《自动控制系统》课程改革的研究与实践

《自动控制系统》作为自动化专业一门实用性和工程性较强的专业主干课程,其所涉及的相应知识和技术更新较快。为了使学生更好地掌握该课程,培养学生的实践动手能力和综合应用能力,在教学过程中,应注重根据课程的发展和社会对相关知识的需求,结合人才培养方案,整合教学内容,改进教学方法和手段,加强实验实践能力的训练;充分利用课程设计与毕业设计环节,构建"理论教学+实验实践教学+课程设计+毕业设计"四位一体的课程建设体系。

“自动控制系统”课程试题库微机管理软件的研制

介绍了《自动控制系统》试题库的设计思想， 题库的组成以及微机管理系统软件的主要功能和特点。即：管理系统是在ｗｉｎｄｏｎｓ９８ 环境下， 利用ｄｅｌｐｈｉ４－０ 编程工具开发而生成的， 且具有一定的通用性， 可用于任何同类型而不同学科的试题库， 该管理系统可根据输入信息对试题进行搜寻、制作、组合、显示、打印、修改、分析、保护等操作。

粤港澳大湾区背景下电气专业课程思政建设探索与实践——以《自动控制原理与系统》为例

《自动控制原理与系统》是电气自动化技术专业开设的专业核心课程,属于必修课,课程主旨以反馈控制理论为核心,研究控制系统建模方法、线性系统的分析与设计方法及自动控制系统的工作原理、自动调节过程等。本文在粤港澳大湾区建设背景下,结合电气专业人才培养体系,以《自动控制原理与系统》课程为例,通过大湾区背景下电气专业课程思政建设路径与创新方法研究实践,旨在实现自动控制原理与系统专业课与思政育人的同向同行。

《自动控制原理与系统》课程的改革

电气自动化工程专业是我院向教育部申报成功的教学改革试点专业,按照专业教改思路和人才培养的模式,我们对《自动控制原理与系统》课程进行了改革。 一、以经典线性控制理论为主线 针对自动控制理论抽象,学生不知自控理论用于何处和怎样具体应用的问题,我们在教学中,采取了理论与实践相结合的教学方法。

A HOLONIC FRAMEWORK OF RECONFIGURABLE SHOP FLOOR CONTROL SYSTEMS IN AUTOMATED MANUFACTURING SYSTEMS

The agility and the flexibility of the current shop floor control systems have been limited so far, owing to the lack of structural flexibility and agility in its control software layer. Most of them are based on traditional hierarchical architecture and the top down approach and depend structurally on their specific configuration and job scheduling. Not only can they hardly satisfactorily adapt to these increasing changes and disturbances, but also make the redevelopment and maintenance of shop floor control system (SFCS) to need high cost and much time. And SFCS based on the heterarchical architecture don′t provide a predictable and high performance system, especially not in the heterogeneous environments, where the resources are scarce and the current decisions have serious repercussions on the future performances. For this reason, the heterarchical control is hardly applied in industry. Obviously, it is necessary to develop a new structural framework of reconfigurable SFCS to improve their agility, flexibility and maintainability. This paper presents a holonic framework of reconfigurable SFCS based on holonic manufacturing concepts. The framework is composed of resource holons, product holons and other staff holons. The model of each holon and the co operative mechanisms of holons are described. To verify the proposed approach experimentally, a prototype reconfigurable SFCS for a flexible manufacturing shop floor producing discrete parts is implemented.

Locality Improvement Technology for Auto-control System of Aquatic Seedling

[Objective] The aim was to improve part of auto-control system of aquatic seedling breeding and to lay foundation for highly-efficient and stable use of the sys- tem. [Method] The executive and drive modules of the auto-control system were im- proved, after which real-time monitor, data display and alarm modules were tested on time. [Result] In the test, for the improved system, stability and sensitivity were enhanced; different components matched better; transmitting electric resistanc6 was reduced. [Conclusion] The research provides references for auto-control of water temperature and dissolved oxygen, and faults clearing in aquatic seedling breeding.

Integrated Automation of Power Plant Electrical System

Aiming at the comparatively laggard level of power plant electrical system automation, this paper analyzes the feasibility,necessity and some key points of the application of integrated automation technology to power plant electrical system. New idea using fieldbus control system technology is presented. This paper also gives the outline and detailed schemes.

《自控》教学中重视培养学生的辩证唯物主义观点

《自控》教材中包含着丰富的辩证唯物主义思想 ,在教学中重视培养学生学会运用辩证唯物主义的观点和方法 ,更好地理解和掌握所学的知识和技能。

Current Share Control IC Design for Paralleled DC/DC Converters

To keep even current distribution among DC/DC converters in a paralleled power system,an automatic master-slave control （AMSC） current sharing scheme is presented,which was implemented by a current share control IC. A current feedback loop for output voltage adjustment is proposed for low signal distortion. Moreover,a special startup control logic is designed to improve startup timing and to speed up the initial current sharing. It was completed in 1.5μm bipolar-CMOS-DMOS （BCD） technology with an area of 3.6mm^2 . Using it,a paralleled power system of two DC/DC converters capable of outputting 12V/3A was built. Experimental results show that the current sharing error at full load is kept within 1%.

