A minimized zero mean entropy approach to networked control systems
A novel control method is proposed for networked control systems with nonlinear process, probably non-Gaussian process noise and time delays. The performance index of closed loop control system consists of entropy, mean value and control energy constraint. Two stochastic control methods for networked control systems are given under the same general frame. One method utilizes gradient optimal techniques to obtain an optimal control law, and the stability of closed loop systems is analyzed. The other method gives the optimal solution of control law directly. The implementation issues are emphasized. The sliding window techniques and non-parametric probability density function estimation techniques are employed to obtain the entropy of tracking error recursively. As a result, the controller can be on-line tuned. Finally, the methodology is illustrated by simulations.

title: Novel Parameter Identification by Using a High-Gain Observer With Application to a Gas Turbine Engine
abstract: In this study, a novel identification technique, that is high-gain observer-based identification approach, is proposed for systems with bounded process and measurement noises. For system parameters with abnormal changes, an adaptive change detection and parameter identification algorithm is next presented. The presented technique and algorithm are finally applied to the parameter identification of the gas turbine engine by using the recorded input data from the engine test-bed. The identified parameters and the response curves are desirable. The simulations have proved the effectiveness of the proposed procedure compared with the previous identification approach.

title: An Intelligent Mill Load Switching Control of the Pulverizing System for an Alumina Sintering Process
abstract: This paper proposes an intelligent switching control strategy for the pulverizing system for an alumina sintering process. The control strategy consists of a coordinating controller, a proportional-integral (PI) controller, a rule-based reasoning controller and a switching mechanism. The practical application to a pulverizing system in an alumina sintering process has shown that when the hot air temperature is low and varies frequently, this control strategy ensures that the mill load and the temperature of the mill outlet are both within their required ranges, and also controls the mill load at the level corresponding to the maximum mill output. Moreover, it has been observed that the proposed control strategy can avoid the fault operating condition and effectively reduce the unit energy consumption.

title: Advances in stochastic distribution control
abstract: Stochastic distribution control systems aims at the controller design so as to realize a shape control of the distributions of certain random variables in the process. Once the probability density functions (PDFs) of these variables are used to describe their distributions, the control task is to obtain control signals so that the output PFDs of the system are made to follow their target PDFs. In this paper, a survey of the recent developments on the research of stochastic distribution control systems will be made.

title: Robust minimum entropy tracking control with guaranteed stability for nonlinear stochastic systems under modeling errors
abstract: In this paper, robust minimum entropy tracking control problem is considered for nonlinear stochastic systems. The controlled systems are described by nonlinear non-Gaussian difference equations with the un-modeled uncertainty and modeling error, as well as time delays. Entropy is adopted to characterize the uncertainty of the tracking error. The nonlinear multi-step-ahead predictive cost function is used and the relationship between the probability density functions of the input and the tracking error via the uncertain mapping is established. With these formulations, the cost function can be bounded as a nonlinear functional of the control input and the known bounds of the errors. Explicit design algorithms are presented for the robust suboptimal controller and further for the stabilization controllers. The Renyi's entropy has also been used to simplify the cost function. Simulations are given to demonstrate the effectiveness of the proposed control algorithm.

title: Minimum entropy control of nonlinear ARMA systems over a communication network
abstract: In this paper, the entropy concept has been utilized to characterize the uncertainty of the tracking error for nonlinear ARMA stochastic systems over a communication network, where time delays in the communication channels are of random nature. A recursive optimization solution has been developed. In addition, an alternative algorithm is also proposed based on the probability density function of the tracking error, which is estimated by a neural network. Finally, a simulation example is given to illustrate the efficiency and feasibility of the proposed approach.

