-delay systems based onT-S models” by Y. Cui et al., the authors have developeda robust 𝐻

∞control with disturbance attenuation level 𝛾

approach for a class of uncertain switched fuzzy time-delaysystems based on T-S models. Each and every subsystemof the switched systems is an uncertain fuzzy one to whichthe PDC (parallel distributed compensation) controller ofevery subfuzzy system is proposed with its main conditiongiven in a more solvable form of convex combinations. Theclosed-loop stability of the proposed robust 𝐻

∞control

scheme is rigorously proved using Lyapunov theory. Finally,switching law of the state-dependent form achieving systemquadratic stability of the switched fuzzy system is given. In thepaper entitled “direct adaptive fuzzy sliding mode control withvariable universe fuzzy switching term for a class of MIMOnonlinear systems” byG.Haigang et al., the authors developeda novel framework for the control of the MIMO nonlinearwith model uncertainty and external disturbances. They alsoproposed a high-precision controller by the variable universefuzzy control theory. In the paper entitled “A Fuzzy approachto robust control of stochastic nonaffine nonlinear systems”by T. Gang et al., the authors investigate the stabilizationproblem for a class of discrete-time stochastic nonaffinenonlinear systems (SNNS) based on generalized stochasticT-S fuzzy models. By using the function approximationcapability of the stochastic T-S fuzzy models, the originalSNNS can be exactly represented by a stochastic T-S fuzzymodel with some norm bounded approximation errors asthe uncertainty term on any compact set. In this way, thestabilization problem of the SNNS can be solved as a robuststabilization problem of the obtained uncertain stochasticT-S fuzzy models. By using a class of piecewise dynamicfeedback fuzzy controllers and piecewise quadratic Lyapunovfunctions, robust semiglobally stabilization of SNNS can beformulated in terms of linear matrix inequalities. In thepaper entitled “adaptive fuzzy tracking control for uncertainnonlinear time-delay systems with unknown dead-zone input”by C. Chiang, the problem of output tracking control isinvestigated for a class of uncertain nonlinear state time-delay systems containing unknown dead-zone input andunmatched uncertainties. In general systems, there existsome nonsmooth nonlinearities in the actuators, such asdead zone, saturation, and backlash. However, the dead-zone characteristics in actuators may severely limit theperformance of the systems. Also, time-delay characteristic

and the existence of uncertain elements usually confrontedin engineering systemsmay degrade the control performanceand make the systems unstable. The main features of theproposed robust adaptive fuzzy controller are summarized asfollows. (i) An adaptive law is used to estimate the proper-ties of the dead-zone model intuitively and mathematically,without constructing a dead-zone inverse. (ii) Fuzzy logicsystems with some appropriate learning laws are appliedto approximate the nonlinear gain function and the upperbounded functions of uncertainties. (iii)Theunknownupperbound of the uncertainties caused by approximation (orfuzzy modeling) error is estimated by a simple adaptive law.(iv) By means of Lyapunov stability theorem, the proposedcontroller cannot only guarantee the robust stability of thewhole closed-loop system, but also obtain the good trackingperformance. In this paper entitled “Fuzzy PD control ofnetworked control systems based on CMAC neural network”by L. Huang and J. Chen, the main problem is how to designthe fuzzy PD controller and combine with the cerebellarmodel articulation controller to compose a integral controllerwhich used in the networked control systems effectively. Inorder to solve this problem, the switching control systembetween fuzzy PD and PD control is proposed. PD controlin the small deviation is applied to obtain higher staticcontrol accuracy, and fuzzy PD control in large deviationsis applied to obtain faster dynamic response and smallerovershoot. The paper entitled “Fuzzy control and connectedregion marking algorithm-based SEM nanomanipulation” byD. Li et al. is motivated for manipulating the nanocomponentin SEM with telepresence as in macroscale. With the help ofvirtual reality and haptic technology, the SEM-based master-slave telenanomanipulation platform is established havingthe performance of security, reliable, and real time withoutforce sensor. The CRM algorithm is introduced to processthe 2D SEM image which provides effective position data ofthe objects for updating the virtual environment. The fuzzycontrol algorithm is adopted in the master-slave control toobtain relatively stable control variable to avoid damage ofplatform.

