Automatic Virtual Entity Simulation of Conceptual Design Results Part I： Symbolic Scheme Generation and Identification

The development of new products of high quality, low unit cost, and short lead time to market are the key elements required for any enterprise to obtain a competitive advantage. For shorting the lead time to market and improving the creativity and performances of the product, a rule-based conceptual design approach and a methodology to simulate the conceptual design results generated in conceptual design process in automatical virtual entity form are presented in this paper. This part of paper presents a rule-based conceptual design method for generating creative conceptual design schemes of mechanisms based on Yan＇s kinematic chain regeneration creative design method. The design rules are adopted to describe the design requirements of the functional characteristics, the connection relationships and topological characteristics among mechanisms. Through the graphs-based reasoning process, the conceptual design space is expanded extremely, and the potential creative conceptual design results are then dug out. By refining the design rules, the solution exploration problem is avioded, and the tendentious conceptual design schemes are generated. Since mechanical, electrical and hydraulic subsystems can be transformed into general mechansims, the conceptual design method presented in this paper can also be applied in the conceptual design problem of complex mechatronic systems. And then the method to identify conceptual design schemes is given.     

An Approach to Representation for Principle Scheme Design

One of the open issues in principle scheme design of mechanical systems is principle representation, which not only outlines the physical principles, but also facilitates the design synthesis. An energy-based approach to represent principle scheme design is proposed. Firstly, an energy interaction model of mechanical systems is established and an intermediate model is derived, in which principle scheme design is transformed into solving the energy functions of system. Then the energy functions are modeled with the language of bond graphs, and principle representation for components is presented. Finally, characteristics of the developed representation approach are analyzed and a design example of gate drive system is given to demonstrate this approach.     

Application of Hopfield Neural Networks Approach in Solar Energy Product Conceptual Design简

A new product conceptual design approach is put forward based on Hopfield neural networks models. By research on the mechanisms of Hopfield neural networks, the associative simulation approaches are proposed. The approach is given by Hebb learn- ing law, Hopfield neural networks and crossover and mutation. The calculating models and the calculating formulas for the concep- tual design are put forward. Finally, an example for the conceptual design of a solar energy lamp is given. The better results are ob- tained in the conceptual design.     

An Image-Based Virtual Reality Prototype System

The most important goal of virtual reality is to create a virtual world computers where users are allowed to view the environment and control the virtual objects interactively.Traditionally,virtual reality systems use 3D computer graphics to model and render a virtual environment in real time.However,this approach usually requires laborious modeling and expensive special-purpose rendering hardware.Image-based rendering is a new approach in composing a virtual environment in which a set of panoramic images is used to compose the virtual environment and walking in the space is accomplished by “hopping”to different panoramic points.This paper introduces an experimental image-based VR system.The techniques utilized in the system,in particular the authoring and interactive control tools of the system,are described in detail.     

A loop-based apparatus for at-speed self-testing

At-speed testing using external tester requires an expensive equipment,thus built-in self-test(BIST) is an alternative technique due to its ability to perform on-chip at-speed self-testing.The main issue in BIST for at-speed testing is to obtain high delay fault coverage with a low hardware overhead.This paper presents an improved loop-based BIST scheme,in which a configurable MISR (multiple-input signature register)is used to generate test-pair sequences.The structure and operation modes of the BIST scheme are described.The topological properties of the state-transition-graph of the proposed BIST scheme are analyzed.Based on it ,an approach to design and efficiently implement the proposed BIST scheme is developed.Experimental results on academic benchmark circuits are presented to demonstrate the effectiveness of the proposed BIST scheme as well as the design approach.     

A Domain Knowledge Driven Approach for User Interface Software Development

A domain knowledge driven user interface development approach is described.As a conceptual design of the user interface,the domain knowledge defines the user interface in terms of objects,actions and their relationships that the user would use to interact with the application system.It also serves as input to a user interface management system (UIMS) and is the kernel of the target user interface.The principal ideas and the implementation techniques of the approach is discussed.The user interface model,user interface designer oriented high-level specification notatiopn,and the transformation algorithms on domain knowledge are presented.     

A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control

Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parametermodel-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.     

A new dynamical evolutionary algorithm based on statistical mechanics

In this paper,a new dynamical evolutionary algorithm(DEA) is presented based on the theory of statistical mechanics.The novelty of this kind of dynamical evolutionary algorithm is that all individuals in a population(called particles in a dynamical system)are running and searching with their population evolving driven by a new selecting mechanism.This mechanism simulates the principle of molecular dynamics,which is easy to design and implement.A basic theoretical analysis for the dynamical evolutionary algorithm is given and as a consequence two stopping criteria of the algorithm are derived from the principle of energy minimization and the law of entropy increasing.In order to verify the effectiveness of the scheme,DEA is applied to sloving some typical numerical function minimization problems which are poorly solved by traditional evolutionary algorithms.The experimental results show that EAT is fast and reliable.     

