动态矩阵算法在大时滞环节中的应用

介绍一个电阻炉炉温微机控制系统,并采用动态矩阵控制算法设计了预测控制器。由于电阻炉炉温系统是一个纯滞后大惯性环节,其参数整定与常规对象有所不同。通过合适的参数设计,该控制器达到了较好的性能,实际运行结果表明,该控制器具有良好的控制特性。     

Cloud Neural Fuzzy PID Hybrid Integrated Algorithm of Flatness Control

In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neural network and fuzzy integration. By indeterminacy artificial intelligence, the problem of fixing the membership functions of input variables and fuzzy rules was solved in an actual fuzzy system and the nonlinear mapping between variables was implemented by neural network. The algorithm has the adaptive learning ability of neural network and the indetermi- nacy of a cloud model in processing knowledge, which makes the fuzzy system have more persuasion in the process of knowledge inference, realizing the online adaptive regulation of PID parameters and avoiding the defects of the traditional PID controller. Simulation results show that the algorithm is simple, fast and robust with good control performance and application value.     

Active Pulse Structural Control Using Artificial Neural Networks

Increasing interest has focused on applying active control systems to civil engineering structures subjected to dynamic loading. This study presents an active pulse control algorithm, termed the adaptive neural structural active pulse (ANSAP) controller, to control civil engineering structures under dynamic loading. The ANSAP controller minimizes structural cumulative responses during earthquakes by applying active pulse control forces. The effect of pulses is assumed to be delayed until just before the next sampling time so that the control force can be calculated in time and applied; the newly developed control strategy circumvents the effect of time delay due to the computation time. The ANSAP controller also circumvents the difficulty of obtaining system parameters of a real structure for the algorithm for active structural control. Illustrative examples reveal significant reductions in cumulative structural responses, which demonstrates the feasibility of using the adaptive artificial network for controlling civil engineering structures under dynamic loading.     

Robust Adaptive Control for Mobile Manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and thc convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.     

基于RBFNN在线辨识的自适应PID预焙阳极焙烧炉温度控制

针对工况变化频繁的焙烧炉焙烧过程,提出了采用基于径向基函数(RBF)神经网络(NN)在线辨识的自适应PID控制策略。该方法通过RBF神经网络的自学习能力在线辨识系统模型,进而获得被控对象的Jacobian信息,实现对PID参数的在线调整。在对算法进行改进的基础上将其应用于预焙阳极焙烧炉温度过程控制中,实验结果表明,该方法具有很强的自适应能力和鲁棒性,达到了满意的控制效果。     

冷轧机机架间张力预测函数控制器的设计

由于常规PID控制器的参数往往针对一种情况进行整定,很难保持冷连轧张力始终处于一个好的控制状态。在分析了张力控制原理的基础上,应用预测函数控制设计了辊缝式调张法张力控制系统,用预测函数控制,其控制量计算方程简单,实时控制计算量小,达到了张力控制的精度要求,仿真结果证明了该控制器显著提高了系统的动态响应性能,其控制效果优于常规PID控制器。     

模糊预测控制在电阻炉温度控制中的应用

利用模糊控制对对象模型要求低、响应速度快、预测控制的超前性的特点,设计了模糊预测控制器来对电阻炉温度进行控制。仿真结果表明,此方法增强了系统的跟踪性,对纯滞后具有较好的补偿作用,对被控参数具有较强的适应能力,比传统的控制方法精度高、速度快、控制质量优良。     

Closed Loop Predictive Optimal Control Algorithm Using ARMA Models

A predictive optimal control algorithm based on auto-regressive moving average (ARMA) models has been developed. Being a closed loop algorithm, it can be used in the control of structures against any source of random excitation without any special arrangement for measuring the excitation. The algorithm combines two mathematical models: (1) An ARMA model representing the environment and the structure as a single system subjected to the unknown random excitation; and (2) a single-degree-of-freedom system, which represents the structure subjected to a known history of control force only. Unlike some ARMA based control algorithms, which are only for seismic excitations, the proposed algorithm permits the control system to be operational under any type of dynamic load. This results in a large reduction in the standby time of the control system and increases its reliability. In comparison with these algorithms, the proposed algorithm requires less measurements and sensors. The algorithm has the option for reducing or avoiding time delay.     