New development of longwall mining equipment based on automation and intelligent technology for thin seam coal

The paper introduced complete sets of automatic equipment and technology used in thin seam coal face, and proposed the comprehensive mechanization and automation of safe and high efficiency mining models based on the thin seam drum shearer. The key technology of short length and high power thin seam drum shearer, and new type roof support with big extension ratio and plate canopy were introduced. The new research achievement on automatic control system of complete sets of equipment for the thin seam coal, which composed of electronic-hydraulic system, compact thin seam roof supports, high effective shearer with intelligent control system, and characterized by automatical follow-up and remote control technology, was described in this paper..

Adaptive terminal sliding mode control for high-order nonlinear dynamic systems

An adaptive terminal sliding mode control (SMC) technique is proposed to deal with the tracking problem for a class of high-order nonlinear dynamic systems. It is shown that a function augmented sliding hyperplane can be used to develop a new terminal sliding mode for high-order nonlinear systems. A terminal SMC controller based on Lyapunov theory is designed to force the state variables of the closed-loop system to reach and remain on the terminal sliding mode, so that the output tracking error then converges to zero in finite time which can be set arbitrarily. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated. It is also shown that the stability of the closed-loop system can be guaranteed with the proposed control strategy. The simulation of a numerical example is provided to show the effectiveness of the new method.

Input-output approach to robust stability and stabilization for uncertain singular systems with time-varying discrete and distributed delays

Based on input-output approach, the robust stability and stabilization problems for uncertain singular systems with time-varying delays are investigated. The parameter uncertainties are assumed to be norm-bounded and the time-varying delays include both discrete delay and distributed delay. By introducing a new input-output model, the time-delay system is embedded in a family of systems with a forward system without time delay and a dynamical feedback uncertainty. A sufficient and necessary condition, which guarantees the system regular, impulse-free and stable for all admissible uncertainties, is obtained. Based on the strict linear matrix inequality, the desired robust state feedback controller is also obtained. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.

New predictive control algorithms based on Least Squares Support Vector Machines

Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built by using LS-SVM with linear kernel function, and then the obtained linear LS-SVM model is transformed into linear input-output relation of the controlled system. However, for the strongly nonlinear system, the off-line model of the controlled system is built by using LS-SVM with Radial Basis Function (RBF) kernel. The obtained nonlinear LS-SVM model is linearized at each sampling instant of system running, after which the on-line linear input-output model of the system is built. Based on the obtained linear input-output model, the Generalized Predictive Control (GPC) algorithm is employed to implement predictive control for the controlled plant in both algorithms. The simulation results after the presented algorithms were implemented in two different industrial processes model; respectively revealed the effectiveness and merit of both algorithms.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

Simulation Research on a SVPWM Control Algorithm for a Four-Leg Active Power Filter

In this paper the topology of a four-leg shunt active-power filter (APF) is given. The APF compensates har-monic and reactive power in a three-phase four-wire system. The scheme adopted for control of the four-leg active power filter,a 3-Dimensional Pulse Width Modulation (PWM) technique,is presented. The theoretical deduction of a space vector PWM (SVPWM) algorithm is given in this paper. The paper also analyzes the distribution of the volt-age-space vector of the four-leg converter in αβγ coordinates and describes methods to determine the location of the voltage-space vector and to calculate duration time. Finally,the algorithm is implemented in simulation; the results show that the total harmonic distortion (THD) of the three phase-current waveforms is reduced. The neutral wire current,after compensation,is about 0 A showing that the topology of the four-leg shunt APF is feasible and the proposed scheme is effective.

UPF based autonomous navigation scheme for deep space probe

The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then, aiming at the conditions that large initial estimation errors and non-Gaussian distribution of state or measurement errors may exist in orbit determination process of the two phases, UPF (unscented particle filter) is introduced into the navigation schemes. By tackling nonlinear and non-Gaussian problems, UPF overcomes the accuracy influence brought by the traditional EKF (extended Kalman filter), UKF (unscented Kalman filter), and PF (particle filter) schemes in approximate treatment to nonlinear and non-Gaussian state model and measurement model. The numerical simulations demonstrate the feasibility and higher accuracy of the UPF navigation scheme.

Observer-based Iterative and Repetitive Learning Control for a Class of Nonlinear Systems

In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.

Iterative Learning Control With Incomplete Information： A Survey

Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.