Process Parameters Optimization: A Design Study for TiO$_{2}$ Thin Film of Vacuum Sputtering Process

This paper proposes a procedure for process parameters design by combining both modeling and optimization methods. The proposed procedure integrates the Taguchi method, the artificial neural network (ANN), and the genetic algorithm (GA). First, the Taguchi method is applied to minimize experimental numbers and to collect experimental data representing the quality performances of a system. Next, the ANN is used to build a system model based on the data from the Taguchi experimental method. Then, the GA is employed to search for the optimal process parameters. A process parameters design for a titanium dioxide (TiO₂) thin film in the vacuum sputtering process is studied in this paper. The quality objective is to form a smaller water contact angle on the TiO₂ thin-film surface. The water contact angle is 4° obtained from the system model of the proposed procedure. The process parameters obtained from the proposed procedure were used to conduct the experiment in the vacuum sputtering process for the TiO₂ thin film. The water contact angle given from the practical experiment is 3.93°. The difference percent is 1.75% between 4° and 3.93°. The result obtained from the system model of the proposed procedure is promising. Hence, we can conclude that the proposed procedure is a very good approach in solving the problem of the process parameters design.     

Network-Based ${{cal H}}_{!!!infty }$ Output Tracking Control

This paper is concerned with the problem of H_infin output tracking for network-based control systems. The physical plant and the controller are, respectively, in continuous time and discrete time. By using a sampled-data approach, a new model based on the updating instants of the holder is formulated, and a linear matrix inequality (LMI)-based procedure is proposed for designing state-feedback controllers, which guarantee that the output of the closed-loop networked control system tracks the output of a given reference model well in the H_infin sense. Both network-induced delays and data packet dropouts have been taken into consideration in the controller design. The network-induced delays are assumed to have both an upper bound and a lower bound, which is more general than those used in the literature. The introduction of the lower bound is shown to be advantageous for reducing conservatism. Moreover, the controller design method is further extended to more general cases, where the system matrices of the physical plant contain parameter uncertainties, represented in either polytopic or norm-bounded frameworks. Finally, an illustrative example is presented to show the usefulness and effectiveness of the proposed H_infin output tracking design.     

$H_{bm infty}$ Fuzzy Filtering of Nonlinear Systems With Intermittent Measurements

This paper is concerned with the problem of H _infin fuzzy filtering of nonlinear systems with intermittent measurements. The nonlinear plant is represented by a Takagi-Sugeno (T-S) fuzzy model. The measurements transmission from the plant to the filter is assumed to be imperfect, and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the phenomenon of the missing measurements. Attention is focused on the design of an H _infin filter such that the filter error system is stochastically stable and preserves a guaranteed H _infin performance. A basis-dependent Lyapunov function approach is developed to design the H _infin filter. By introducing some slack matrix variables, the coupling between the Lyapunov matrix and the system matrices is eliminated, which greatly facilitates the filter-design procedure. The developed theoretical results are in the form of linear matrix inequalities (LMIs). Finally, an illustrative example is provided to show the effectiveness of the proposed approach.     

$H_{infty}$ Controller Synthesis via Switched PDC Scheme for Discrete-Time T--S Fuzzy Systems

This paper is concerned with the problem of designing switched state feedback $H_{infty}$ controllers for discrete-time Takagi--Sugeno (T--S) fuzzy systems. New types of state feedback controllers, namely, switched parallel distributed compensation (PDC) controllers, are proposed, which are switched based on the values of membership functions. Switched quadratic Lyapunov functions are exploited to derive a new method for designing switched PDC controllers to guarantee the stability and $H_{infty}$ performances of closed-loop nonlinear systems. The design conditions are given in terms of solvability of a set of linear matrix inequalities. It is shown that the new method provides better or at least the same results of the existing design methods via the pure PDC scheme with a quadratic Lyapunov function or switched constant controller gain scheme. Numerical examples are given to illustrate the effectiveness of the proposed method.      

