离散非线性系统开闭环P型迭代学习控制律及其收敛性

本文在讨论了一般开环与闭环迭代学习控制的不足后，针对一类离散非线性系统，提出了新的开闭环ＰＧ型迭代学习控制律，给出了它的收敛性证明，仿真结果表明：开闭环Ｐ型迭代律优于单纯的开环或产才环Ｐ型迭代 律。     

Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators

In this paper, an open-loop PD-type iterative learning control (ILC) scheme is first proposed for two kinds of distributed parameter systems (DPSs) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained. Finally, one numerical example for a distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.      

Application of an iterative identification for control scheme to a neutralization process

In this paper an iterative scheme for identification and control is discussed. During the identification step a plant model which is suitable for the subsequent controller design step is obtained by estimation of the (dual) Youla-parameter from measurements of the input and output of the plant. Using the identified plant model, the frequency response of the ideal controller which perfectly realizes the desired closed-loop response for set-point changes is computed. This controller, in general, may not be realizable or is of high-order. A realizable, low-order controller is then calculated using frequency-weighted approximation. These steps are repeated until the performance of the closed-loop system is satisfactory or cannot be improved further. The proposed scheme is applied successfully to the identification and control of a continuous neutralization reactor.     

一类输出饱和系统的学习控制算法研究

传感器饱和是控制系统中较为常见的一种物理约束. 本文针对一类含饱和输出的受限系统, 提出了两种学习控制算法. 具体而言, 首先, 对于重复运行的被控系统, 设计了开环P型迭代学习控制器, 实现在有限时间区间内对期望轨迹的完全跟踪, 并在λ范数意义下分析了算法的收敛性, 给出了含饱和输出的迭代学习控制系统的收敛条件. 进而, 针对期望轨迹为周期信号的被控系统, 提出了闭环P型重复学习控制算法, 并分析了这类系统的收敛性条件. 最后, 通过一个仿真实例验证了本文所提算法的有效性.     

Closed-loop identification: a two step approach

The accuracy aspects of identification (with respect to both variance and bias of estimates) and the role of filtering in closed-loop identification is discussed in this paper. It is shown that the key difference between closed-loop and open-loop identification is the existence of the sensitivity function. A closed-loop identification algorithm which asymptotically yields the same expressions as open-loop identification, in both variance and bias errors, is proposed. The proposed algorithm is evaluated by simulated examples as well as experiments performed on a computer-interfaced pilot-scale process.     

An approach to polynomial NARX/NARMAX systems identification in a closed-loop with variable structure control

Many physical processes have nonlinear behavior which can be well represented by a polynomial NARX or NARMAX model. The identification of such models has been widely explored in literature. The majority of these approaches are for the open-loop identification. However, for reasons such as safety and production restrictions, open-loop identification cannot always be done. In such cases, closed-loop identification is necessary. This paper presents a two-step approach to closed-loop identification of the polynomial NARX/NARMAX systems with variable structure control （VSC）. First, a genetic algorithm （GA） is used to maximize the similarity of VSC signal to white noise by tuning the switching function parameters. Second, the system is simulated again and its parameters are estimated by an algorithm of the least square （LS） family. Finally, simulation examples are given to show the validity of the proposed approach.     

On closed-loop system identification using polyspectral analysis given noisy input–output time-domain data

The problem of closed-loop system identification given noisy input–output measurements is considered. It is assumed that the closed-loop system operates under an external non-Gaussian input which is not measured. If the external input has non-vanishing integrated bispectrum (IB) and data IB is used for identification, then the various disturbances/noise processes affecting the system are assumed to be zero-mean stationary with vanishing IB. If the external input has non-vanishing integrated trispectrum (IT) and data IT is used for identification, then the various disturbances/noise processes affecting the system are assumed to be zero-mean stationary Gaussian. Noisy measurements of the (direct) input and output of the plant are assumed to be available. The closed-loop system must be stable but it is allowed to be unstable in open loop. Parametric modeling of the various noise sequences affecting the system is not needed. First the open-loop transfer function is estimated using the integrated polyspectrum and cross-polyspectrum of the time-domain input–output measurements. Then two existing techniques for parametric system identification given consistent estimates of the underlying transfer function, are exploited. The parameter estimators are strongly consistent. Asymptotic performance analysis is also carried out. A computer simulation example using an unstable open-loop system is presented to illustrate the proposed approach.     