Over the past decades, the observer/filter problems offuzzy systems have been investigated extensively, since theyare very useful in signal processing and engineering appli-cations. In the paper entiled “Robust observer design forTakagi-Sugeno fuzzy systems with mixed neutral and discretedelays and unknown inputs” by H. Karimi and M. Chadli, arobust observer design is proposed for Takagi-Sugeno fuzzyneutral models with unknown inputs. The model consists ofa mixed neutral and discrete delay, and the disturbances areimposed on both state and output signals. Delay-dependentsufficient conditions for the design of an unknown input T-Sobserver with time delays are given in terms of linear matrixinequalities. In the paper entitled “Observer-based robustadaptive fuzzy control for MIMO nonlinear uncertain systemswith delayed output” by C. Chiang, the problem of controllerdesign is considered for a class ofMIMOnonlinear uncertainoutput-delay systems whose states are not available. Thecommon feature of most previous results is the assumptionthat the controlled systems are free of uncertainties, orthe uncertainties are assumed to be a bounded external


disturbance. Therefore, the motivation of this paper is tosynthesize an observer-based robust adaptive fuzzy controlscheme to deal with the tracking control problem for a classof MIMO nonlinear uncertain systems with delayed outputin the presence of uncertainties including the structuraluncertainty. In the paper entitled “Unknown input observerdesign for fuzzy bilinear system: an LMI approach” by D.Saoudi et al., a new method to design a Fuzzy BilinearObserver (FBO) with unknown inputs is developed for aclass of nonlinear systems. The nonlinear system is modeledas a fuzzy bilinear model (FBM). This kind of T-S fuzzymodel is especially suitable for a nonlinear system with abilinear term. The proposed fuzzy bilinear observer subjectto unknown inputs is developed to ensure the asymptoticconvergence of the error dynamic using the Lyapunovmethod. An unknown input fuzzy bilinear fault diagnosisobserver design is also proposed. Specifying for a class ofnonlinear systems described by Takagi-Sugeno (T-S) model,in the paper, entitled “A reduced-order TS fuzzy observerscheme with application to actuator faults reconstruction” byD. Krokavec and A. Filasova, is newly defined the reduced-order T-S fuzzy observer, and it is demonstrated that thematching requirement, under which it can be disposed toactuator faults estimation, can be reflected in the observerdesign stipulation. The stability conditions, relying on thefeasibility of an associated system of linearmatrix inequalities(LMI), are derived and guarantee that the observer schemeasymptotically estimates actuator faults. In terms of fuzzysystems, the article provides a suitable newmethodology andexpands the theoretical basis of TS fuzzy model applicationsin control system design.The paper entitled “Terminal slidingmode control using adaptive fuzzy-neural observer” by D. Xuet al. proposed a dynamic approximation algorithm whichis used to simplify the nonaffine nonlinear systems as affinenonlinear systems with time-varying parameters. And thetime-varying parameters can be obtained by a filter. Next,an adaptive fuzzy-neural observer is designed to estimatethe signals of position, velocity, and unknown functions.Terminal sliding mode control is used to design based onthe observer. Stability analysis and simulations can showthat the method is effective. The paper entitled “Filteringfor discrete fuzzy stochastic time-delay systems with sensorsaturation” by J. You et al. investigates the 𝐻

∞filtering

problem for T-S fuzzy systems with time varying delayand sensor saturation. The communication channel betweenthe plant and the filer is supposed to be imperfect, andrandom noise depending on the state and external distur-bance is taken into account. The key method employed tohandle with the time-varying delay is to develop the ScaledSmall Gain (SSG) theorem to the stochastic systems. Themain contribution is that this paper establishes a researchapproach that could handle with time varying delay andsensor saturation together, and both characteristics are alwaysinvolved in many theoretical and practical problems. Thepaper entitled “Robust stabilization for continuous Takagi-Sugeno fuzzy system based on observer design” by Y. Manaiand M. Benrejeb investigates the influence of new ParallelDistributed Controller (PDC) on the stabilization regionof continuous Takagi-Sugeno (T-S) fuzzy models. Using a

nonquadratic Lyapunov function, new sufficient stabilizationcriterion is established in terms of linear matrix inequality.The criterion examines the derivative membership function;an approach to determine state variables is given based onobserver design.