A New Recurrent Neural Network for Solving Convex Quadratic Programming Problems With an Application to the $k$-Winners-Take-All Problem

In this paper, a new recurrent neural network is proposed for solving convex quadratic programming (QP) problems. Compared with existing neural networks, the proposed one features global convergence property under weak conditions, low structural complexity, and no calculation of matrix inverse. It serves as a competitive alternative in the neural network family for solving linear or quadratic programming problems. In addition, it is found that by some variable substitution, the proposed network turns out to be an existing model for solving minimax problems. In this sense, it can be also viewed as a special case of the minimax neural network. Based on this scheme, a k-winners-take-all (k-WTA) network with O(n) complexity is designed, which is characterized by simple structure, global convergence, and capability to deal with some ill cases. Numerical simulations are provided to validate the theoretical results obtained. More importantly, the network design method proposed in this paper has great potential to inspire other competitive inventions along the same line.     

An intelligent fuzzy sliding mode control system with application on precision table positioning

In this paper, an intelligent fuzzy sliding mode control system, which cooperates with a new learning approach called modulus genetic algorithm, is proposed. Furthermore, it is applied to a high precision table positioning system for verifying its practicability. Fuzzy sliding mode controller (FSMC) is a special type of fuzzy controller with certain attractive advantages than the conventional fuzzy controller. The learning and stability issues of FSMC are discussed in the paper. Furthermore, to overcome the encoding/decoding procedure that leads to considerable numeric errors in conventional genetic algorithm, this paper proposes a new algorithm called modulus genetic algorithm (MGA). The MGA uses the modulus operation such that the encoding/decoding procedure is not necessary. It has the following advantages: (1) the evolution can be speeded up; (2) the numeric truncation error can be avoided; (3) the precision of solution can be increased. For verifying the practicability of the proposed approach, the MGA‐based FSMC is applied to design a position controller for a high precision table. The experimental results show the proposed approach can achieve submicro positioning precision. © 2001 John Wiley & Sons, Inc.     

H∞ Estimation for Uncertain Systems With Limited Communication Capacity

This paper investigates the problem of robust H_infin estimation for uncertain systems subject to limited communication capacity. The parameter uncertainty belongs to a given convex polytope and the communication limitations include measurement quantization, signal transmission delay, and data packet dropout, which appear typically in a network environment. The problem of H_infin filter design is first solved for a nominal system subject to the aforementioned information limitations, which is then extended to the uncertain case based on the notion of quadratic stability. To further reduce the overdesign in the quadratic framework, this paper also proposes a parameter-dependent filter design procedure, which is much less conservative than the quadratic approach. The quadratic and parameter-dependent approaches provide alternatives for designing robust H_infin filters with different degrees of conservativeness and computational complexity. Two examples, including a mass-spring system, are utilized to illustrate the design procedures proposed in this paper.     

基于Simulink/RTW的汽车电子控制系统的研究

随着汽车电子控制系统的日益先进和复杂化,传统的手工编写代码实现汽车电控系统的开发模式已不能满足开发需要;结合基于模型的设计方法和代码生成技术,提出了一种基于Simulink/RTW的汽车电子实时控制系统的新型设计方法;利用Simulink进行算法开发、系统建模和仿真验证,然后通过RTW自动生成嵌入式代码,实现汽车电子实时控制系统的开发;并将该设计方法应用到发动机控制系统的开发过程中,通过与Simulink中仿真结果进行对比,验证了该方法的可行性与正确性;经过实践证明这种新型设计方法可以大大缩短控制系统的开发周期,对于嵌入式控制系统的开发具有一定的实用价值。     

Convergent LMI Relaxations for Quadratic Stabilizability and ${{mathscr H}}_{infty}$ Control of Takagi–Sugeno Fuzzy Systems

This paper investigates the quadratic stabilizability of Takagi–Sugeno (T--S) fuzzy systems by means of parallel distributed state feedback compensators. Using Finsler's lemma, a new design condition assuring the existence of such a controller is formulated as a parameter-dependent linear matrix inequality (LMI) with extra matrix variables and parameters in the unit simplex. Algebraic properties of the system parameters and recent results of positive polynomials are used to construct LMI relaxations that, differently from most relaxations in the literature, provide certificates of convergence to solve the control design problem. Due to the degrees of freedom obtained with the extra variables, the conditions presented in this paper are an improvement over earlier results based only on PÓlya's theorem and can be viewed as an alternative to the use of techniques based on the relaxation of quadratic forms. An extension to cope with guaranteed ${{{mathscr{H}}}}_{!infty }$ attenuation levels is also given, with proof of asymptotic convergence to the global optimal controller under quadratic stability. The efficiency of the proposed approach in terms of precision and computational effort is demonstrated by means of numerical comparisons with other methods from the literature.      

