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adaptive systems THEORY: SOME BASIC CONCEPTS, METHODS AND RESULTS

Journal of systems Science & Complexity 2003年第3期16卷 293-306页

作者： QUO Lei(Institute of systems Science, Academy of Mathematics and systems Sciences, Chinese Academy of Sciences, Beijing 100080, China) Institute of systems Science Academy of Mathematics and Systems Sciences Chinese Academy of Sciences 北京 100080

The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.

关键词： adaptive systems estimation control uncertainty stochastic systems stability

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Online adaptive Approximate Optimal Tracking Control with Simplified Dual Approximation Structure for Continuous-time Unknown Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2014年第4期1卷 412-422页

作者： Jing Na Guido Herrmann the Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology the Department of Mechanical Engineering University of Bristol

This paper proposes an online adaptive approximate solution for the infinite-horizon optimal tracking control problem of continuous-time nonlinear systems with unknown *** requirement of the complete knowledge of system dynamics is avoided by employing an adaptive identifier in conjunction with a novel adaptive law, such that the estimated identifier weights converge to a small neighborhood of their ideal *** adaptive steady-state controller is developed to maintain the desired tracking performance at the steady-state, and an adaptive optimal controller is designed to stabilize the tracking error dynamics in an optimal manner. For this purpose, a critic neural network(NN) is utilized to approximate the optimal value function of the Hamilton-Jacobi-Bellman(HJB) equation,which is used in the construction of the optimal controller. The learning of two NNs, i.e., the identifier NN and the critic NN, is continuous and simultaneous by means of a novel adaptive law design methodology based on the parameter estimation *** of the whole system consisting of the identifier NN,the critic NN and the optimal tracking control is guaranteed using Lyapunov theory; convergence to a near-optimal control law is proved. Simulation results exemplify the effectiveness of the proposed method.

关键词： Optimal control Artificial neural networks Convergence adaptive systems Approximation methods Parameter estimation Steady-state Learning (artificial intelligence) adaptive control

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adaptive Iterative Learning Control for a Class of Nonlinear Time-varying systems with Unknown Delays and Input Dead-zone

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IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 302-314页

作者： Jianming Wei Yunan Hu Meimei Sun the Department of Control Engineering Naval Aeronautical Engineering Institute

This paper presents an adaptive iterative learning control(AILC) scheme for a class of nonlinear systems with unknown time-varying delays and unknown input dead-zone.A novel nonlinear form of dead-zone nonlinearity is *** assumption of identical initial condition for iterative learning control(ILC) is removed by introducing boundary layer *** uncertainties with time-varying delays are compensated for by using appropriate Lyapunov-Krasovskii functional and Young’s *** basis function neural networks are used to model the time-varying *** hyperbolic tangent function is employed to avoid the problem of *** to the property of hyperbolic tangent function,the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function(CEF) in two cases,while keeping all the closedloop signals ***,a simulation example is presented to verify the effectiveness of the proposed approach.

关键词： Time-varying systems Delays adaptive systems Learning (artificial intelligence) Nonlinear systems Trajectory Iterative methods

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The Investigation of Data Voting Algorithm for Train Air-Braking System Based on Multi-Classification SVM and ANFIS

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Chinese Journal of Electronics 2024年第1期33卷 274-281页

作者： Juhan WANG Ying GAO Yuan CAO Tao TANG School of Electronics and Information Engineering Beijing Jiaotong University Graduate Department China Academy of Railway Science National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

The pressure data of the train air braking system is of great significance to accurately evaluate its operation state. In order to overcome the influence of sensor fault on the pressure data of train air braking system, it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault, the system can accurately identify and locate the position of the faulty sensor, and estimate the fault data according to other normal data. A fault-tolerant mechanism based on multi-classification support vector machine(SVM) and adaptive network-based fuzzy inference system(ANFIS) is introduced. Multi-classification SVM is used to identify and locate the system fault state, and ANFIS is used to estimate the real data of the fault sensor. After estimation, the system will compare the real data of the fault sensor with the ANFIS estimated data. If it is similar,the system will recognize that there is a false alarm and record it. Then the paper tests the whole mechanism based on the real data. The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.

