自适应鲁棒最优PI控制器

提出一种具有鲁棒性能的自适应最优PI控制器, 它首先基于控制回路在正常运行操作中产生的过程输入和输出信号, 通过信号分解和频域分析在线辨识出过程对象在重要频率点的频率特性, 然后计算出可同时满足鲁棒性能指标λ和最小负载扰动特性的最优PI控制器参数, 同时控制性能可以很方便地根据实际需要通过改变鲁棒性能指标λ来调节. PI控制器的自适应过程不需要过程对象和控制器的任何先验知识, 也不需要中断控制回路的正常运行, 仿真实验表明了自适应控制器的有效性和可行性.     

基于Ziegler-Nichols频率响应方法的自适应PID控制

提出一种基于Ziegler-Nichols频率响应方法的自适应PID控制器,它通过控制回路正常运行中的过程对象输入输出数据在线辨识出过程对象重要的临界频率响应特性,然后基于Zieger-Nichols整定规则或改进的方法在线更新PID控制器参数.PID控制器的自适应过程不需要系统的任何先验知识,也不需要建立任何对象模型,可以保证控制回路始终运行在最佳状态.仿真实验表明了自适应PID控制的有效性和可行性.     

大滞后过程的P I 控制器整定

提出一种简单而有效的大滞后过程PI控制器整定方法．基于继电反馈试验,辨识出一阶加纯滞后模型,其Nyquist曲线在一个大的频率范围内接近于大滞后过程．根据有效模型并基于一种新的鲁棒性能指标,设计出PI控制器．仿真结果表明了PI控制器的有效性。     

预测PI控制器性能评价与参数整定

控制器的性能评价与参数自整定能极大的提高工业过程的控制性能,目前这个领域的研究越来越受到控制界的重视。针对大滞后过程对象控制中用到的一种预测PI控制器（PPI）,提出了一种性能评价与参数自整定方法。该方法采用一种更精确的继电辨识方法来确定过程参数,并以一种鲁棒稳定性性能指标与绝对误差积分（IAE）性能指标相结合作为性能评价与参数整定的依据。两种性能指标结合的方法,保证了控制器有较强的设定点跟踪能力和噪声抑制能力,并具有很好的鲁棒稳定性。仿真结果表明了该方法的有效性和可行性。     

冷连轧AGC 系统的自适应Smith 广义预测控制

针对冷连轧AGC 系统存在较大的时间滞后以及对象模型参数时变的特点,提出了一种自适应Smith 广义预测控制算法. 该算法用Smith 预估器来克服滞后的影响,利用激光测速仪间接测量AGC 系统的滞后时间以修 正Smith 预估器的时滞部分模型,使用渐消记忆递推最小二乘算法在线辨识对象参数来修正Smith 预估器的非时滞 部分的模型,并根据辨识得到的对象参数设计自适应广义预测控制器代替传统Smith 预估算法中的PID 控制器. 仿 真研究表明,在模型失配及干扰的情况下,该控制算法仍然具有良好的控制性能和鲁棒稳定性能.     

自适应内模控制方法在磨矿过程中的应用

针对磨矿生产过程中球磨机给矿环节存在的大滞后、大惯性、参数时变等特性,提出了一种增益自适应内模控制方法,将内模控制和对象增益参数辨识算法相结合,通过在线辨识被控对象模型的增益参数,对内模控制器和被控时象模型进行校正,以减少模型参数变化和各种干扰对系统的影响.计算机仿真和实际应用效果均表明,与常规PID控制及IMC控制效果相比,该控制方法对于阶跃响应具有超调小、响应时间快、鲁棒性能好等特点,满足磨矿生产过程对控制器性能的要求,实现了球磨机给矿环节的稳定化控制,为选矿过程综合自动化系统的实施奠定了基础.     

