Separation principle for quasi‐one‐sided Lipschitz nonlinear systems with time delay

In this article, we address the problem of output stabilization for a class of nonlinear time‐delay systems. First, an observer is designed for estimating the state of nonlinear time‐delay systems by means of quasi‐one‐sided Lipschitz condition, which is less conservative than the one‐sided Lipschitz condition. Then, a state feedback controller is designed to stabilize the nonlinear systems in terms of weak quasi‐one‐sided Lipschitz condition. Furthermore, it is shown that the separation principle holds for stabilization of the systems based on the observer‐based controller. Under the quasi‐one‐sided Lipschitz condition, state observer and feedback controller can be designed separately even though the parameter (A,C) of nonlinear time‐delay systems is not detectable and parameter (A,B) is not stabilizable. Finally, a numerical example is provided to verify the efficiency of the main results.     

Cluster validation in clustering‐based one‐class classification

Reconstruction‐based one‐class classification has shown to be very effective in a number of domains. This approach works by attempting to capture the underlying structure of the normal class, typically, by means of clusters of objects. It has the main disadvantage, however, that one has to indicate the number of clusters in advance, for this yields an efficient way of computing a clustering. In this paper, we introduce a new algorithm, OCKRA++, which achieves a better performance, by enhancing a clustering‐based one‐class ensemble classifier (OCKRA) with a cluster validity index that is used to set the best number of clusters during the classifier's training process. We have thoroughly tested OCKRA++ in a particular domain, namely masquerade detection. For this purpose, we have used the Windows‐Users and ‐Intruder simulation Logs data set repository, which contains 70 different masquerade data sets. We have found that OCKRA++ is currently the algorithm that achieves the best area under the curve, with a significant difference, in masquerade detection using the file system navigation approach.     

Closed‐loop one‐way‐travel‐time navigation using low‐grade odometry for autonomous underwater vehicles

This paper extends the progress of single beacon one‐way‐travel‐time (OWTT) range measurements for constraining XY position for autonomous underwater vehicles (AUV). Traditional navigation algorithms have used OWTT measurements to constrain an inertial navigation system aided by a Doppler Velocity Log (DVL). These methodologies limit AUV applications to where DVL bottom‐lock is available as well as the necessity for expensive strap‐down sensors, such as the DVL. Thus, deep water, mid‐water column research has mostly been left untouched, and vehicles that need expensive strap‐down sensors restrict the possibility of using multiple AUVs to explore a certain area. This work presents a solution for accurate navigation and localization using a vehicle's odometry determined by its dynamic model velocity and constrained by OWTT range measurements from a topside source beacon as well as other AUVs operating in proximity. We present a comparison of two navigation algorithms: an Extended Kalman Filter (EKF) and a Particle Filter(PF). Both of these algorithms also incorporate a water velocity bias estimator that further enhances the navigation accuracy and localization. Closed‐loop online field results on local waters as well as a real‐time implementation of two days field trials operating in Monterey Bay, California during the Keck Institute for Space Studies oceanographic research project prove the accuracy of this methodology with a root mean square error on the order of tens of meters compared to GPS position over a distance traveled of multiple kilometers.     

A one‐step leapfrog HIE‐FDTD method for rotationally symmetric structures

In this work, they propose a one‐step leapfrog hybrid implicit‐explicit finite‐difference time‐domain (HIE‐FDTD) method for body‐of‐revolution (BOR). Meanwhile, its Convolutional Perfect Matched Layer (CPML) absorbing boundary condition is implemented. In this method, the implicit difference is applied in the angular direction. All the resultant updating equations are still explicit. However, the stability condition of the proposed method is relaxed. The analytical analysis shows that its time step is only determined by the smaller one of spatial increments Δρ and Δz. A scattering example is provided to demonstrate the new algorithm. At the same time, the relative of reflection error of the CPML is given with comparisons of Mur.     

Consensus in multi‐agent systems with communication constraints

The problem of second‐order consensus is investigated in this paper for a class of multi‐agent systems with a fixed directed topology and communication constraints where each agent is assumed to share information only with its neighbors on some disconnected time intervals. A novel consensus protocol designed based on synchronous intermittent local information feedback is proposed to coordinate the states of agents to converge to second‐order consensus under a fixed strongly connected topology, which is then extended to the case where the communication topology contains a directed spanning tree. By using tools from algebraic graph theory and Lyapunov control approach, it is proved that second‐order consensus can be reached if the general algebraic connectivity of the communication topology is larger than a threshold value and the mobile agents communicate with their neighbors frequently enough as the network evolves. Finally, a numerical example is simulated to verify the theoretical analysis. Copyright © 2011 John Wiley & Sons, Ltd.     