LQ regulator design method for system with delay based on spectral decomposition of the hamiltonian

A design method to construct an LQ regulator for a system with time-delay is proposed. It is based on a new technique for composing the solution of an infinite-dimensional Riccati equation using the spectral decomposition of the hamiltonian. This design method has the feature that the closed-loop poles can be calculated a priori from the open-loop poles and one scalar design parameter, so that we can choose the parameter to obtain an optimal control law which results in the desired degree of exponential stability of the closed-loop system.     

迭代学习控制与二维分析

本文探讨了在学习时间有限和元情形下用二维系统方法分析迭代学习控制的可能性，给出线性离散系统在开环与闭环学习中各种学习律下的稳定与收敛的充要条件，并比较了各种学习律的收敛速度，指出随着学习次数的增加，在一定条件下，Ｐ型学习与其它类型的学习算法具有相同的收敛速度。     

Twisting Sliding Mode Control of an Electrostatic MEMS Micromirror for a Laser Scanning System

In this paper, we present a twisting control scheme with proportional-integral-derivative (PID) sliding surface for a two-axis electrostatic torsional micromirror, and the utilization of the proposed scheme in a laser scanning system. The experimental results of set-point regulation verify that the proposed scheme provides enhanced transient response and positioning performance as compared to traditional sliding mode control. To evaluate the tracking performance of the closed-loop system, triangular waves with different frequencies are used as desired traces. With the proposed scheme the experimental results verified that the closed-loop controlled micromirror follows the given triangular trajectories precisely. A micromirror-based laser scanning system is developed to obtain images. When compared with open-loop control, the experimental results demonstrated that the proposed scheme is able to reduce the distortion of the raster scan, and improve the imaging performance in the presence of cross-coupling effect.      

油田电泵井自动控制系统的研究与应用

针对大港油田电泵井都为开环控制的现状,提出对电泵井进行闭环自动控制,现场试验安装电泵井井下参数采集系统、地面变频控制系统和数据处理系统,并完成电泵井自动控制算法设计,实现了对电泵井的自动控制。现场应用表明,该方法有效克服了电泵井开环控制存在的诸多问题,确保了供产液的平衡,有效保证油井长期稳定开采,同时远程控制进一步降低了工人的劳动强度、提高了数字化油田的水平,取得了很好的实际应用效果。     

Migrating from target-controlled infusion to closed-loop control in general anaesthesia

The target-controlled infusion (TCI) technique has been successfully and commercially used in clinical general anaesthesia with the intravenous anaesthetic agent propofol. The technique is based on a population pharmacokinetic model and is an open-loop control system. Closed-loop control requires a reliable and consistent signal for feedback utilisation. With all anaesthetic agents the somatosensory evoked potentials (SEP) have been shown to give increased latency as anaesthetic depth is increased. Using infusion rate and SEP response data from rats anaesthetised with propofol a mathematical model was derived to describe the anaesthetic process. This model was used as a design reference to develop a proportional integral (PI) closed-loop control system using SEP as the feedback measure. A serials of 10 trials were conducted to investigate the difference between continuous bolus injection and infusion, all under closed-loop control. The trials showed that the use of SEPs in closed-loop control of anaesthesia is feasible.     

