基于FPGA的高速数据存储系统优化设计

针对遥测系统数据记录装置中数据传输速率与存储速率不匹配的问题,提出Flash的并行存储方案,采用交替双平面的编程方式可以使得存储器的存储速率达到单片Flash最高存储速率的2倍,即60 MB/s;对控制单元FPGA内部双端口RAM的逻辑设计进行改进,解决了数据存储异常的现象。在数据回收方面,提出了多备份的设计思想和备用读数接口的设计方案,已在工程应用中得到成功实践,验证了该数据记录装置的可靠性。     

辅锅控制程序在CENTUM-CS上的实现

全面介绍辅锅点火系统，从硬件配置、安全条件、点火逻辑和软件组态等几个方面论述辅锅控制程序的原理及其在CENTUM—CS上的实现方法，对CS系统的进一步开发利用具有较大的启发和借鉴作用。     

Stabilization of Rössler chaotic dynamical system using fuzzy logic control algorithm

This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rössler chaotic dynamical system. The fuzzy logic control system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis in the sense of Lyapunov is carried out using Lyapunov’s direct method. The new FLCA is formulated to offer sufficient inequality stability conditions. The asymptotic complexity of our algorithm is analyzed and proved to be lower in comparison with that of linear matrix inequality-based FLCAs. A set of simulation results illustrates the effectiveness of the proposed FLCA.     

A simple method to solve the forward displacement analysis of the general six-legged parallel manipulator

In this work a simple method to solve the forward displacement analysis of the general 6-6 fully parallel manipulator is applied. The method is based on generating closure equations upon the unknown coordinates of three points embedded to the moving platform. The method is easy to follow and it is available for both, planar and three-dimensional moving platforms. Numerical examples are included with the purpose to show the application of the method.     

An adaptive neural control scheme for articulatory synthesis of CV sequences

Reproducing the smooth vocal tract trajectories is critical for high quality articulatory speech synthesis. This paper presents an adaptive neural control scheme for such a task using fuzzy logic and neural networks. The control scheme estimates motor commands from trajectories of flesh-points on selected articulators. These motor commands are then used to reproduce the trajectories of the underlying articulators in a 2nd order dynamical system. Initial experiments show that the control scheme is able to manipulate the mass-spring based elastic tract walls in a 2-dimensional articulatory synthesizer and to realize efficient speech motor control. The proposed controller achieves high accuracy during on-line tracking of the lips, the tongue, and the jaw in the simulation of consonant–vowel sequences. It also offers salient features such as generality and adaptability for future developments of control models in articulatory synthesis.     

Modeling and verifying probabilistic Multi-Agent Systems using knowledge and social commitments

Multi-Agent Systems (MASs) have long been modeled through knowledge and social commitments independently. In this paper, we present a new method that merges the two concepts to model and verify MASs in the presence of uncertainty. To express knowledge and social commitments simultaneously in uncertain settings, we define a new multi-modal logic called Probabilistic Computation Tree Logic of Knowledge and Commitments (PCTL^kc in short) which combines two existing probabilistic logics namely, probabilistic logic of knowledge PCTLK and probabilistic logic of commitments PCTLC. To model stochastic MASs, we present a new version of interpreted systems that captures the probabilistic behavior and accounts for the communication between interacting components. Then, we introduce a new probabilistic model checking procedure to check the compliance of target systems against some desirable properties written in PCTL^kc and report the obtained verification results. Our proposed model checking technique is reduction-based and consists in transforming the problem of model checking PCTL^kc into the problem of model checking a well established logic, namely PCTL. So doing provides us with the privilege of re-using the PRISM model checker to implement the proposed model checking approach. Finally, we demonstrate the effectiveness of our approach by presenting a real case study. This framework can be considered as a step forward towards closing the gap of capturing interactions between knowledge and social commitments in stochastic agent-based systems.     

A survey on nature-inspired optimization algorithms with fuzzy logic for dynamic parameter adaptation

Metaheuristic optimization algorithms have become a popular choice for solving complex problems which are otherwise difficult to solve by traditional methods. However, these methods have the problem of the parameter adaptation and many researchers have proposed modifications using fuzzy logic to solve this problem and obtain better results than the original methods. In this study a comprehensive review is made of the optimization techniques in which fuzzy logic is used to dynamically adapt some important parameters in these methods. In this paper, the survey mainly covers the optimization methods of Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Ant Colony Optimization (ACO), which in the last years have been used with fuzzy logic to improve the performance of the optimization methods.     

Customizable hardware design of fuzzy controllers applied to autonomous car driving

Nowadays, final products often encompass a certain intelligence therein to deal with variation or lack of precision in the sensing input data. This intelligence is usually acquired via the utilization of existing soft techniques, such as artificial neural networks, genetic algorithms and fuzzy control, among others. Thus, it is profitable to have on-the-shelf shell scalable and adaptive hardware designs that implement these soft techniques. This availability allows for an immediate embedding of any of those designs onto final products. This usually entails a reduced time-to-market of the product. Process control is one of the many applications that took advantage of the fuzzy paradigm. In general, controllers are embedded into the controlled device. This paper presents a novel design of a reconfigurable efficient parallel architecture to implement fuzzy controllers on hardware with almost no design effort for final users. The proposed architecture is herein proven suitable for embedding. It is customizable, so it allows the setup and configuration of the controller parameters, and hence its use for any problem application. Two fuzzy controllers that model autonomous car driving are implemented and their cost and performance evaluated.     

Feedback PID-like fuzzy controller for pH regulatory control near the equivalence point

In this research the use of a feedback PID-like fuzzy controller scheme for pH control is presented to deal with instability problems near the equivalence point in neutralization processes. State space analysis of the titration curves and a fuzzy clustering algorithm based on calculating a measure of potential derived from the square distance of the pH data are complementary applied to define the membership structure and the fuzzy sets of the controller. To test the performance of the controller, both simulated and experimental runs were used. The fuzzy controller was tested for compensating step-change perturbations of propionic acidic flow rates, propionic acid concentration, and buffering conditions. Stationary cycling behavior has been observed for large loads of acidic flow rates. It was found that though the rejection time was strongly dependent on the mean residence time of the liquid solutions, the proposed controller keep the neutralization process operating close to the specified set point of pH = 7.     

ECS-100 DCS控制系统在离子膜制碱装置中的应用

介绍某公司引进的离子膜制碱装置采用国产DCS系统的原由，系统的结构及特点。详细论述ECS-100 DCS在装置的特殊控制、顺序控制、联锁等方面的应用情况。