一种三自由度串级控制的仿真研究

关于优化控制系统性能问题,由于控制系统中存在非线性滞后各种干扰因素,严重影响响应和稳定性。为实现在线独立调节副回路设定响应与扰动抑制响应,增强主回路的抗干扰能力,改善系统性能,提出一种新的三自由度串级控制方法。在副回路中采用两自由度内模控制,主回路采用单位反馈控制结构,并根据闭环最优灵敏度函数方法确定主控制器,从而保证系统的整体性能。对各个控制器的解析建模设计,对每个控制器都可以进行单参数调节和优化,并对主回路和副回路存在的乘性不确定性进行仿真。仿真结果表明,新的控制方法具有较好的设定值跟踪性能和抗干扰能力,提高了系统的鲁棒稳定性。     

一类工业过程运行反馈优化控制方法

为了克服流程工业运行优化中控制回路闭环系统的动态误差对运行优化性能的影响,本文针 对一类工业过程提出了使运行指标实际值与目标值偏差和控制回路输出与设定值跟踪误差的二次性能 指标极小化的运行优化反馈控制方法. 该方法由运行层设定值反馈控制和回路控制层设定值跟踪控制组成,其中设定值反馈控制采用基于LMI的 模型预测控制,回路控制采用衰减率可调的带有积分项的状态反馈调节律. 本文给出了保证运行优化反馈控制闭环系统渐近稳定的充分条件,并开展了浮选过程运行优化反馈控制仿 真实验,实验结果表明所提方法的有效性.     

工业过程运行的解耦内模控制方法

工业过程运行控制的目的是实现反映过程整体运行性能的工艺指标. 将常规解耦内模控制(Internal model control, IMC)进行推广, 提出了优化过程运行的解耦IMC方法. 通过对广义解耦内模控制器的设计获得了具有高维解耦能力、鲁棒稳定性和抗干扰能力强的回路设定模型. 该模型能够响应系统的各种不确定性和干扰, 对回路设定值进行调整, 通过控制回路的输出跟踪调整后的设定值, 从而实现期望的工艺指标. 磨矿回路运行的解耦IMC设计实例及仿真验证了所提方法的有效性.     

DMC-DMC串级控制算法分析与研究

将动态矩阵控制算法与串级控制系统相结合,在串级控制的主、副回路中均采用动态矩阵控制算法(DMC)进行控制.经仿真证明,该DMC-DMC串级控制算法具有快速的动态响应,控制效果较好.     

数据驱动的复杂磨矿过程运行优化控制方法

针对赤铁矿磨矿过程的磨矿粒度（Grinding particle size,GPS）与控制回路输出之间的动态特性难以用数学模型描述,且磨矿粒度不能在线测量,并受矿石成分与性质频繁波动干扰,难以采用已有运行优化方法的难题,结合磨矿过程的特点,利用数据,采用神经网络,提出由回路预设定值优化、性能指标估计、优化设定值评价以及磨矿粒度软测量组成的数据驱动的磨矿过程运行优化控制方法. 该方法由磨矿粒度软测量估计矿浆粒度,通过回路预设定值优化模块求得使性能指标估计值接近最优值的回路预设定值,经优化设定值评估产生回路设定值,最后通过控制回路跟踪设定值,将矿浆粒度控制在目标值范围内并尽可能的接近目标值. 通过研制的运行优化与控制研究平台,采用实际运行数据进行仿真实验,表明所提方法的有效性.     

西门子主汽温度控制策略的仿真研究

火电厂的主汽温度存在大惯性、大延迟等缺陷,而常规串级控制难以取得良好的控制效果.针对以上问题,提出采用西门子公司的主汽温度控制策略控制主汽温.它是一个具有导前温度信号的双回路汽温调节系统,其内回路采用导前温度为反馈信号,通过计算进入过热器的蒸汽具有的焓值来确定喷水减温阀出口温度的设定值.仿真结果表明,此控制策略具有抗干扰能力强、对惯性和延迟适应性好等优点.     

工业过程多速率分层运行优化控制

工业过程运行优化控制通常采用基础回路层和运行层两层结构,涉及不同时间尺度特性的被控对象,且由于检测装置采样周期不同难以统一控制与采样周期;此外,运行层动态往往机理复杂难以建模.因此针对这一多层次、多时间尺度且部分模型未知的复杂多速率控制问题,本文提出一种工业过程多速率分层运行优化控制方法.该方法在使用提升技术解决分层多速率问题的基础上,采用一种基于Q-!学习的数据驱动运行层设定值优化方法,更新基础回路层的设定值;并针对提升后的系统采用模型预测控制（Model predictive control,MPC）方法设计基础回路层控制器以跟踪设定值,从而实现运行指标的优化控制.对典型工业闭路磨矿过程进行了仿真实验,验证了本文所提方法的有效性.     