The applications of various control schemes have receivedconsiderable research interests in the past decades. In thework entitled “An iterative procedure for optimizing theperformance of the fuzzy-neural job cycle time estimationapproach in a wafer fabrication factory” by T. Chen and Y.Wang, a classifying fuzzy-neural approach, based on the com-bination of principal component analysis (PCA), fuzzy c-means (FCM), and back propagation network (BPN), isproposed to estimate the cycle time of a job in a waferfabrication factory. The paper entitled “Switched two-level𝐻∞

and robust fuzzy learning control of an overhead crane”by K. Hung et al. investigates the use of fuzzy techniques formodeling nonlinear plants as a combination of a nominallinear system and a T-S fuzzy blending of affine terms. Thistype of dynamic model significantly simplifies subsequentanalysis and control designs, because assumptions on theplant dynamics can be significantly reduced. In the paperentitled “A two-wheeled self-balancing robot with the fuzzy PDcontrol method” by J. Wu et al., the utility and effectiveness ofsoft computing approaches for a two-wheeled self-balancingrobot with structured and unstructured uncertainties arepresented. In this approach, precompensation of a hybridfuzzy PD controller is proposed.The control scheme consistsof a fuzzy logic-based precompensator followed by fuzzy PDcontrol. Moreover, a fuzzy supervisory controller is used tosupervise conventional proportional and derivative actions,such that the conventional gains are adapted online throughfuzzy reasoning. Due to the influence of nonlinear friction,creep phenomenon occurs when the moving speed is lowin the telescopic boom system of heavy-load transfer robot.To solve this problem and to improve control precision, B.You et al. in the paper entitled “Low-speed control of heavy-load transfer robot with long telescopic boom based on stribeckfriction model” built a three-loop control nonlinear modelof the system with the Stribeck friction disturbance modelto simulate the motion of the telescopic boom in low speed.Fuzzy PID control was used to solve the problem of “flat-top”position tracking and “dead-zone” speed tracking. The creepphenomenon was eliminated, and the tracking accuracy androbustness of the system were also improved.The paper enti-tled “Using metaheuristic and fuzzy system for optimizationof material-pull in a push pull flow logistics network” by A.Mehrsai et al. generally complies with a known problem inmanufacturing environment, which is the coordination ofheterogeneous material flows throughout supply chains andwithin every production plant. Alternative flows of material,following push and pull principles of control cause collectionof inventory and WIP of materials as well as lags in deliverytimes. Model-based control of material flows regarding theinterference of human in the entire process seems relativelyvery complex to practitioners in industries. In contrast, inthis paper some material flow strategies are recommendedto simplify and improve the flows throughout. Besides, someheuristics (i.e., genetic algorithm and simulated annealing)

Mathematical Problems in Engineering 5

to solve the flow coordination are experimented here as well.Fuzzy logic as a suitable solution for solving human centeredoperations is reasonably explained and experimented in twoapplications, that is, control of pallets within an assembly sys-tem as well as normalization of multiobjective optimizationproblem. In the paper entitled “A novel evaluation model forhybrid power system based on vague set and dempster-shaferevidence theory” by D. Niu et al., due to advantages of vagueset processing abundant uncertain and fuzzy information, itis chosen to determine basic decision matrix of evaluationmodel. Combining vague set with D-S evidence theory, anovel evaluation algorithm is established and applied into thecomprehensive benefit evaluation of hybrid power system. Inthe paper entitled “𝐻

∞fuzzy control of DC-DC converters

with input constraint,” D. Saifia et al. study fuzzy controlof DC-DC converters under actuator saturation. Becauselinear control design methods do not take into account thenonlinearity of the system, a T-S fuzzy models and a con-troller design approach are used. The input constraint is firsttransformed into a symmetric saturationwhich is representedby a polytopic model. Stabilization conditions for the 𝐻

∞

state feedback system of DC-DC converters under actuatorsaturation are established using the Lyapunov approach. Inthe paper entitled “A compound fuzzy disturbance observerbased on sliding modes and its application on flight simulator,”Y. Wu et al. present a compound fuzzy disturbance observerbased on sliding modes. The proposed method improvesthe performance of the disturbance inhibition when thereexists huge modeling mismatch. Traditional methods usehigh-gain control, which may cause resonance in controllingelastic electromechanical systems, to inhibit equivalent dis-turbance. The proposed method employs fuzzy tools to dealwith the primary part of the disturbance, and the residualdisturbance is compensated by sliding mode control. Theproposed method improves the robustness and performanceof the system while avoiding the disadvantages of traditionalmethods. Finally, the paper entitled “Fuzzy formation controland collision avoidance for multiagent systems” by Y. Changet al. investigates the formation control of leader-followermultiagent systems, where the problem of collision avoidanceis considered. Based on the graph-theoretic concepts andlocally distributed information, a neural fuzzy formationcontroller is designed with the capability of online learning.The learning rules of controller parameters can be derivedfrom the gradient descent method. To avoid collisionsbetween neighboring agents, a fuzzy separation controlleris proposed such that the local minimum problem can besolved.

