A novel polysilicon-assisted silicon-controlled rectifier (SCR) is presented and analyzed in this paper, which is fabricated in HHNEC’s 0.18 μm EEPROM process. The polysilicon-assisted SCRs take advantage of polysilicon layer to help bypass electro-static discharge (ESD) current without occupying extra layout area. TLP current-voltage (I-V) measurement results show that given the same layout areas, robustness performance of polysilicon-assisted SCRs can be improved to 3 times of conventional MLSCR’s. Moreover, one-finger such polysilicon-assisted SCRs, which occupy only 947 μm² layout area, can undergo 7-kV HBM ESD stress. Results further demonstrate that the S-type I-V characteristics of polysilicon-assisted SCRs are adjustable to different operating conditions by changing the device dimensions. Compared with traditional SCRs, this new SCR can bypass more ESD currents and consumes smaller IC area.

This paper presents an equalization algorithm for continuous phase modulation (CPM) over frequency-selective channels. A specific training sequence is first embedded in each data packet. By recursive least-squares (RLS) estimation, the channel information parameters can be acquired, and a fractionally spaced equalizer performs joint decoding and equalization. Simulation results show that the proposed algorithm can acquire the channel information parameters rapidly and accurately, and that the fractionally spaced equalizer can eliminate the intersymbol interference (ISI) effectively, and is not sensitive to timing inaccuracy, so this algorithm can be exploited for demodulation system in burst mode.

This paper develops a unified methodology for a real-time speed control of brushless direct-current motor drive systems in the presence of measurement noise and load torque disturbance. First, the mathematical model and hardware structure of system is established. Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived. This is followed by an adaptive control algorithm to compensate for the effects of noise and disturbance. Those two algorithms working together can provide a very-high-speed regulation and dynamic response over a wide range of operating conditions. Simulated responses are presented to highlight the effectiveness of the proposed control strategy.

This paper deals with the design and performance analysis of the transmission precoder optimization for multiple-input multiple-output (MIMO) systems with limited feedback of channel state information (CSI). We assume that the receiver can get perfect channel knowledge by channel estimation while the transmitter only has partial channel knowledge from limited feedback. We present a minimum mean square error (MMSE) criterion based codebook construction algorithm for MIMO precoded spatial multiplexing systems under a specific average power constraint. The optimal transmitter structure is employed in this paper. Simulation results show that the MMSE criteria based codebook construction algorithm with hybrid design of power allocation and precoding can achieve better performance than that of equal power allocation based codebook of previous research.

A dual S shaped micro strip antenna with a realistic feed is proposed for generation of tilted beam radiation pattern pertaining for beam steering applications. To achieve this, four feeding points are located at a distance of 5.6 mm from the antenna centre. These feeding points when excited one by one generate four tilted beams in four different space quadrants, thus yielding a beam steerable antenna. Importantly, since the proposed antenna is symmetrical in the structure, all the four tilted beams have the same radiation pattern characteristics. A further enhancement of the antenna bandwidth is also achieved using 100-µm capacitive coupling between the feed and the antenna strip.

In this paper, we extend a novel unconstrained multiobjective optimization algorithm, so-called multiobjective extremal optimization (MOEO), to solve the constrained multiobjective optimization problems (MOPs). The proposed approach is validated by three constrained benchmark problems and successfully applied to handling three multiobjective engineering design problems reported in literature. Simulation results indicate that the proposed approach is highly competitive with three state-of-the-art multiobjective evolutionary algorithms, i.e., NSGA-II, SPEA2 and PAES. Thus MOEO can be considered a good alternative to solve constrained multiobjective optimization problems.

The robust exponential stability of a larger class of discrete-time recurrent neural networks (RNNs) is explored in this paper. A novel neural network model, named standard neural network model (SNNM), is introduced to provide a general framework for stability analysis of RNNs. Most of the existing RNNs can be transformed into SNNMs to be analyzed in a unified way. Applying Lyapunov stability theory method and S-Procedure technique, two useful criteria of robust exponential stability for the discrete-time SNNMs are derived. The conditions presented are formulated as linear matrix inequalities (LMIs) to be easily solved using existing efficient convex optimization techniques. An example is presented to demonstrate the transformation procedure and the effectiveness of the results.