Human Centered Design in Multi-agent Virtual Environment

The efficient and reliable human centered design of products and processes is a major goal in manufacturing industries for numerous human factors must be taken into account during the entire life cycle of products. A multi-agents intelligent design system is presented for manufacturing process simulation and products＇ ergonomic analysis. In virtual design environment, the virtual human with high-level intelligence performs tasks＇ operation autonomously and shows optimum posture configuration with ergonomic assessment results in real time. The functions are realized by intelligent agents architecture based on a modem approach derived from fuzzy multi-objects decision-making theory. A case study is presented to demonstrate the feasibility of the suggested methodology.     

Adaptive fuzzy dynamic surface control for a class of perturbed nonlinear time-varying delay systems with unknown dead-zone

In this paper,adaptive dynamic surface control(DSC) is developed for a class of nonlinear systems with unknown discrete and distributed time-varying delays and unknown dead-zone.Fuzzy logic systems are used to approximate the unknown nonlinear functions.Then,by combining the backstepping technique and the appropriate Lyapunov-Krasovskii functionals with the dynamic surface control approach,the adaptive fuzzy tracking controller is designed.Our development is able to eliminate the problem of "explosion of complexity" inherent in the existing backstepping-based methods.The main advantages of our approach include:1) for the n-th-order nonlinear systems,only one parameter needs to be adjusted online in the controller design procedure,which reduces the computation burden greatly.Moreover,the input of the dead-zone with only one adjusted parameter is much simpler than the ones in the existing results;2) the proposed control scheme does not need to know the time delays and their upper bounds.It is proven that the proposed design method is able to guarantee that all the signals in the closed-loop system are bounded and the tracking error is smaller than a prescribed error bound,Finally,simulation results demonstrate the effectiveness of the proposed approach.     

Fault detection and identification based on combining logic and model in a wall-climbing robot

A combined logic- and model-based approach to fault detection and identification （FDI） in a suction foot control system of a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events （elementary causes）, which can lead to a root event （a particular fault）. Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot.     

Active resilient defense control against false data injection attacks in smart grids

The emerging of false data injection attacks (FDIAs) can fool the traditional detection methods by injecting false data, which has brought huge risks to the security of smart grids. For this reason, a resilient active defense control scheme based on interval observer detection is proposed in this paper to protect smart grids. The proposed active defense highlights the integration of detection and defense against FDIAs in smart girds. First, a dynamic physical grid model under FDIAs is modeled, in which model uncertainty and parameter uncertainty are taken into account. Then, an interval observer-based detection method against FDIAs is proposed, where a detection criteria using interval residual is put forward. Corresponding to the detection results, the resilient defense controller is triggered to defense the FDIAs if the system states are affected by FDIAs. Linear matrix inequality (LMI) approach is applied to design the resilient controller with H_{{\infty }} performance. The system with the resilient defense controller can be robust to FDIAs and the gain of the resilient controller has a certain gain margin. Our active resilient defense approach can be built in real time and show accurate and quick respond to the injected FDIAs. The effectiveness of the proposed defense scheme is verified by the simulation results on an IEEE 30-bus grid system.     

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model （GFHM）. Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.     

Recent advances on formal methods for safety and security of cyber-physical systems

Cyber-physical systems (CPSs) are engineering systems with both computational and physical components [1]. Typical CPSs include energy systems, transportation systems, autonomous vehicles, etc. CPSs are usually hybrid involving complex interactions of continuous dynamics with discrete logics. The development of controller design and verification algorithms for such complex systems are crucial and challenging tasks. Ever-increasing demands for safety and security of CPSs put stringent constraints on their analysis and design, and necessitate the use of formal model-based approaches. In recent years, we have witnessed a substantial increase in the use of formal techniques for the verification and design of safety–critical and security-sensitive CPSs [2]. Due to the complex functionalities of safety–critical CPSs, ensuring safety is extremely challenging. In particular, since CPSs involve both continuous and discrete dynamics, safety not only requires that the low-level physical trajectory is within constrained regions, e.g., the value of the state should never exceed a threshold, but also requires that the high-level behavior of the system satisfies some desired specifications, e.g., executing a set of tasks in a right order. However, existing control theory mainly focuses on simple low-level specifications such as stability. To describe functional safety of the high-level behaviors of CPSs, more rich specification languages, such as regular languages and linear temporal logics (LTL), are needed. Also, security-related attacks are increasingly becoming pervasive in safety–critical cyber-physical systems; such security vulnerabilities related to information leaks in CPSs are extremely difficult to discover and mitigate as the interaction between the embedded control software and the physical environment exposes numerous attack surfaces for malicious exploitation. To enforce complex specifications for safety–critical cyber-physical systems, one of the most popular approaches developed in the past 50 years is the abstraction-based approach, which consists of the following steps: 1) abstract the original infinite continuous system as a finite symbolic system; 2) synthesize a supervisory controller based on the symbolic model to enforce desired specifications; 3) refine the symbolic controller synthesized to control the original system. To construct the symbolic model, a typical approach is to discretize the state-space to induce a finite quotient system. The key here is to establish certain relationship between the original system and its abstraction. In the seminal work of [3], the notion of approximate bi-simulation relation was proposed to capture the equivalence of two models with guaranteed abstraction error; this idea was further extended to the notion of alternating bi-simulation relation for the purpose of control [4]. Recently in [5], a more unified relation called feedback refinement relation was proposed. Compositional approaches have also been developed to compute finite abstractions for large-scale interconnected CPSs [6]....     