Appendix

A. Accepted Papers According toClassified Topics

A.1. Papers on the Topic of Stability

(1) Delay-dependent Stability Analysis of UncertainFuzzy Systems with State and Input Delays underImperfect Premise Matching.

(2) Stability Analysis and Stabilization of T-S FuzzyDelta Operator Systems with Time-Varying Delay viaan Input-Output Approach.

A.2. Papers on the Topic of Modeling/Identification

(3) A Novel Identification Method for GeneralizedT-S Fuzzy Systems.(4) Approximate analytic and numerical solutions toLane-Emden equation via fuzzy modeling method.(5) Bi-objective Optimization Method and Applica-tion of Mechanism Design Based on Pigs’ PayoffGame Behavior.(6) Fuzzy investment portfolio selection modelsbased on interval analysis approach.(7) On interval valued supra fuzzy syntopogenousstructure.

A.3. Papers on the Topic of Control for Fuzzy Systems

(8) Fuzzy Sliding Mode Controller Design UsingTakagi-Sugeno modelled Nonlinear Systems.(9) Fuzzy variable structure control for uncertainsystems with disturbance.(10) Robust 𝐻

∞Control for A Class of Uncertain

Switched Fuzzy Time-Delay Systems based on T-SModels.(11) Direct Adaptive Fuzzy SlidingMode Control withVariable Universe Fuzzy Switching Term for a class ofMIMO Nonlinear Systems.(12) A Fuzzy Approach to Robust Control of Stochas-tic Non-Affine Nonlinear Systems.(13) Adaptive Fuzzy Tracking Control for UncertainNonlinear Time-Delay SystemswithUnknownDead-Zone Input.(14) Fuzzy PDControl of Networked Control SystemsBased on CMAC Neural Network.(15) Fuzzy Control and Connected Region MarkingAlgorithm-based SEM Nanomanipulation.

A.4. Papers on the Topic of Observer/Filter Design for Com-plex Systems

(16) Robust Observer Design for Takagi-SugenoFuzzy Systems with Mixed Neutral and Discretedelays and Unknown Inputs.(17) Observer-based Robust Adaptive Fuzzy Con-trol for MIMO Nonlinear Uncertain Systems withDelayed Output.

(18) Unknown Input Observer Design for FuzzyBilinear System: an LMI Approach.(19) A reduced-order TS fuzzy observer scheme withapplication to actuator faults reconstruction.


(20) Terminal Sliding Mode Control using AdaptiveFuzzy-Neural Observer.(21) Filtering for Discrete Fuzzy Stochastic Time-Delay Systems with Sensor Saturation.(22) Robust Stabilization for Continuous Takagi-Sugeno Fuzzy System based on Observer Design.

A.5. Papers on the Topic of Applications

(23) An Iterative Procedure for Optimizing the Per-formance of the Fuzzy-neural Job Cycle Time Estima-tion Approach in a Wafer Fabrication Factory.

(24) Switched Two-Level𝐻∞

and Robust Fuzzy Lea-rning Control of an Overhead Crane.(25) A Two-Wheeled Self-Balancing Robot with theFuzzy PD Control Method.(26) Low-Speed Control of Heavy-Load TransferRobot with Long Telescopic Boom Based on StribeckFriction Model.(27) Using Meta-Heuristic and Fuzzy System forOptimization of Material-Pull In A Push-Pull FlowLogistics Network.(28) A Novel Evaluation Model for Hybrid PowerSystem Based on Vague Set and Dempster-ShaferEvidenceTheory.

(29) 𝐻∞

Fuzzy Control of DC-DC Converters withInput Constraint.(30)ACompoundFuzzyDisturbanceObserver basedon Sliding Modes and Its Application on FlightSimulator.

(31) Fuzzy Formation Control and Collision Avoid-ance for Multi-Agent Systems.

Acknowledgments

The guest editors would like to thank all the authors of thisspecial issue for contributing the high quality papers, and wehope the reader will share our joy and find this special issuevery useful.We are also very grateful to the reviewers for theirefforts in reviewing the papers on time.

Hamid Reza KarimiMohammed Chadli

Peng Shi

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Editorial New Developments in Mathematical Control and …downloads.hindawi.com/journals/mpe/2013/126878.pdf · 2019-07-31 · New Developments in Mathematical Control and Information