Iterative learning controllers with time-varying gains for large-scale industrial processes to track trajectories with different magnitudes

In this article, a set of decentralised open-loop and closed-loop iterative learning controllers are embedded into the procedure of steady-state hierarchical optimisation utilising feedback information for large-scale industrial processes. The task of the learning controllers is to generate a sequence of upgraded control inputs iteratively to take responsibility for sequential step function-type control decisions, each of which is determined by the steady-state optimisation layer and then imposed on the real system for feedback information. In the learning control scheme, the learning gains are designated to be time-varying which are adjusted by virtue of expertise experiences-based IF-THEN rules, and the magnitudes of the learning control inputs are amplified by the sequential step function-type control decisions. The aim of learning schemes is to further effectively improve the transient performance. The convergence of the updating laws is deduced in the sense of Lebesgue 1-norm by taking advantage of the Hausdorff–Young inequality of convolution integral and the Hoelder inequality of Lebesgue norm. Numerical simulations manifest that both the open-loop and the closed-loop time-varying learning gain-based schemes can effectively decrease the overshoot, accelerate the rising speed and shorten the settling time, etc.     

Accurate identification for control: the necessity of an iterativescheme

If approximate identification and model-based control design are used to accomplish a high-performance control system, then the two procedures must be treated as a joint problem. Solving this joint problem by means of separate identification and control design procedures practically entails an iterative scheme. A frequency-response identification technique and a robust control design method are used to set up such an iterative scheme. Each identification step uses the previously designed controller to obtain new data from the plant. The associated identification problem has been solved by means of a coprime factorization of the unknown plant. The technique's utility is illustrated by an example     

基于改进IMC的开环不稳定时滞过程控制

针对开环不稳定对象,在传统内模控制结构中增加了一个预稳定控制器,提出了改进的内模控制结构,给出了闭环系统内稳定判定定理;更重要的是提出一个综合闭环性能和相角裕度的指标函数,将该指标函数最大化,可获得在不同归一化时滞情况下的优化预稳定控制器整定参数,并拟合出公式．最后,与国际上最新发表的控制方法进行了对比,显示了该方法的优越性．     

Analysis of the identification of closed-loop systems using least-squares methods

This paper presents theory and results concerning the analysis of the identification of closed-loop systems using least-squares methods. The least-squares technique is applied in its normal form and in a modified version developed to cope with the bias problem. The analysis has been established following a mathematical investigation of the problem, and by simulation of different identification experiments applied to different structures of closed-loop systems.

The results derived from this analysis show the conditions under which the identifiability of the open-loop process can be ensured, considering different situations such as whether or not there is noise present at the system output and whether or not external signals are used to perform the identification experiments.

Practical experiments of closed-loop identification on a micromachine system in use in the Department of Electrical Engineering of the University of Manchester are also described. Results for different experimental conditions are presented through graphs showing both the plant and the identified model outputs for the same sequence of sampled input signals.     

Identification of closed-loop linear systems via cyclic spectralanalysis given noisy input-output time-domain data

The problem of closed-loop system identification given noisy time-domain input-output measurements is considered. It is assumed that the various disturbances affecting the system are zero-mean stationary whereas the closed-loop system operates under an external cyclostationary input which is not measured. Noisy measurements of the (direct) input and output of the plant are assumed to be available. The closed-loop system must be stable, but it is allowed to be unstable in open loop. No knowledge about the linear-feedback mechanism is assumed. Two identification algorithms are investigated using cyclic spectral analysis of noisy input-output data. For both approaches, the open-loop transfer function is first estimated using the cyclic spectrum and cyclic cross-spectrum of the input-output data. These transfer function estimates are then used as “data” for the proposed algorithms. Both classes of parameter estimators are shown to be weakly consistent in any stationary noise (both at input as well as output). Asymptotic performance analysis of the proposed parameter estimators is also provided. Computer simulation examples are presented in support of the proposed approaches     

Comparison of the closed-loop identification methods in terms of the bias distribution

Several schemes for plant model identification in closed-loop operation including classical direct method, two-step identification and closed-loop output error algorithms are considered. These methods are analyzed and compared in terms of the bias distribution of the estimates for the case that the noise model is estimated as well as the case that a fixed model of noise is considered (output error structure). The problems concerning the filtered direct method which is often used in the iterative identification and control scheme are mentioned. It is shown that these problems may be solved by the closed-loop output error identification method.