SwingStates: adding state machines to Java and the Swing toolkit

This article describes SwingStates, a Java toolkit designed to facilitate the development of graphical user interfaces and bring advanced interaction techniques to the Java platform. SwingStates is based on the use of finite‐state machines specified directly in Java to describe the behavior of interactive systems. State machines can be used to redefine the behavior of existing Swing widgets or, in combination with a new canvas widget that features a rich graphical model, to create brand new widgets. SwingStates also supports arbitrary input devices to implement novel interaction techniques based, for example, on bi‐manual or pressure‐sensitive input. We have used SwingStates in several Master's‐level classes over the past two years and have developed a benchmark approach to evaluate the toolkit in this context. The results demonstrate that SwingStates can be used by non‐expert developers with little training to successfully implement advanced interaction techniques. Copyright © 2007 John Wiley & Sons, Ltd.     

D‐type iterative learning control for one‐sided Lipschitz nonlinear systems

In this paper, the problem of iterative learning control for a class of nonlinear systems is studied. Here, the nonlinear functions satisfy the one‐sided Lipschitz and quadratically inner‐bounded conditions. For such nonlinear systems, open‐loop and closed‐loop D‐type learning algorithms are adopted, respectively, and furthermore, the convergence conditions of the D‐type learning algorithms are established. It is shown that both algorithms can ensure that the system output converges to the desired trajectory on the whole time interval. Finally, the validity of the presented D‐type learning algorithms is verified by a numerical example.     

Robust observer design for uncertain one‐sided Lipschitz systems with disturbances

In this paper, we study the robust observer design problem for a class of uncertain one‐sided Lipschitz systems with disturbances. Not only the system matrices but also the nonlinear functions are assumed to be uncertain. The nominal models of nonlinearities are assumed to satisfy both the one‐sided Lipschitz condition and the quadratically inner‐bounded condition. By utilizing a novel approach, our observer designs are robust against unknown nonlinear uncertainties and system and measurement noises. The new approach also relaxes some conservativeness in related existing results, ie, less conservative observer design conditions are obtained. Furthermore, the problem of designing reduced‐order observers is considered in case the output measurement is not subject to uncertainty and disturbance. Two examples are provided to show the efficiency and advantages of our results over existing works.     

Robust adaptive control for a class of semi‐strict feedback systems with state and input constraints

This paper proposes a dynamic surface control (DSC)–based robust adaptive control scheme for a class of semi‐strict feedback systems with full‐state and input constraints. In the control scheme, a constraint transformation method is employed to prevent the transgression of the full‐state constraints. Specifically, the state constraints are firstly represented as the surface error constraints, then, an error transformation is introduced to convert the constrained surface errors into new equivalent variables without constraints. By ensuring the boundedness of the transformed variables, the violation of the state constraints can be prevented. Moreover, in order to obtain magnitude limited virtual control signal for the recursive design, the saturations are incorporated into the control law. The auxiliary design systems are constructed to analyze the effects of the introduced saturations and the input constraints. Rigorous theoretical analysis demonstrates that the proposed control law can guarantee all the closed‐loop signals are uniformly ultimately bounded, the tracking error converges to a small neighborhood of origin, and the full‐state constraints are not violated. Compared with the existing results, the key advantages of the proposed control scheme include: (i) the utilization of the constraint transformation can handle both time‐varying symmetric and asymmetric state constraints and static ones in a unified framework; (ii) the incorporation of the saturations permits the removal of a feasibility analysis step and avoids solving the constrained optimization problem; and (iii) the “explosion of complexity” in traditional backstepping design is avoided by using the DSC technique. Simulations are finally given to confirm the effectiveness of the proposed approach.     