自适应内模控制方法在磨矿过程中的应用

针对磨矿生产过程中球磨机给矿环节存在的大滞后、大惯性、参数时变等特性,提出了一种增益自适应内模控制方法,将内模控制和对象增益参数辨识算法相结合,通过在线辨识被控对象模型的增益参数,对内模控制器和被控对象模型进行校正,以减少模型参数变化和各种干扰对系统的影响。计算机仿真和实际应用效果均表明,与常规PID控制及IMC控制效果相比,该控制方法对于阶跃响应具有超调小、响应时间快、鲁棒性能好等特点,满足磨矿生产过程对控制器性能的要求,实现了球磨机给矿环节的稳定化控制,为选矿过程综合自动化系统的实施奠定了基础。     

高阶时滞对象的预测PI(D)控制

利用频率域模型降阶理论,提出了高阶时滞对象的预测PI(D)控制器两种设计方法.一种方法是直接将高阶滞后对象在频率域内降阶为低阶滞后对象,针对低阶滞后对象设计预测PI(D)控制器;另一种方法是按照规定的性能指标设计控制器,并将该控制器在频率域内降阶为具有预测PI(D)控制器的结构形式.这两种方法设计的控制器均具有结构简单、可调参数少、参数调节方便的特点.仿真表明:在模型失配的情况下,此两类预测PI(D)控制器仍然具有良好的控制性能和鲁棒稳定性能.     

基于系统特征的自适应被动容错控制及其应用

本文在黄金分割鲁棒自适应控制器的基础上，设计了一种自适应被动容错控制器，能在线辨识对象特征模型，在线提取系统动态性能特征和故障特征，对控制系统执行机构和测量部件的某些软故障具有被动容错能力。与传统ＰＩＤ控制的对比仿真充分说明了这种控制方案的优越性。     

具有超稳定结构的鲁棒自适应控制器

针对结构和参数未知的非线性系统,提出了一种具有神经网络的超稳定鲁棒自适应控制器.控制器基于一阶线性模型,采用Popov超稳定理论设计,其建模误差由BP网在线辨识,辨识结果在前馈补偿器中加以补偿,有效地实现了鲁棒自适应控制.文中还给出了仿真结果.     

A combined FSP and reset control approach to improve the set-point tracking task of dead-time processes

This paper presents a non-linear control scheme to deal with dead-time processes, specially for systems where fast closed-loop responses are required. The control scheme is based on the combination of two control strategies appeared in the literature to deal with dead-time processes, the Filtered Smith Predictor (FSP), which is a Smith Predictor (SP) including a filter to improve the robustness; and the PI+CI, a PI with a partial reset action on the control signal when the process output reaches the reference input. In the proposed strategy, the reset action allows to achieve very small rise times with small overshoots, improving the results from FSP. On the other hand, the use of the robust predictor allows to deal with the dead-time in a better and systematic way than the existing PI+CI solutions. The improvements of the proposed control scheme are evaluated through simulations and real experiments on an industrial heat exchanger.     

A dead-time compensating PID controller structure and robust tuning

In the present paper a dead-time compensating proportional-integral-derivative (DTC–PID) controller with anti-windup action is derived. The proposed controller also can be configured as a PID controller or as a dead-time compensating PI (DTC–PI) controller. For stable, integrating and unstable processes, approximated with the first-order plus dead-time (FOPDT) model, robust tuning procedure is derived for the DTC–PI controller. Optimization of the regulatory performance of the DTC–PID controller is based on the frequency response of higher-order models, under constraints on the robustness and sensitivity to measurement noise. Excellent performance/robustness trade-off is obtained for stable, integrating and unstable processes, including dead-time, as confirmed by simulations and by experimental results obtained on a laboratory thermal process.     

一阶时滞过程的数字PI快速镇定算法

研究一阶时滞过程的数字PI镇定问题。研究表明,当闭环系统临界稳定时,实轴以外具有最小辐角的极点是临界稳定极点。通过确定临界稳定极点的位置,得到数字PI控制系统的稳定性判据。根据该稳定性判据,可以快速地确定数字PI控制系统的参数稳定域。     

A unified step response procedure for autotuning of PI controller and Smith predictor for stable processes

The step response autotuning of PI controller and Smith dead-time compensator (DTC), for stable processes, is studied in detail. A simple and effective procedure proposed is based on the first-order plus dead-time model, obtained from the step response by measuring the time to go to ten and sixty three percent of the steady-state value of the process output. The tuning formulae derived contain an adjustable parameter, with a clear meaning with respect to the performance/robustness, enabling the user to specify its value within a well defined range, in accordance with the expected range of process parameter variations and the controller used (PI or DTC). Comparison with recently proposed methods and experimental results presented confirm that high and consistent closed-loop system performance/robustness are obtained for a wide range of dynamic characteristics common to industrial processes.     