This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.

This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.

To reduce mechanical vibrations induced by big errors compensation, a new software compensation method based on an improved digital differential analyzer (DDA) interpolator for static and quasi-static errors of machine tools is proposed. Based on principle of traditional DDA interpolator, a DDA interpolator is divided into command generator and command analyzer. There are three types of errors, considering the difference of positions between compensation points and interpolation segments. According to the classification, errors are distributed evenly in data processing and compensated to certain interpolation segments in machining. On-line implementation results show that the proposed approach greatly improves positioning accuracy of computer numerical control (CNC) machine tools.

The container loading problem (CLP) is a well-known NP-hard problem. Due to the computation complexity, heuristics is an often-sought approach. This article proposes two heuristics to pack homogeneous rectangular boxes into a single container. Both algorithms adopt the concept of building layers on one face of the container, but the first heuristic determines the layer face once for all, while the second treats the remaining container space as a reduced-sized container after one layer is loaded and, hence, selects the layer face dynamically. To handle the layout design problem at a layer’s level, a block-based 2D packing procedure is also developed. Numerical studies demonstrate the efficiency of the heuristics.

In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user’s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.

This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct control of six joints. The original structure of the PUMA robot is retained. The hardware of the new controller includes such in-house designed parts as pulse width modulation (PWM) amplifiers, digital and analog controllers, I/O cards, signal conditioner cards, and 16-bit A/D and D/A boards. An Intel Pentium IV industrial computer is used as the central controller. The control software is implemented using VC++ programming language. The trajectory tracking performance of all six joints is tested at varying velocities. Experimental results show that it is feasible to implement the suggested open architecture platform for PUMA 500 series robots through the software routines running on a PC. By assembling controller from off-the-shell hardware and software components, the benefits of reduced and improved robustness have been realized.

Localization is one of the substantial issues in wireless sensor networks. The key problem for the mobile beacon localization is how to choose the appropriate beacon trajectory. However, little research has been done on it. In this paper, firstly, we deduce the number of positions for a beacon to send a packet according to the acreage of ROI (region of interest); and next we present a novel method based on virtual force to arrange the positions in arbitrary ROI; then we apply TSP (travelling salesman problem) algorithm to the positions sequence to obtain the optimal touring path, i.e. the reduced beacon trajectory. When a mobile beacon moves along the touring path, sending RF signals at every position, the sensors in ROI can work out their position with trilateration. Experimental results demonstrate that the localization method, based on the beacon reduced path, is efficient and has flexible accuracy.

P2P systems are categorized into tree-based and mesh-based systems according to their topologies. Mesh-based systems are considered more suitable for large-scale Internet applications, but require optimization on latency issue. This paper proposes a content subscribing mechanism (CSM) to eliminate unnecessary time delays during data relaying. A node can send content data to its neighbors as soon as it receives the data segment. No additional time is taken during the interactive stages prior to data segment transmission of streaming content. CSM consists of three steps. First, every node records its historical segments latency, and adopts gamma distribution, which possesses powerful expression ability, to express latency statistics. Second, a node predicts subscribing success ratio of every neighbor by comparing the gamma distribution parameters of the node and its neighbors before selecting a neighbor node to subscribe a data segment. The above steps would not increase latency as they are executed before the data segments are ready at the neighbor nodes. Finally, the node, which was subscribed to, sends the subscribed data segment to the subscriber immediately when it has the data segment. Experiments show that CSM significantly reduces the content data transmission latency.