基于模糊神经解耦控制的板型板厚控制系统仿真

面对板型板厚控制这一复杂、多变量耦合的非线性系统,本文提出了一种两级串联结构的模糊神经网络解耦控制策略,前级为自调整模糊控制器,后级为基于动态耦合特性的自适应神经网络解耦控制器,并从理论上证明了学习算法的收敛性。实现了无模型板型板厚综合控制。仿真结果表明,该控制系统收敛性好、抗干扰性强,取得令人满意的板型板厚控制精度。     

Adaptive Dynamic Surface Control for Integrated Missile Guidance and Autopilot

Integrated guidance and control for homing missiles utilizing adaptive dynamic surface control approach is considered based on the three channels independence design idea.A time-varying integrated guidance and control model with unmatched uncertainties is first formulated for the pitch channel, and an adaptive dynamic surface control algorithm is further developed to deal with these unmatched uncertainties.It is proved that the proposed feedback controller can ensure not only the accuracy of target interception,but also the stability of the missile dynamics.Then, the same control approach is further applied to the control design of the yaw and roll channels.The 6-degree-of-freedom (6-DOF) nonlinear missile simulation results demonstrate the feasibility and advantage of the proposed integrated guidance and control design scheme.     

采用Smith预估低通滤波补偿的AGC控制系统

作为现代轧机核心技术的板厚控制系统,其性能直接决定了轧制产品质量,提高该系统的控制性能具有重要意义。为此,建立了考虑延时环节的板厚控制模型,通过在Smith预估控制器的反馈回路串接低通滤波器对系统进行预估控制,用来对控制器进行补偿,以提高控制系统鲁棒性。针对改进后系统可调参数多,参数调整困难的问题,提出通过遗传算法程序进行PI控制器及滤波补偿器参数的整定。仿真研究结果表明,基于遗传算法参数寻优的Smith预估控制器低通滤波补偿算法提高了系统鲁棒性和系统控制精度,达到了期望的控制性能。     

120t转炉自动控制系统研究

介绍了120t转炉自动化控制系统,阐述了PLC控制、PROFIBUS-DP网、工业以太网、西门子变频器技术以及基础自动化方面的情况。     

基于LQR-QPSO的地下铲运机控制参数优化研究

现代控制理论是实现地下铲运机路径跟踪控制的重要技术之一。目前,控制算法应用的难点在于参数的选取和整定。为解决控制参数整定问题,提出应用量子行为粒子群优化算法（QPSO）对基于线性二次型调节（LQR）的状态反馈控制器进行参数优化,实现对地下铲运机精准、稳定的路径跟踪控制。状态反馈控制器基于铲运机的误差动力学模型得出,优化后的路径跟踪控制最大横向位置偏差低于0.23 m。仿真试验结果表明：相较于标准粒子群优化算法,QPSO算法优化的路径跟踪控制器的最大横向位置偏差减小53.4%,优化效果更好、成功率更高。     

Approach of Synthesizing Model Predictive Control and Its Applications for Rotary Kiln Calcination Process

An actual control demand of rotary kiln is taken as background. By analyzing and improving approach of S-MPC (synthesizing model predictive control), an effective strategy which applies complex S-MPC in actual industrial process is designed. Firstly, after analyzing the main components technology and calcination reaction mechanism in detail, the calcining belt state-space model of rotary kiln is built using PO-Moesp (past-output multivariable output error state space model identification) method. Then, calcining belt temperature predictive control system is designed. The control system combines time-delay gain scheduled, output-tracking, recursive subspace adaptive and other methods, and forms the off-line/on-line predictive controller of rotary kiln. At last, MATLAB is applied for simulation, experiments run in constant value tracking and servo tracking situation. Simulation results show its effectiveness and feasibility.     

Automatic Downstream Water-Level Feedback Control of Branching Canal Networks: Simulation Results

Previous research on canal automation has dealt with the control of single, in-line canals, while canal operators typically have to control an entire network of canals. Because the branches in a network are hydraulically coupled with each other, control of a branching canal network based on separate controllers for each branch may not be the most effective control strategy. A methodology by which existing automatic control systems could be modified to control branching canal networks is provided in a companion paper. This paper presents results of hydraulic simulations of the new methodology to estimate the controllability of a large portion of the branching canal network operated by the Salt River Project (SRP). Two types of controllers were used for this study: (1) linear quadratic regulator (LQR) and (2) model predictive control (MPC). Both controllers used the same underlying process model [integrator-delay (ID) model], and both controllers were capable of feedback and feedforward control. Under feedback control alone, both controllers gave similar performance, but were unable to effectively control the overall system because of the long delay times. When feedforward control was added to the feedback controller, both of these control systems were able to effectively control the branching canal network operated by SRP. For the LQR controller, the volume compensation method for routing known demand change was used as the feedforward controller. For the MPC controller, the ID model was used as the feedforward controller. Slight differences were noted between the performance of the two feedforward controllers.     