Robust adaptive control for uncertain nonlinear systems with unknown control directions and actuator nonlinearity

A robust adaptive control scheme is proposed for a class of uncertain nonlinear systems in strict feedback form with both unknown control directions and non-symmetric dead-zone nonlinearity based on backstepping design.The conditions that the dead-zone slopes and the boundaries are equal and symmetric are removed by simplifying nonlinear dead-zone input model,the assumption that the priori knowledge of the control directions to be known is eliminated by utilizing Nussbaum-type gain technique and neural networks(NN) approximation capability.The possible controller singularity problem and the effect of dead-zone input nonlinearity are avoided perfectly by combining integral Lyapunov design with sliding mode control strategy.All the signals in the closed-loop system are guaranteed to be semi-globally uniformly ultimately bounded and the tracking error of the system is proven to be converged to a small neighborhood of the origin.Simulation results demonstrate the effectiveness of the proposed control scheme.     

Visual Similarity Based Document Layout Analysis

In this paper, a visual similarity based document layout analysis （DLA） scheme is proposed, which by using clustering strategy can adaptively deal with documents in different languages, with different layout structures and skew angles. Aiming at a robust and adaptive DLA approach, the authors first manage to find a set of representative filters and statistics to characterize typical texture patterns in document images, which is through a visual similarity testing process. Texture features are then extracted from these filters and passed into a dynamic clustering procedure, which is called visual similarity clustering. Finally, text contents are located from the clustered results. Benefit from this scheme, the algorithm demonstrates strong robustness and adaptability in a wide variety of documents, which previous traditional DLA approaches do not possess.     

Observer-based adaptive fuzzy backstepping control of uncertain nonlinear pure-feedback systems

In this paper,a new fuzzy adaptive control approach is developed for a class of SISO uncertain pure-feedback nonlinear systems with immeasurable states.Fuzzy logic systems are utilized to approximate the unknown nonlinear functions;and the filtered signals are introduced to circumvent algebraic loop systems encountered in the implementation of the controller,and a fuzzy state adaptive observer is designed to estimate the immeasurable states.By combining the adaptive backstepping technique,an adaptive fuzzy output feedback control scheme is developed.It is proven that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded(SGUUB),and the observer and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Simulation studies are included to illustrate the efectiveness of the proposed approach.     

无线传感器网络中一种新的分布式定位方案研究

Node localization in wireless sensor networks (WSN) is treated as a functional dual of target tracking from a novel perspective in the paper. Different from the traditional tracking problem in WSN, using the static location-ware node to estimate the moving target, the mobile node is used to help unknown nodes to accurately discover their positions. A new node localization scheme virtual beacons-energy ratios localization (VB-ERL) and its refinements for the WSN are presented. In the scheme, the mobile node moves in the surveillant field based on the Gauss-Markov mobility model and periodically broadcasts the information packets. Each static unknown node receives the virtual beacons and energy in its sensing range, and estimates its location by finding the intersection of a set of hyper-spheres. Simulation results show the proposed scheme is efficient.     

Flexibility analysis of a tracking control method for air-breathing hypersonic vehicles

This paper studies the flexibility of a tracking control method originally proposed by the authors for air-breathing hypersonic vehicles （AHVs）. The main feature of this method is to design the tracking controller without canceling but using aero-propulsive, as well as elevator-to-lift couplings. By introducing a virtual input, the tracking controller and external reference trajectories are simultaneously obtained by solving a system of linear algebraic equations. This system of linear algebraic equations is always solvable and the solution space of the corresponding homogeneous system is of dimension 3, which leads to much freedom in choosing or defining the free variables. The flexibility is reflected by the fact that the flight requirements of AHVs are involved in the definition of the free variables. Three case studies on different maneuvers, i.e., flight at constant dynamic pressure, flight at variant dynamic pressure and flight with fast climb rate are considered to verify the flexibility of this method. Simulation results show its effectiveness and flexibility.