Integrated Auto-Tuning PID Control of Continuous Casting Process

PID controllers were used for the hydraulic servo system of sliding gate and the tundish weight control system in continuous caster.These two loops were synthesized in mould level controller based on model reduction and internal model control strategy.Satisfactory control performance of this synthetic mould level controller was demonstrated by simulations and on-line experiments.

Vibration energy harvesting for low frequency using auto-tuning parametric rolling pendulum under exogenous multi-frequency excitations

An electromagnetic parametrically excited rolling pendulum energy harvester with self-tuning mechanisms subject to multi-frequency excitation is proposed and investigated in this paper.The system consists of two uncoupled rolling pendulum.The resonance frequency of each the rolling pendulum can be automatically tuned by adjusting its geometric parameters to access parametric resonance.This harvester can be used to harvest the energy at low frequency.A prototype is developed and evaluated.Its mathematical model is derived.A cam with rolling follower mechanism is employed to generate multi-frequency excitation.An experimental study is conducted to validate the proposed concept.The experimental results are confirmed by the numerical results.The harvester is successfully tuned when the angular velocity of the cam is changed from 1.149 to 1.236 Hz.

Sliding Mode Control with Auto-Tuning Law for Maglev System

This paper presents a control strategy for maglev system based on the sliding mode controller with auto-tuning law. The designed adaptive controller will replace the conventional sliding mode control (SMC) to eliminate the chattering resulting from the SMC. The stability of maglev system is ensured based on the Lyapunov theory. Simulation results verify the effectiveness of the proposed method. In addition, the advantages of the proposed controller are indicated in comparison with a traditional sliding mode controller.

SHA: QoS-Aware Software and Hardware Auto-Tuning for Database Systems

While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.

MPFFT：An Auto-Tuning FFT Library for OpenCL GPUs

Fourier methods have revolutionized many fields of science and engineering, such as astronomy, medical imaging, seismology and spectroscopy, and the fast Fourier transform （FFT） is a computationally efficient method of generating a Fourier transform. The emerging class of high performance computing architectures, such as GPU, seeks to achieve much higher performance and efficiency by exposing a hierarchy of distinct memories to software. However, the complexity of GPU programming poses a significant challenge to developers. In this paper, we propose an automatic performance tuning framework for FFT on various OpenCL GPUs, and implement a high performance library named MPFFT based on this framework. For power-of-two length FFTs, our library substantially outperforms the cIAmdFft library on AMD GPUs and achieves comparable performance as the CUFFT library on NVIDIA GPUs. Furthermore, our library also supports non-power-of-two size. For 3D non-power-of-two FFTs, our library delivers 1.5x to 28x faster than FFTYV with 4 threads and 20.01x average speedup over CUFFT 4.0 on Tesla C2050.

Auto-tuning of FOPI Controllers for TITO Processes with Experimental Validation

In this paper, the auto-tuning of a fractional order proportional and integral(FOPI) controller is proposed and experimentally validated for two-input two-output(TITO) processes. The proposed method first identifies an unknown TITO plant into fractional order TITO model with time delay. Furthermore, decoupling the TITO process into two fractional order single-input single-output(SISO) transfer function models makes it easier for designing the decentralized FOPI controllers. The proposed control method is a generalization of both integer order and fractional order TITO systems depending on the value of the order of the model. One advantage of this method is the non-requirement of a-priori information of gain and phase crossover frequencies of the system while tuning the controllers. The proposed algorithm is validated both by simulation of a class of TITO process models as well as by experimental analysis of a coupled tank system(CTS).

PI controller relay auto-tuning using delay and phase margin in PMSM drives

This paper presents an auto-tuning method for a proportion plus integral（PI） controller for permanent magnet synchronous motor（PMSM） drives, which is supposed to be embedded in electro-mechanical actuator（EMA） control module in aircraft. The method, based on a relay feedback with variable delay time, explores different critical points of the system frequency response.The Nyquist points of the plant can then be derived from the delay time and filter time constant.The coefficients of the PI controller can then be obtained by calculation while shifting the Nyquist point to a specific position to obtain the required phase margin. The major advantage of the autotuning method is that it can provide a series of tuning results for different system bandwidths and damping ratios, corresponding to the specification for delay time and phase margin. Simulation and experimental results for the PMSM controller verify the performance of both the current loop and the speed loop auto-tuning.

Auto-Tuning Parameters of Fractional PID Controller Design for Air-Conditioning Fan Coil Unit

The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintain a steady indoor temperature in summer and winter,the control quality cannot meet the related requirements of air-conditioning automation,such as large overshoot,large steady state error.long regulating time,etc.In view of these factors,this paper develops a fractional order PID controller to deal with such problem associated with FCU.Then,by varving mutation factor and crossover rate of basic differential evolution algorithmadaptivelv,a modified differential evolution algorithm(MDEA)is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller.This fractional order PID coutrol system is configured and the corresponding mumerical simulation is conducted by means of MATLAB software.The results indicate that the proposed fractional order PID control svstem and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.