Nonlinear observer design for one‐sided Lipschitz systems with time‐varying delay and uncertainties

This paper investigates the problem of state observer design for a class of nonlinear uncertain dynamical systems with interval time‐varying delay and the one‐sided Lipschitz condition. By constructing the novel Lyapunov–Krasovskii functional while utilizing the free‐weighting matrices approach, the one‐sided Lipschitz condition and the quadratic inner‐bounded condition, novel sufficient conditions, which guarantee the observer error converge asymptotically to zero, are established for a class of nonlinear dynamical systems with interval time‐varying delay in terms of the linear matrix inequalities. The computing method for observer gain matrix is given. Finally, two examples illustrate the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.     

DSVD‐autoencoder: A scalable distributed privacy‐preserving method for one‐class classification

One‐class classification has gained interest as a solution to certain kinds of problems typical in a wide variety of real environments like anomaly or novelty detection. Autoencoder is the type of neural network that has been widely applied in these one‐class problems. In the Big Data era, new challenges have arisen, mainly related with the data volume. Another main concern derives from Privacy issues when data is distributed and cannot be shared among locations. These two conditions make many of the classic and brilliant methods not applicable. In this paper, we present distributed singular value decomposition (DSVD‐autoencoder), a method for autoencoders that allows learning in distributed scenarios without sharing raw data. Additionally, to guarantee privacy, it is noniterative and hyperparameter‐free, two interesting characteristics when dealing with Big Data. In comparison with the state of the art, results demonstrate that DSVD‐autoencoder provides a highly competitive solution to deal with very large data sets by reducing training from several hours to seconds while maintaining good accuracy.     

Applications of anisotropic one‐step leapfrog HIE‐FDTD method in microwave circuit and antenna

To verify the effect of artificial anisotropy parameters in one‐step leapfrog hybrid implicit‐explicit finite‐difference time‐domain (FDTD) method, we calculated several microwave components with different characteristics. Introduced auxiliary field variable can reduce the program difficulty and improve the computational efficiency without additional computational time and memory cost. Analyses of the numerical results are proved that the calculation time is reduced to about one‐sixth compared to the traditional FDTD method for the same example simulated. The memory cost and relative error are remained at a good level. The numerical experiments for microwave circuit and antenna have been well demonstrated the method available.     

Adaptive fault‐tolerant control of an axially moving system with time‐varying constraints

In this paper, for an axially moving system, with the purpose of suppressing vibration, an adaptive fault‐tolerant control method with time‐varying constraints is investigated. The dynamics of the system are comprised of an ordinary differential equation coupled with a partial differential equation. The method used in our study is known as fault‐tolerant control to process affairs of actuator failures occur. Actual control substitutes for ideal control to regulate the vibration when the actuator occurs undesired failures. Time‐varying constraints are appropriate to cope with the variation range of the performance. Lyapunov function has proven that the adaptive control law is feasible, as well as verifying the exponential stability of the system. Eventually, simulations we have done suggest that the effectiveness of the designed control is feasible.     

Guaranteed‐cost fuzzy controller design for a self‐sustaining bicycle with practical constraints

This study presents a guaranteed‐cost fuzzy controller for a self‐sustaining bicycle. First, the nonlinear dynamics of the bicycle are exactly transformed into a T‐S fuzzy system with model uncertainty. The guaranteed‐cost fuzzy controller is then designed for the transformed T‐S fuzzy system. For practical considerations, the input/state constraints are also satisfied in the design. The main contribution of this study is the guaranteed‐cost control design for a T‐S fuzzy system with model uncertainty and input/state constraints. Finally, simulation results show the validity of the proposed controller design method. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Automating maintenance for a one‐way transmitting blackboard system used for autonomous multi‐tier control

The blackboard architecture has particular utility in applications where conclusions must be drawn in the absence of human involvement. Through properly crafted rules, this approach can determine what a collection of data may mean. This can be utilized by other onboard software to limit transmission to only relevant data or conclusions. Some applications, such as robotic exploration, may preclude or severely limit the availability of controller‐to‐craft‐agent communications. In this case, the maintenance of the system must be performed autonomously.This paper discusses common maintenance tasks that may be relevant to a long‐running blackboard‐based system (e.g. clearing extraneous data from the blackboard regularly to improve performance, archiving relevant but infrequently used data for performance enhancement). A system for automating these tasks is presented that is suitable for most blackboard‐style systems. Its particular utility to those that cannot be easily accessed is discussed. Quantitative analysis of the value of removing rules from the system is performed and presented, and these results are extrapolated to several prospective blackboard maintenance approaches.     