Enhancing trajectory tracking for a class of process control problems using iterative learning

A method of enhancing tracking in repetitive processes, which can be approximated by a first-order plus dead-time model is presented. Enhancement is achieved through filter-based iterative learning control (ILC). The design of the ILC parameters is conducted in frequency domain, which guarantees the convergence property in iteration domain. The filter-based ILC can be easily added to existing control systems. To clearly demonstrate the features of the proposed ILC, a water heating process under a PI controller is used as a testbed. The empirical results show improved tracking performance with iterative learning.     

Properties of optimal stochastic control systems with dead-time

Structural, stability and sensitivity properties of optimal stochastic control systems for dead-time, stable minimum phase as well as non-minimum phase processes are presented. The processes are described by rational transfer functions plus dead-times and the disturbances by rational spectral densities. It is shown that although the frequency domain design techniques guarantee asymptotically stable systems for given process and disturbance models, many of the designs might be practically unstable. Necessary and sufficient conditions that must be imposed on the design to assure practically stable optimal systems are derived. The uncertainties in the parameters and in the structure of the process model are measured by means of an ignorance function. Sufficient conditions in terms of the ignorance function, which guarantee stable design and by means of which the bounds of the uncertainties for a given design may be estimated, are stated. Conditions under which the optimal designs possess attractive relative stability properties, namely gain and phase margins of at least 2 and 60°, respectively, are stated, too. It is further shown that any optimal controller, for the type of processes discussed in this paper, may be separated into a primary controller and into a dead-time compensator where the latter is completely independent of the cost and the disturbance properties. Such a decomposition gives excellent insight into the role of the cost and the disturbance in the design. When low order process and disturbance models are used, the conventional PI and PID control laws coupled with the dead-time compensator emerge.     

An unified approach for DTC design using interactive tools

This paper presents an interactive tool for dead-time compensator design. The tool is based on an unified dead-time compensator and considers models commonly used in industrial process control. The main contribution of this work is that the proposed tool and controller are simple to analyze and tune as they are based on an unique modified structure of the Smith predictor valid for every type of dead-time process (including integrating and unstable systems). Simple frequency analysis and block diagram transformations are used together with simulations to illustrate the main problems associated to the control of dead-time processes. Several examples of typical processes are presented to illustrate the fundamental concepts associated to the control of these systems. The interactive tool is not only useful for designing and analyzing but also for training and educational purposes.     

预测PI控制系统的时滞稳定裕度

The variation of plant dead-time deeply affects the stability of the predictive PI control system. It is important for designing and applying the PPI controller to calculate the delay margin. A criterion of stability for the PPI system and the quantitive relationship among the delay margin, the time constant of the closed-loop system, and the dead-time of the model are given. A graphic algorithm to compute the delay margin is also developed. The phenomenon that there exist more than one stability delay zones is discussed. The algorithm is shown to be precise by some simulations.     

纯滞后系统的状态反馈优化设计方法

针对纯滞后对象,提出一种串级双环状态反馈控制方式,使这种对象获得较理想的控制品质。系统的设计方法包括：采用数值逼近方法将对象拟合成有理多项式,并选择一种优化的期望闭环系统,作为串级系统内外环的参考模型;根据串级内、外环不同结构分别采用开环和闭环校正,并引入状态观测器,大幅度地减少状态的检测数量;同时采用内外环系统的协调设计,拉开内外环回路的操作频率,有利于提高系统的鲁棒性。通过工业过程中的纯滞后对象进行仿真实验,证实本方法相当有效,系统动态性能和抗干扰能力明显增强。     

On the explicit dead-time compensation for robust model predictive control

Computational simplicity is one of the most important aspects to take into account in robust model predictive control (MPC). In dead-time processes, it is common to use an augmented state-space representation in order to apply robust MPC strategies but, this procedure may affect computational aspects. In this paper, explicit dead-time compensation will be used to avoid augmented representation. This technique will be analyzed in terms of robust stability and constraint satisfaction for discrete-time linear systems. The results of this discussion will be applied to a robust tube-based MPC strategy which is able to guarantee robust stability and constraint satisfaction of a dead-time system by considering a prediction model without dead-time. Moreover, taking advantage of the proposed scheme, the robust MPC will be particularized for first-order plus dead-time models which simplifies significantly controller synthesis. The proposed dead-time compensation method will be applied to different robust MPC strategies in two case studies: (i) a simulated quadruple-tank system, and (ii) an experimental scaled laboratory heater process.