加热炉炉温智能控制系统的一种设计方案

针对步进式加热妒炉温控制系统中存在时变、非线性等特征,设计了燃气、空气回路流量设定值调节系统,并在该系统中了采用RBF神经网络整定PID控制器参数;针对炉温控制系统中参数耦合和系统模型不确定的问题,分别在燃气和助燃空气回路中设计了一种基于最小二乘支持向量机(LS-SVM)的逆控制解耦系统,并对燃气和空气回路流量设定值进行动态跟踪.仿真结果表明:该步进式加热炉炉温智能控制系统具有鲁棒性好、抗干扰能力强、超调小,动态跟踪品质好和稳态精度高等特点.     

基于案例推理增强学习的磨矿过程设定值优化

磨矿粒度和循环负荷是磨矿过程产品质量与生产效率的关键运行指标,相对于底层控制偏差,回路设定值对其影响要严重的多.然而,磨矿过程受矿石成分与性质、设备状态等变化因素影响,运行工况动态时变,难以建立模型,因此难以通过传统的模型方法优化回路设定值.本文将增强学习与案例推理相结合,提出一种数据驱动的磨矿过程设定值优化方法.首先根据当前运行工况,采用基于Prey-Predator优化的案例推理方法,决策出可行的基于Elman神经网络的Q函数网络模型;然后利用实际运行数据,在增强学习的框架下,根据Q函数网络模型优化回路设定值.在基于METSIM的磨矿流程模拟系统上进行实验研究,结果表明所提方法可根据工况变化在线优化回路设定值,实现磨矿运行指标的优化控制.     

串级控制系统的PID参数自动整定算法

针对本质稳定过程，以ＦＦＴ变换为手段，通过对串级系统输入输出数据的分析，得到主、副对象的频域特性，并通过降阶得到二阶模型及其无因次时滞，给出了主、副回路ＰＩＤ参数自动整定算法及公式。仿真结果表明了其良好的跟踪及抗干扰性能。     

Control performance assessment for multivariable systems based on a modified relative variance technique

In this paper, a new technique is presented which enables the relative performance of both single and multiple loop control systems to be determined. The technique is based on the relative variance index technique which has been proposed recently for monitoring single loop control systems. This technique provides a control loop performance metric that considers the performance of the control system relative to both minimum variance and open-loop control. A major limitation with this technique is that it requires a highly restrictive assumption to be made regarding the structure of the disturbance to the process and the extension of the technique to multiple loop systems is not straight forward. The technique proposed in this paper does not require any assumptions to be made regarding the structure of the disturbance and can be extended to multiple loop situations with relative ease. The ability of the proposed technique to assess the performance of controllers applied to two simulated systems and also an industrial process is examined and it is shown that the proposed approach is superior to alternative techniques. A further benefit of the proposed technique is that it is able to provide an estimate of the potential improvement to the performance of the control loop that is achievable if the control system is retuned or redesigned.     

具有执行器故障的四旋翼无人机自适应预定性能控制

针对具有执行器故障的四旋翼无人机,提出一种自适应预定性能控制方案.首先,基于内环姿态控制及外环位置控制的双闭环控制策略,将无人机系统解耦为位置子系统和姿态子系统;其次,设计自适应控制方案,对存在的执行器故障参数进行自适应估计,有效地解决了执行器故障下无人机稳定控制问题;然后,提出一种预定性能控制策略,保证系统的暂稳态性能满足预先给定的性能指标;最后,通过仿真实例验证所提出方法的有效性.     

液压伺服系统的预测函数控制及其仿真研究

为了提高液压伺服系统的跟踪性能和鲁棒性,将预测函数控制(PFC)和PID控制的优点相结合,提出了一种PFC-PID串级控制策略.内环采用PID控制来提高抗十扰性,把内环作为外环PFC控制的广义对象,对广义对象进行拟合简化得到一阶加纯滞后系统,作为PFC的预测模型,外环采用PFC来获得良好的跟踪性能和鲁棒性.通过Matlab建模、仿真及与PID控制的比较表明,PFC-PID串级控制策略能够改善液压伺服系统的控制性能.     