关键词： Support vector machines Fault diagnosis Pressure sensors Fuzzy logic Fault tolerance adaptive systems Fault tolerant systems

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Distributed adaptive Resource Allocation:An Uncertain Saddle-Point Dynamics Viewpoint

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2209-2221页

作者： Dongdong Yue Simone Baldi Jinde Cao Qi Li Bart De Schutter the School of Mathematics Southeast UniversityNanjing 210096China IEEE the Yonsei Frontier Laboratory Yonsei UniversitySeoul 03722South Korea the School of Automation Southeast UniversityNanjing 210096China the Delft Center for systems and Control Delft University of TechnologyDelft 2628 CDThe Netherlands

This paper addresses distributed adaptive optimal resource allocation problems over weight-balanced *** leveraging state-of-the-art adaptive coupling designs for multiagent systems,two adaptive algorithms are proposed,namely a directed-spanning-tree-based algorithm and a node-based *** benefits of these algorithms are that they require neither sufficiently small or unitary step sizes,nor global knowledge of Laplacian eigenvalues,which are widely required in the *** is shown that both algorithms belong to a class of uncertain saddle-point dynamics,which can be tackled by repeatedly adopting the Peter-Paul inequality in the framework of Lyapunov *** to this new viewpoint,global asymptotic convergence of both algorithms can be proven in a unified *** effectiveness of the proposed algorithms is validated through numerical simulations and case studies in IEEE 30-bus and 118-bus power systems.

关键词： adaptive systems directed graphs resource alloca-tion saddle-point dynamics

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Design of a large-scale model for wind tunnel test of a multiadaptive flap concept

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Chinese Journal of Aeronautics 2024年第2期37卷 58-80页

作者： Mürüvvet Sinem SICIM DEMIRCI Rosario PECORA Metin Orhan KAYA Aeronautical Engineering Department Istanbul Technical UniversityIstanbulTurkey Industrial Engineering Department University of Naples Federico IINapoliItaly

The design and application of morphing systems are ongoing issues compelling the aviation *** Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation *** primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly *** ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic *** the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft *** flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight ***,during the cruise,the tip of the flap is deflected for load control and induced drag *** manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft *** the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape ***,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale *** strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic ***,

关键词： Morphing structures Smart aircraft Morphing flap adaptive systems Finger-like ribs Wind tunnel tests Large-scale morphing archi-tectures Variable camber airfoil

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Multi-Sensor Fusion adaptive Estimation for Nonlinear Under-observed System with Multiplicative Noise

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Chinese Journal of Electronics 2024年第1期33卷 282-292页

作者： Yongpeng CUI Xiaojun SUN School of Electronic Engineering Heilongjiang University Key Laboratory of Information Fusion Estimation and Detection

The adaptive fusion estimation problem was studied for the multi-sensor nonlinear under-observed systems with multiplicative noise. A one-step predictor with state update equations was designed for the virtual state with virtual noise first of all. An extended incremental Kalman filter(EIKF) was then proposed for the nonlinear under-observed systems. Furthermore, an adaptive filtering method was given for optimization. The fusion adaptive incremental Kalman filter weighted by scalar was finally proposed. The comparison analysis was made to verify the optimization of the state estimation using adaptive filtering method in the filtering process.