无人直升机自抗扰自适应轨迹跟踪混合控制

为满足无人直升机高精度轨迹跟踪的控制需求,并降低直升机动力学模型误差对飞行控制器飞行控制效果产生的影响,提出自抗扰自适应直升机混合控制.该控制器的内环控制采用模型跟随自适应控制,通过使用动量反向传播算法(MOBP)对该内环控制参数进行实时优化.通过使用自抗扰控制(ADRC)对直升机的水平速度进行控制.仿真结果表明,该混合控制器能够实现直升机对预定轨迹的跟踪.相对PID和级联ADRC控制,该控制器具有更好的抗扰性和鲁棒性.通过在200 kg级的专业植保无人直升机XV-2上搭载所提出的控制器,使其自主飞行轨迹跟踪控制的均方根误差在0.6 m以内.      

Performance of Model Predictive Control on ASCE Test Canal 1

Model predictive control (MPC) is a popular control algorithm in the process control industry that is particularly suited to the automatic control of irrigation water delivery systems because it explicitly accounts for the long delay times encountered in open-channel flow. In addition, a feedforward routine is easy to implement in MPC and many of the constraints that canal operators face can be directly incorporated into the MPC scheme. The ASCE Task Committee on Canal Automation Algorithms developed a series of test cases to evaluate the performance of canal control algorithms. In this paper, simulation tests were performed on ASCE test canal 1 using a remote downstream control configuration of MPC. The MPC algorithm effectively controls ASCE test canal 1, and its performance was similar to that of other proposed controllers. When there were no minimum gate movement constraints, MPC was fairly robust because the controller performance did not significantly degrade under untuned conditions. In the presence of minimum gate movement constraints, the water levels continually oscillate around the water level setpoint. Using the configuration presented in this paper, the feedforward portion of MPC does not perform as well as other proposed feedforward routines. This underperformance is related to the simplifications made by the underlying process model and not to MPC itself.     

Cerebellar Model Articulation Controller (CMAC) for Suppression of Structural Vibration

Applicability of the cerebellar model articulation controller (CMAC) to structural control is explored, and a training algorithm for the suppression of structural vibration is proposed. The training epochs and controlled responses by both the CMAC and the well-known multilayer neural network are compared in the numerical example. The dynamics of the hydraulic actuator and the time delay of the controller are considered in the simulation. It is concluded that the CMAC is a promising candidate for a structural controller.     

Predictive Optimal Linear Control of Elastic Structures during Earthquake. Part I

A predictive optimal linear control (POLC) algorithm is proposed for controlling the seismic responses of elastic structures. This algorithm compensates for time delay that occurs in real control application by predicting the structural response in the classical optimal linear control equation. The unique feature of this proposed POLC algorithm is that it compensates for time delay very effectively over a very wide range of time delay magnitudes. Numerical examples of single-degree-of-freedom structures are presented to study the performance of the proposed POLC system for various time delay magnitudes. Results show that a time delay always causes degradation of control efficiency, and POLC can greatly reduce this degradation. The effects of natural periods and damping of the structure, different earthquake characteristics and numerical integration schemes, and choices of control gains on the degradation induced by time delay are carefully studied in the analysis. Results show that using a larger time delay magnitude may give smaller structural responses, and this magnitude is independent of earthquake characteristics but dependent on the control gains. Finally, practical application of POLC is performed on a six-story moment-resisting steel frame. It is demonstrated that POLC maintains stability in multi-degree-of-freedom structures and at the same time it has a satisfactory control performance.     

PLC在龙钢400m^2烧结系统中的应用

陕西龙钢集团400m2烧结控制系统采用稳定的集散型PLC实现分布式环网控制,PLC从站之间采用支持热插拔的分布式I/O用于连接工业控制系统中各种现场装置,上位机PLC之间通讯采用工业以太环网结构。该系统应用后,运行情况良好,产量显著提高,降低了能耗,实现了工厂网络化、信息化。