A New Neuroadaptive Control Architecture for Nonlinear Uncertain Dynamical Systems: Beyond $sigma $- and $e$-Modifications

This paper develops a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture involving additional terms in the update laws that are constructed using a moving time window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress and cancel system uncertainty without the need for persistency of excitation. A nonlinear parametrization of the system uncertainty is considered and state and output feedback neuroadaptive controllers are developed. To illustrate the efficacy of the proposed approach we apply our results to a spacecraft model with unknown moment of inertia and compare our results with standard neuroadaptive control methods.      

Fragile Watermarking Based on Encoding of the Zeroes of the $z$-Transform

In this paper, a new fragile watermarking method for digital image authentication is proposed based on the zero locations of the $z$-transform. The $z$ -transform domain is a new transform space for fragile watermark embedding. Our watermarking method is designed by exploiting the sensitivity of the positions of the zeroes of the $z$ -transform around the unit circle to any change made on the host image. The watermarking system can localize the portions of a watermarked image that have been tampered with with high accuracy. In addition, the newly proposed scheme is more secure than normal least-significant bits-based fragile watermarking techniques. Experimental results as well as the theoretical analysis demonstrated the fragility and accuracy of the new method.      

A linear matrix inequality (LMI) approach to robust H/sub 2/ sampled-data control for linear uncertain systems

In this paper, we consider the H/sub 2/ sampled-data control for uncertain linear systems by the impulse response interpretation of the H/sub 2/ norm. Two H/sub 2/ measures for sampled-data systems are considered. The robust optimal control procedures subject to these two H/sub 2/ criteria are proposed. The development is primarily concerned with a multirate treatment in which a periodic time-varying robust optimal control for uncertain linear systems is presented. To facilitate multirate control design, a new result of stability of hybrid system is established. Moreover, the single-rate case is also obtained as a special case. The sampling period is explicitly involved in the result which is superior to traditional methods. The solution procedures proposed in this paper are formulated as an optimization problem subject to linear matrix inequalities. Finally, we present a numerical example to demonstrate the proposed techniques.     

A new adaptive control for periodic tracking/disturbance rejection

This paper proposes a new adaptive feedforward cancellation (AFC) control that achieves periodic tracking and/or periodic disturbance rejection. The new control design is a direct scheme in the sense that it adaptively updates the desired control without estimating the unknown disturbance. The proposed new control has several advantages. First, its adaptation gain can be arbitrarily chosen without upsetting the system stability. Second, it can be applied to not only minimum‐phase systems, but also non‐minimum phase systems. Finally, it is shown that the proposed AFC control is independent of where the disturbance enters the system. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

New encoding/decoding methods for designing fault-tolerant matrixoperations

Algorithm-based fault tolerance (ABFT) can provide a low-cost error protection for array processors and multiprocessor systems. Several ABFT techniques (weighted check-sum) have been proposed to design fault-tolerant matrix operations. In these schemes, encoding/decoding uses either multiplications or divisions so that overhead is high. In this paper, new encoding/decoding methods are proposed for designing fault-tolerant matrix operations. The unique feature of these new methods is that only additions and subtractions are used in encoding/decoding. In this paper, new algorithms are proposed to construct error detecting/correcting codes with the minimum Hamming distance 3 and 4. We will show that the overhead introduced due to the incorporation of fault tolerance is drastically reduced by using these new coding schemes     

A Novel Blood Glucose Regulation Using TSK$^{0}$-FCMAC: A Fuzzy CMAC Based on the Zero-Ordered TSK Fuzzy Inference Scheme

This paper presents a novel blood glucose regulation for type I (insulin-dependent) diabetes mellitus patients using biologically inspired TSK⁰-FCMAC, a fuzzy cerebellar model articulation controller (CMAC) based on the zero-ordered Takagi-Sugeno-Kang (TSK) fuzzy inference scheme. TSK⁰-FCMAC is capable of performing localized online training with an effective fuzzy inference scheme that could respond swiftly to changing environment such as human's endocrine system. Without prior knowledge of disturbance (e.g., food intake), the proposed fuzzy CMAC is able to capture the glucose-insulin dynamics of individuals under different dietary profiles. Preliminary simulations show that the blood glucose level is kept within the state of euglycemia. The design of the proposed system follows closely to what is available in real life and is suitable for animal and clinical pilot testing in the near future.     