异构HPL算法中CPU端高性能BLAS库优化

异构HPL(high-performance Linpack)效率的提高需要充分发挥加速部件和通用CPU计算能力,加速部件集成了更多的计算核心,负责主要的计算,通用CPU负责任务调度的同时也参与计算.在合理划分任务、平衡负载的前提下,优化CPU端计算性能对整体效率的提升尤为重要.针对具体平台体系结构特点对BLAS(basic linear algebra subprograms)函数进行优化往往可以更加充分地利用通用CPU计算能力,提高系统整体效率.BLIS(BLAS-like library instantiation software)算法库是开源的BLAS函数框架,具有易开发、易移植和模块化等优点.基于异构系统平台体系结构以及HPL算法特点,充分利用三级缓存、向量化指令和多线程并行等技术手段优化CPU端调用的各级BLAS函数,应用auto-tuning技术优化矩阵分块参数,从而形成了异构环境下优化的BLIS算法库HBLIS.与MKL相比,HPL整体性能提高了11.8%.

Infinity Norm Measurement of Sensitivity for Closed-Loop Systems Using Chirp as Excitation

A simple identification method based on a closed-loop experiment is proposed to measure the infinity norm of sensitivity function.A chirp signal,modified to have desired band-limited characteristic and finite duration,is used as the excitation in the experiment,and the sensitivity function is calculated using Fourier transform of input and error signals before the infinity norm is evaluated through maximization of the magnitude of sensitivity function.With an additional feature of providing values of gain margin and phase margin at a little extra effort,this method can be used in the identification step of a controller auto-tuning procedure,as having been supported by simulation results showing its capability of providing fast and accurate estimates for a large variety of processes.

基于MapReduce的混合连接算法

运行在Hadoop上的数据仓库Hive可以让更多的用户通过SQL接口来处理Hadoop数据。然而,Hive却没有为连接操作提供有效的途径,而连接操作是一种常见且在Hadoop中非常费时的操作。为了解决连接操作在Hadoop中性能的问题,本文提出一种混合策略的连接算法HJ-A,根据当前应用场景在几种连接算法之间选择相对较合适的算法,实验结果表明,HJ-A可以在大多数的Hadoop场景中发挥很好的性能。

Design of FOPI Controller for Time Delay Systems and Its Experimental Validation

In this paper,we report on the identification and modeling of unknown and higher order processes into first order plus dead time(FOPDT)plants based on the limit cycle information obtained from a single relay feedback test with an online fractional order proportional integral(FOPI)controller.The parameters of the test processes are accurately determined by the state space method while the FOPI controller settings are re-tuned to achieve enhanced performance based on the identified model parameters based on the balancedtuning method.A new performance index,integral time fractional order absolute error(ITFIAE)is introduced in this paper for balanced tuning of fractional order(FO)controllers.It requires minimum design specifications without a-priori knowledge of gain and phase crossover frequencies and is done non-iteratively without disrupting the closed loop.Four test processes and experimental analysis on a coupled tank system(CTS)validate the theory proposed.

WATuning:A Workload-Aware Tuning System with Attention-Based Deep Reinforcement Learning

Configuration tuning is essential to optimize the performance of systems(e.g.,databases,key-value stores).High performance usually indicates high throughput and low latency.At present,most of the tuning tasks of systems are performed artificially(e.g.,by database administrators),but it is hard for them to achieve high performance through tuning in various types of systems and in various environments.In recent years,there have been some studies on tuning traditional database systems,but all these methods have some limitations.In this article,we put forward a tuning system based on attention-based deep reinforcement learning named WATuning,which can adapt to the changes of workload characteristics and optimize the system performance efficiently and effectively.Firstly,we design the core algorithm named ATT-Tune for WATuning to achieve the tuning task of systems.The algorithm uses workload characteristics to generate a weight matrix and acts on the internal metrics of systems,and then ATT-Tune uses the internal metrics with weight values assigned to select the appropriate configuration.Secondly,WATuning can generate multiple instance models according to the change of the workload so that it can complete targeted recommendation services for different types of workloads.Finally,WATuning can also dynamically fine-tune itself according to the constantly changing workload in practical applications so that it can better fit to the actual environment to make recommendations.The experimental results show that the throughput and the latency of WATuning are improved by 52.6%and decreased by 31%,respectively,compared with the throughput and the latency of CDBTune which is an existing optimal tuning method.

音准修正技术在现场音乐演出中的应用

2012年浙江卫视《中国好声音》与湖南卫视《我是歌手》等音乐节目火爆荧屏,将一个本是专业音乐圈内才会讨论的音准修正问题炒到了媒体头条,有人强调"真实的音乐才是好音乐"、也有人说"播出效果完美最重要",本文借此话题展开论述,除了介绍修音的技术层面以外,还从音乐美学、道德的角度阐述它在现场音乐演出中的应用和影响,以期让非专业人士清晰理解音准修整技术在现实中的运用。