Derivation of a second-order switching surface in the boundary control of buck converters

A second-order switching surface in the boundary control of buck converters is derived in this letter. The formulated switching surface can make the overall converter exhibit better steady-state and transient behaviors than the one with a first-order switching surface. The switching surface is derived by estimating the state trajectory movement after a switching action, resulting in a high state trajectory velocity along the switching surface. This phenomenon accelerates the trajectory moving toward the target operating point. The proposed control scheme has been successfully applied to a 120-W buck converter. The large-signal performance and a comparison with the first-order switching surface have been studied.     

High-performance MIM capacitor using ALD high-k HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectrics

For the first time, we successfully fabricated and demonstrated high performance metal-insulator-metal (MIM) capacitors with HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectric using atomic layer deposition (ALD) technique. Our data indicates that the laminate MIM capacitor can provide high capacitance density of 12.8 fF//spl mu/m/sup 2/ from 10 kHz up to 20 GHz, very low leakage current of 3.2 /spl times/ 10/sup -8/ A/cm/sup 2/ at 3.3 V, small linear voltage coefficient of capacitance of 240 ppm/V together with quadratic one of 1830 ppm/V/sup 2/, temperature coefficient of capacitance of 182 ppm//spl deg/C, and high breakdown field of /spl sim/6 MV/cm as well as promising reliability. As a result, the HfO/sub 2/-Al/sub 2/O/sub 3/ laminate is a very promising candidate for next generation MIM capacitor for radio frequency and mixed signal integrated circuit applications.     

An evolutionary algorithm for large traveling salesman problems

This work proposes an evolutionary algorithm, called the heterogeneous selection evolutionary algorithm (HeSEA), for solving large traveling salesman problems (TSP). The strengths and limitations of numerous well-known genetic operators are first analyzed, along with local search methods for TSPs from their solution qualities and mechanisms for preserving and adding edges. Based on this analysis, a new approach, HeSEA is proposed which integrates edge assembly crossover (EAX) and Lin-Kernighan (LK) local search, through family competition and heterogeneous pairing selection. This study demonstrates experimentally that EAX and LK can compensate for each other's disadvantages. Family competition and heterogeneous pairing selections are used to maintain the diversity of the population, which is especially useful for evolutionary algorithms in solving large TSPs. The proposed method was evaluated on 16 well-known TSPs in which the numbers of cities range from 318 to 13509. Experimental results indicate that HeSEA performs well and is very competitive with other approaches. The proposed method can determine the optimum path when the number of cities is under 10,000 and the mean solution quality is within 0.0074% above the optimum for each test problem. These findings imply that the proposed method can find tours robustly with a fixed small population and a limited family competition length in reasonable time, when used to solve large TSPs.     

Measurement and numerical simulation of three‐dimensional fiber orientation states in injection‐molded short‐fiber‐reinforced plastics

To determine three‐dimensional fiber orientation states in injection‐molded short‐fiber composites, a confocal laser scanning microscope (CLSM) is used. Since the CLSM optically sections the specimen, more than two images of the cross sections on and below the surface of the composite can be obtained. Three‐dimensional fiber orientation states can be determined by using geometric parameters of fiber images obtained from two parallel cross sections. For experiments, carbon‐fiber‐reinforced polystyrene is examined by the CLSM and geometric parameters of fibers on each cross‐sectional plane are measured by an image analysis. In order to describe fiber orientation states compactly, orientation tensors are determined at different positions of the prepared specimen. Three‐dimensional orientation states are obtained without any difficulty by determining the out‐of‐plane angles utilizing fiber images on two parallel planes acquired by the CLSM. Orientation states are different at different positions and show the shell–core structure along the thickness of the specimen. Fiber orientation tensors are predicted by a numerical analysis and the numerically predicted orientation states show good agreement with measured ones. However, some differences are found at the end of cavity. They may result from the fountain flow effects, which are not considered in the numerical analysis. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 500–509, 2003     

Advanced disturbance observer design for mechanical positioning systems

Disturbance-observer (DOB)-based controller design is one of the most popular methods in the field of motion control. In this paper, the generalized disturbance compensation framework, named the robust internal-loop compensator (RIC) is introduced and an advanced design method of a DOB is proposed based on the RIC. The mixed sensitivity optimization problem, which is the main issue of DOB design, is also solved through the parametrization of the DOB in the RIC framework. Differently from conventional methods, the Q-filter is separated from the mixed sensitivity optimization problem and a systematic design law for the DOB is proposed. This guarantees the robustness and optimality of the DOB and enables the design for unstable plants.     

Diagnosis and correction of multiple logic design errors in digitalcircuits

This paper presents a technique to correct multiple logic design errors in a gate-level netlist. A number of methods have been proposed for correcting single logic design errors. However, the extension of these methods to more than one error is still very limited. We direct our attention to circuits with a low multiplicity of errors. By assuming different error dependency scenarios, multiple errors are corrected by repeatedly applying a single error search and correction algorithm. Experimental results on correcting double-design errors and triple-design errors on ISCAS and MCNC benchmark circuits are included     

Fixed-order H∞ compensator design

A method is presented for the construction of fixed-order compensators to provide H_∞ norm constraint for linear control systems with exogenous disturbances. The method is based on the celebrated bounded-real lemma that predicates the H_∞ norm constraint via a Riccati inequality. The synthesis of fixed-order controllers whose dimensions are less than the order of a given plant, is demonstrated by a set of sufficient conditions along with a numerical algorithm.     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

Characterization method of thermomechanical parameters for microelectronic materials

Reliability of thermomechanical simulations is critically linked to the accuracy of the mechanical properties that govern the behaviour of structure, like Young's modulus (E) and coefficient of thermal expansion (CTE). For many cases, the values found in literatures are dealing with bulk properties without detailed information on temperature effects. To address such issues, it is necessary to measure the materials parameters as a function of temperature. The measurement of CTE is usually accomplished by evaluating the thermal deflections of a subjected material layer deposited on a substrate, providing that E is known at a specific temperature of experiment. A bilayer method, based on theory of elasticity, is proposed to determine both E and CTE for a given temperature with a good resolution. This paper presents the theoretical analysis, the design and process of the microsystem test structures, and the main calculation results.