Decentralized $H_{infty }$ Filter Design for Discrete-Time Interconnected Fuzzy Systems

This paper describes a decentralized $H_{infty }$ filter design for discrete-time interconnected fuzzy systems based on piecewise-quadratic Lyapunov functions. The systems consist of $J$discrete-time interconnected Takagi–Sugeno (T–S) fuzzy subsystems, and a decentralized $H_infty$ filter is designed for each subsystem. It is shown that the stability of the overall filtering-error system with $H_{infty }$ performance can be established if a piecewise-quadratic Lyapunov function can be constructed. Moreover, the parameters of filters can be obtained by solving a set of linear matrix inequalities that are numerically feasible. Two simulation examples are given to show the effectiveness of the proposed approach.      

Fuzzy PCA-Guided Robust -Means Clustering

This paper proposes a new approach to robust clustering, in which a robust $k$-means partition is derived by using a noise-rejection mechanism based on the noise-clustering approach. The responsibility weight of each sample for the $k$-means process is estimated by considering the noise degree of the sample, and cluster indicators are calculated in a fuzzy principal-component-analysis (PCA) guided manner, where fuzzy PCA-guided robust $k$-means is performed by considering responsibility weights of samples. Then, the proposed method achieves cluster-core estimation in a deterministic way. The validity of the derived cluster cores is visually assessed through distance-sensitive ordering, which considers responsibility weights of samples. Numerical experiments demonstrate that the proposed method is useful for capturing cluster cores by rejecting noise samples, and we can easily assess cluster validity by using cluster-crossing curves.      

Design of high-performance QCA incrementer/decrementer circuit based on adder/subtractor methodology

This paper focuses on a novel design of an adder/subtractor-based incrementer/decrementer using quantum-dot cellular automata (QCA) technology. QCA is a promising nanotechnology that offers new techniques of computation and data transmission. We use the multilayer crossover technique in the proposed designs to achieve low latency and area for the scalability feature. Moreover, new designs of QCA half and full adders are proposed to improve the operating speed of the incrementer/decrementer. The working of the proposed designs is analyzed via the QCA simulator tool, and the results are compared with previous studies in terms of cell count, area, and latency. According to the analysis, the presented designs perform well; for example, the proposed 4-bit incrementer design shows an improvement of 65 % in terms of area usage and 3.2 times lower latency compared to its existing counterpart.     

“四期建设”工程项目的分析与设计

本文介绍了“四期建设”工程项目的设计,系统是基于J2EE技术,B／S架构三层结构体系,三层的B／S体系结构具有许多传统C／S体系结构不具备的优点,又紧密地结合了Intemet／Intranet技术,它把应用系统带入了一个崭新的发展时代。     

A parametric study on rocking vibration of rotating disk/spindle systems with hydrodynamic bearings: rotating-shaft design

 The system studied in this paper is a rotating disk/spindle assembly supported by hydrodynamic bearings with a rotating shaft design. Based on an experimentally verified mathematical model [1, 2], this paper presents how various spindle parameters affect critical vibration modes of the system, such as half-speed whirls and (0, 1) unbalanced modes (i.e., rocking modes). The parameters studied include number of disks, hub/shaft interface stiffness, shaft rigidity, thrust bearing location, radial bearing stiffness, radial bearing damping, and radial bearing locations. To simulate operational tests, the numerical study focuses on frequency response functions (FRF) of rotating disk/spindle systems subjected to linear base excitations. Simulation results show that 1-disk configuration has smaller FRF amplitude than the 4-disk configuration. In addition, the amplitude of half-speed whirl is primarily controlled by the radial bearing stiffness. In contrast, the amplitude of (0, 1) unbalanced modes is dominated by hub/shaft interface stiffness. Finally, radial bearing locations significantly affect the amplitude of half-speed whirls and (0, 1) unbalanced modes simultaneously. Received: 16 October 2001/Accepted: 31 December 2001