关键词： adaptive systems Information filters Matrices adaptive estimation Kalman filters State estimation Nonlinear systems

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A formal model for plastic human computer interfaces

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Frontiers of Computer Science 2018年第2期12卷 351-375页

作者： Abdelkrim CHEBIEB Yamine AIT AMEUR Computer Science School for Engineers (ESI) Algiers 16270 Algeria IRIT-INPT-ENSEEIHT Toulouse 31071 France

The considerable and significant progress achieved in the design and development of new interaction devices between man and machine has enabled the emergence of various powerful and efficient input and/or output devices. Each of these new devices brings specific interaction modes. With the emergence of these devices, new interaction techniques and modes arise and new interaction capabilities are offered. New user interfaces need to be designed or former ones need to evolve. The design of so called plastic user interfaces contributes to handling such evolutions. The key requirement for the design of such a user interface is that the new obtained user interface shall be adapted to the application and have, at least, the same behavior as the previous （adapted） one. This paper proposes to address the problem of user interface evolution due to the introduction of new interaction devices and/or new interaction modes. More, precisely, we are interested by the study of the design process of a user interface resulting from the evolution of a former user interface due to the introduction of new devices and/or new interaction capabilities. We consider that interface behaviors are described by labelled transition systems and comparison between user interfaces is handled by an extended definition of the bi-simulation relationship to compare user interface behaviors when interaction modes are replaced by new ones.

关键词： formal modeling and verification ontology based modeling plastic user interfaces adaptive systems

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Optimal fusion‐based localization method for tracking of smartphone user in tall complex buildings

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1104-1123页

作者： Harun Jamil Do‐Hyeun Kim Department of Electronics Engineering Jeju National UniversityJeju‐SiRepublic of Korea Department of Computer Engineering Jeju National UniversityJeju‐SiRepublic of Korea

In the event of a fire breaking out or in other complicated situations,a mobile computing solution combining the Internet of Things and wearable devices can actually assist tracking solutions for rescuing and evacuating people in multistory ***,it is crucial to increase the positioning technology's *** sequential Monte Carlo(SMC)approach is used in various applications such as target tracking and intelligent surveillance,which rely on smartphone‐based inertial data ***,the SMC method has intrinsic flaws,such as sample impoverishment and particle degeneracy.A novel SMC approach is presented,which is built on the weighted differential evolution(WDE)*** Monte Carlo approaches start with random particle placements and arrives at the desired distribution with a slower variance reduction,like in a high‐dimensional space,such as a multistory *** differential evolution is included before the resampling procedure to guarantee the appropriate variety of the particle set,prevent the usage of an inadequate number of valid samples,and preserve smartphone user position *** values of the smartphone‐based sensors and BLE‐beacons are set as input to the SMC,which aids in fast approximating the posterior distributions,to speed up the particle congregation process in the proposed SMC‐based WDE ***,the robustness and efficacy of the suggested technique more accurately reflect the actual situation of smartphone *** to simulation findings,the suggested approach provides improved location estimation with reduced localization error and quick *** results confirm that the proposed optimal fusion‐based SMC‐WDE scheme performs 9.92%better in terms of MAPE,15.24%for the case of MAE,and 0.031%when evaluating based on the R2 Score.

关键词： 2‐D adaptive intelligent systems adaptive systems artificial immune system artificial intelligence techniques

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Solving function optimization problems with the immune principle

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Journal of systems Engineering and Electronics 2004年第4期15卷 702-709页

作者： ZuoXingquan LiShiyong DepartmentofControlScienceandEngineering HarbinInstituteofTechnologyHarbin150001P.R.China

adaptive immune evolutionary algorithm is proposed based on the principle of adaptive immune response. Two new algorithm parameters of expansion radius and mutation radius are defined to construct a small neighborhood and a large neighborhood, then expansion and mutation operations are designed to search the local and global regions of solution space simultaneously by using the two neighborhoods, thus, two-level neighborhood search mechanism is realized. The degree of the diversity in the population is described with the average Euclidean distance among all individuals, and it is used to adjust algorithm parameters adaptively to accelerate convergence and avoid getting stuck at local optima. The algorithm is proved to be convergent and its optimization principle is analyzed. The experiment results of multi-modal function optimization show that the algorithm is effective.

关键词： Immune system Optimization Algorithm design and analysis Genetic algorithms adaptive systems Next generation networking Convergence

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