title: Minimizing Area Cost of On-Chip Cache Memories by Caching Address Tags
abstract: This paper presents a technique for minimizing chip-area cost of implementing an on-chip cache memory of microprocessors. The main idea of the technique is Caching Address Tags, or CAT cache, for short. The CAT cache exploits locality property that exists among addresses of memory references. By keeping only a limited number of distinct tags of cached data, rather than having as many tags as cache lines, the CAT cache can reduce the cost of implementing tag memory by an order of magnitude without noticeable performance difference from ordinary caches. Therefore, CAT represents another level of caching for cache memories. Simulation experiments are carried out to evaluate performance of CAT cache as compared to existing caches. Performance results of SPEC92 programs show that the CAT cache, with only a few tag entries, performs as well as ordinary caches, while chip-area saving is significant. Such area saving will increase as the address space of a processor increases. By allocating the saved chip-area for larger cache capacity, or more powerful functional units, CAT is expected to have a great impact on overall system performance.

title: A Workflow Management Mechanism for Peer-to-Peer Computing Platforms
abstract: This paper proposes a workflow management mechanism to address a neglected aspect of existing P2P computing platforms – the lack of support for various computational models. In the workflow management mechanism, a workflow description file is used to define the workflow diagram of the target application. We develop a prototype system, and evaluate it using a test program to demonstrate how the workflow management mechanism effectively works.

title: Processor Performance Modeling using Symbolic Simulation
abstract: We propose a method of analytically characterizing processor performance as a function of circuit latencies. In our approach, we modify traditional simulation to use variables instead of fixed latencies for the internal functional units. The simulation engine then algebraically computes execution times, and the result is a mathematical equation which characterizes the performance space across numerous processor configurations. We discuss the computational complexity issues of this approach and show that instruction chunking and simple equation redundancy checking can make this approach feasible-we can model a large multi-dimensional design space with thousands to millions of design parameter combinations for about 10times the simulation time of a single conventional simulation run. We demonstrate our approach by exploring two different machines: a traditional MlPS-style in-order pipeline and the Intel Graphics

title: A Fast and Robust Ellipse Detection Algorithm Based on Pseudo-random Sample Consensus
abstract: Ellipse is one of the most common features that appears in images. Over years in research, real-timing and robustness have been two very challenging problems aspects of ellipse detection. Aiming to tackle them both, we propose an ellipse detection algorithm based on pseudo-random sample consensus (PRANSAC). In PRANSAC we improve a contour-based ellipse detection algorithm (CBED), which was presented in our previous work. In addition, the parallel thinning algorithm is employed to eliminate useless feature points, which increases the time efficiency of our detection algorithm. In order to further speed up, a 3-point ellipse fitting method is introduced. In terms of robustness, a "robust candidate sequence" is proposed to improve the robustness performance of our detection algorithm. Compared with the state-of-the-art ellipse detection algorithms, experimental results based on real application images show that significant improvements in time efficiency and performance robustness of the proposed algorithm have been achieved.

title: EXOCHI: architecture and programming environment for a heterogeneous multi-core multithreaded system
abstract: Future mainstream microprocessors will likely integrate specialized accelerators, such as GPUs, onto a single die to achieve better performance and power efficiency. However, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature ISAs and functionality that are significantly different from the general purpose CPU cores. In this paper, we present EXOCHI: (1) Exoskeleton Sequencer(EXO), an architecture to represent heterogeneous acceleratorsas ISA-based MIMD architecture resources, and a shared virtual memory heterogeneous multithreaded program execution model that tightly couples specialized accelerator cores with generalpurpose CPU cores, and (2) C for Heterogeneous Integration(CHI), an integrated C/C++ programming environment that supports accelerator-specific inline assembly and domain-specific languages. The CHI compiler extends the OpenMP pragma for heterogeneous multithreading programming, and produces a single fat binary with code sections corresponding to different instruction sets. The runtime can judiciously spread parallel computation across the heterogeneous cores to optimize performance and power.
 We have prototyped the EXO architecture on a physical heterogeneous platform consisting of an Intel® Core™ 2 Duo processor and an 8-core 32-thread Intel® Graphics Media Accelerator X3000. In addition, we have implemented the CHI integrated programming environment with the Intel® C++ Compiler, runtime toolset, and debugger. On the EXO prototype system, we have enhanced a suite of production-quality media kernels for video and image processing to utilize the accelerator through the CHI programming interface, achieving significant speedup (1.41X to10.97X) over execution on the IA32 CPU alone.