CGLIB—a constraint‐based graphics library

CGLIB is a high‐level graphics library for B‐Prolog, a constraint logic programming system. The library provides primitives for creating and manipulating graphical objects and a set of constraints including not‐overlap, grid, table and tree constraints that facilitate the specification of the layouts of objects. The library adopts a construct called action rules which is available in B‐Prolog for creating agents and programming interactions among agents or between agents and the user. The library is a fully working system implemented in B‐Prolog, Java and C. It can be used in many areas such as drawing editors, interactive user interfaces, document authoring, animation, information visualization, intelligent agents and games. The high‐level abstraction of the library and the use of constraints and action rules in the specification of layouts and behaviors can significantly enhance the productivity of the development of graphics. We demonstrate through several examples the effectiveness of the library as a tool for developing graphics‐rich and interactive user interfaces. Copyright © 2003 John Wiley & Sons, Ltd.     

Semi‐global stabilization of discrete‐time systems subject to non‐right invertible constraints

This paper investigates time‐invariant linear systems subject to input and state constraints. We study discrete‐time systems with full or partial constraints on both input and state. It has been shown earlier that the solvability conditions of stabilization problems are closely related to important concepts such as the right invertibility or non‐right invertibility of the constraints, the location of constraint invariant zeros, and the order of constraint infinite zeros. In this paper, for general time‐invariant linear systems with non‐right invertible constraints, necessary and sufficient conditions are developed under which semi‐global stabilization in the admissible set can be achieved by state feedback. Sufficient conditions are also developed for such a stabilization in the case where measurement feedback is used. Such sufficient conditions are almost necessary. Controllers for both state feedback and measurement feedback are constructed as well. Copyright © 2009 John Wiley & Sons, Ltd.     

Data‐driven optimal event‐triggered consensus control for unknown nonlinear multiagent systems with control constraints

This paper considers optimal consensus control problem for unknown nonlinear multiagent systems (MASs) subjected to control constraints by utilizing event‐triggered adaptive dynamic programming (ETADP) technique. To deal with the control constraints, we introduce nonquadratic energy consumption functions into performance indices and formulate the Hamilton‐Jacobi‐Bellman (HJB) equations. Then, based on the Bellman's optimality principle, constrained optimal consensus control policies are designed from the HJB equations. In order to implement the ETADP algorithm, the critic networks and action networks are developed to approximate the value functions and consensus control policies respectively based on the measurable system data. Under the event‐triggered control framework, the weights of the critic networks and action networks are only updated at the triggering instants which are decided by the designed adaptive triggered conditions. The Lyapunov method is used to prove that the local neighbor consensus errors and the weight estimation errors of the critic networks and action networks are ultimately bounded. Finally, a numerical example is provided to show the effectiveness of the proposed ETADP method.     

Nonlinear H∞ observer design for one‐sided Lipschitz discrete‐time singular systems with time‐varying delay

This paper investigates the H_∞ observer design problem for a class of nonlinear discrete‐time singular systems with time‐varying delays and disturbance inputs. The nonlinear systems can be rectangular and the nonlinearities satisfy the one‐sided Lipschitz condition and quadratically inner‐bounded condition, which are more general than the traditional Lipschitz condition. By appropriately dealing with these two conditions and applying several important inequalities, a linear matrix inequality–based approach for the nonlinear observer design is proposed. The resulting nonlinear H_∞ observer guarantees asymptotic stability of the estimation error dynamics with a prescribed performance γ. The synthesis condition of H_∞ observer design for nonlinear discrete‐time singular systems without time delays is also presented. The design is first addressed for one‐sided Lipschitz discrete‐time singular systems. Finally, two numerical examples are given to show the effectiveness of the present approach.     

A coordinating approach for the solution of discrete linear servo‐mechanism problems with constraints

A discrete‐time linear servo‐mechanism problem with system constraints is considered. An approach is developed to solve such a problem using an idea borrowed from large‐scale systems theory, in which a coordinating variable is introduced and used to satisfy state constraints. Under the assumption that the system is stabilizable and has a feasible solution, it is shown that the proposed procedure leads to the optimal solution while satisfying system constraints. A convergence analysis of the algorithm is undertaken and illustrative examples are provided to show the performance of the proposed algorithm. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society