Currently, there is a growing belief that putting an IEEE 802.11-like radio into road vehicles can help the drivers to travel more safely. Message dissemination protocols are primordial for safety vehicular applications. There are two types of safety messages which may be exchanged between vehicles: alarm and beacon. In this paper we investigate the feasibility of deploying safety applications based on beacon message dissemination through extensive simulation study and pay special attention to the safety requirements. Vehicles are supposed to issue these messages periodically to announce to other vehicles their current situation and use received messages for preventing possible unsafe situations. We evaluate the performance of a single-hop dissemination protocol while taking into account the quality of service (QoS) metrics like delivery rate and delay. We realize that reliability is the main concern in beacon message dissemination. Thus, a new metric named effective range is defined which gives us more accurate facility for evaluating QoS in safety applications specifically. Then, in order to improve the performance, the effects of three parameters including vehicle’s transmission range, message transmission’s interval time and message payload size are studied. Due to special characteristics of the safety applications, we model the relationship between communication-level QoS and application-level QoS and evaluate them for different classes of safety applications. As a conclusion, the current technology of IEEE 802.11 MAC layer has still some challenges for automatic safety applications but it can provide acceptable QoS to driver assistance safety applications.

This paper gives a practical schema for using DSP boards to construct Vehicle License Plate Recognition (VLPR) modules that could be embedded in any Intelligent Transportation System (ITS). Using DSP can avoid the heavy investment in dedicated VLPR system and improve the computational power compared to PC software environment. Low cost, high computational power, and high flexibility of DSP provide the License Plate Recognition System (LPRS) an excellent cost-effective solution to execute the major part of the recognition tasks. This paper describes a successful implementation of VLPR system based on Texas Instruments (TI)’s TMS320DM642. The DSP board acquires video (which could be output to a monitor for surveillance) from a camera, captures images from the video, locates and recognizes the license plates in images, and then sends the recognized results and related images after compression to a host PC through the network. Finally, the overall software is optimized according to the features of DM642 chip. Experiments showed that the DSP VLPR system performs well on the local license plates, and that the processing speed and accuracy can meet the requirement of practical applications.

Estimating the global position of a road vehicle without using GPS is a challenge that many scientists look forward to solving in the near future. Normally, inertial and odometry sensors are used to complement GPS measures in an attempt to provide a means for maintaining vehicle odometry during GPS outage. Nonetheless, recent experiments have demonstrated that computer vision can also be used as a valuable source to provide what can be denoted as visual odometry. For this purpose, vehicle motion can be estimated using a non-linear, photogrametric approach based on RAndom SAmple Consensus (RANSAC). The results prove that the detection and selection of relevant feature points is a crucial factor in the global performance of the visual odometry algorithm. The key issues for further improvement are discussed in this letter.

In this paper, a new illumination system with ultra high performance (UHP) lamp is proposed for projection display. Parabolic reflector (PR) and compound parabolic retro-reflector (CPR) were jointly used to collect and collimate the light generated from UHP lamp. A polarization converter system (PCS) was used to increase the light efficiency of the projection display system. A beam transformer between PCS and 2f imaging systems was directly used to make the illumination meet the requirement of projection display system. With the consideration of the loss of reflection, the light efficiency in this projection display system was estimated to be 15.6%.

In this paper, a low-cost measurement approach with bi-beam was presented, which can be used for real-time detection and online analysis of solution refractive index, based on systematical analysis and experiments of conventional detection methods on surface plasmon resonance sensor. This novel method was analyzed theoretically and based on it a sensor system set was established. The factors that affect the sensor’s sensitivity and working range were discussed. The angular adjustment setup was simplified, errors produced by movable components were avoided and the maneuverability was enhanced with this new method. The noiseproof feature and stability of the sensor system were greatly improved as well.

In this paper, we consider an explicit iteration scheme with perturbed mapping for nonexpansive mappings in real q-uniformly smooth Banach spaces. Some weak and strong convergence theorems for this explicit iteration scheme are established. In particular, necessary and sufficient conditions for strong convergence of this explicit iteration scheme are obtained. At last, some useful corollaries for strong convergence of this explicit iteration scheme are given.

In this paper, we shall prove that the Marcinkiewicz integral operator μ_Ω, when its kernel Ω satisfies the L¹-Dini condition, is bounded on the Triebel-Lizorkin spaces. It is well known that the Triebel-Lizorkin spaces are generalizations of many familiar spaces such as the Lebesgue spaces and the Sobolev spaces. Therefore, our result extends many known theorems on the Marcinkiewicz integral operator. Our method is to regard the Marcinkiewicz integral operator as a vector valued singular integral. We also use another characterization of the Triebel-Lizorkin space which makes our approach more clear.