A design method for indirect iterative learning control based on two-dimensional generalized predictive control algorithm

Indirect iterative learning control (ILC) facilitates the application of learning-type control strategies to the repetitive/batch/periodic processes with local feedback control already. Based on the two-dimensional generalized predictive control (2D-GPC) algorithm, a new design method is proposed in this paper for an indirect ILC system which consists of a model predictive control (MPC) in the inner loop and a simple ILC in the outer loop. The major advantage of the proposed design method is realizing an integrated optimization for the parameters of existing feedback controller and design of a simple iterative learning controller, and then ensuring the optimal control performance of the whole system in sense of 2D-GPC. From the analysis of the control law, it is found that the proposed indirect ILC law can be directly obtained from a standard GPC law and the stability and convergence of the closed-loop control system can be analyzed by a simple criterion. It is an applicable and effective solution for the application of ILC scheme to the industry processes, which can be seen clearly from the numerical simulations as well as the comparisons with the other solutions.     

基于DSP的控制力矩陀螺框架数字伺服系统

提出了一种基于TMS320F2812的单框架控制力矩陀螺外框架全数字伺服系统,通过分析控制性能的要求,确定带有电流环、速度环和位置环的三环控制方案,通过对三环的作用进行研究,应用工程化的频域设计方法设计电流环和速度环,给出位置环数字PID控制的改进方案;系统实现了低速高精度稳速控制,与模拟系统相比,控制算法更加方便,大大降低了功耗;在不同速度范围内对三环控制进行仿真和样机调试,结果表明该系统能够很好地实现框架高精度控制。     

An improved parallel cascade control structure for processes with time delay

Parallel cascade control strategies, to improve the dynamic performance of a control system, have been proposed earlier mainly for control of stable processes. In this paper, further results are presented for a new parallel cascade control structure and controller design for controlling stable, unstable or integrating processes with time delay. The design of the disturbance rejection controllers and the setpoint filter are based on loop shaping and ISE performance measures, respectively. A modified Smith predictor scheme is used in the primary loop to enhance the closed-loop performance of the system. The stabilization, robustness and performances of time delay processes are analyzed. The disturbance rejection capability of the proposed scheme is superior as compared to some existing methods. Examples are given to illustrate the usefulness of the proposed method and its superiority over some parallel cascade control schemes.     

Automated exploration of datapath and unrolling factor during power–performance tradeoff in architectural synthesis using multi-dimensional PSO algorithm

A novel algorithm for automated simultaneous exploration of datapath and Unrolling Factor (UF) during power–performance tradeoff in High Level Synthesis (HLS) using multi-dimensional particle swarm optimization (PSO) (termed as ‘M-PSO’) for control and data flow graphs (CDFGs) is presented. The major contributions of the proposed algorithm are as follows: (a) simultaneous exploration of datapath and loop UF through an integrated multi-dimensional particle encoding process using swarm intelligence; (b) an estimation model for computation of execution delay of a loop unrolled CDFG (based on a resource configuration visited) without requiring to tediously unroll the entire CDFG for the specified loop value in most cases; (c) balancing the tradeoff between power–performance metrics as well as control states and execution delay during loop unrolling; (d) sensitivity analysis of PSO parameter such as swarm size on the impact of exploration time and Quality of Results (QoR) of the proposed design space exploration (DSE) process. This analysis presented would assist the designer in pre-tuning the PSO parameters to an optimum value for achieving efficient exploration results within a quick runtime; (e) analysis of design metrics such as power, execution time and number of control steps of the global best particle found in every iteration with respect to increase/decrease in unrolling factor.The proposed approach when tested on a variety of data flow graphs (DFGs) and CDFGs indicated an average improvement in QoR of >28% and reduction in runtime of >94% compared to recent works.     

无刷直流电机的电流跟踪控制

基于无刷直流电机数学模型,采用Simulink建立了无刷直流电机调速系统的仿真模型,研究了两种电流跟踪控制技术。系统采用双闭环控制,速度环采用PI调节器,电流环分别采用滞环比较电流跟踪控制和三角波比较电流跟踪控制。对两种电流跟踪控制方案进行了仿真比较,得出的结论为高性能无刷直流电机控制器的设计提供了参考。     

基于扩张状态观测器的四旋翼无人机快速非奇异终端滑模轨迹跟踪控制

针对受多源干扰影响的四旋翼无人机系统的轨迹跟踪控制问题进行研究,充分考虑位置回路和姿态回路动态特性,提出一种全回路复合快速非奇异终端滑模轨迹跟踪控制方案.首先,通过变换将轨迹跟踪问题转化为位置回路和姿态回路的指令跟踪控制问题;然后,将各通道之间的耦合以及多源干扰影响视作集总干扰,并基于扩张状态观测器对其进行估计;接着,基于干扰估计信息和快速非奇异终端滑模控制算法,分别在位置回路和姿态回路构造复合快速非奇异终端滑模控制器;最后,基于位置回路和姿态回路虚拟控制量解得无人机真实控制量旋翼转速.仿真结果表明,所提出控制方案显著提升了四旋翼无人机轨迹跟踪的响应速度和抗干扰性能.