Stability of self‐tuning control based on Lyapunov function

The overall stability of a self‐tuning controller for discrete‐time systems is proved by using the Lyapunov function in this paper, for minimum and a class of non‐minimum phase systems. The self‐tuning controller utilizes a recursive estimate algorithm for the controller parameters based on the generalized minimum variance criterion. Previously, the stability had been proved in the case of minimum phase systems. A new type of self‐tuning controller for the discrete‐time system with delay in control input is also studied which is named the generalized minimum variance criterion‐β equivalent control, and its stability is proved. The simulation is done to evaluate the performance of the proposed self‐tuning controller. Copyright © 2008 John Wiley & Sons, Ltd.     

Minimum variance in fast,slow and dual‐rate control loops

In certain industrial applications, the control updating rate is faster than the output sampling rate by a certain factor, which leads to dual‐rate (DR) control problems. Generally speaking, a DR controller performs better than a slow single rate (SSR) controller but worse than a fast single rate (FSR) controller in the sense of minimum variance control. This conjecture is theoretically justified in this paper for a continuous linear time‐invariant (LTI) single‐input single‐output (SISO) system. The optimal FSR, DR and SSR controllers are designed under the same performance criterion: variance of the fast sampled output. The discretization of continuous stochastic disturbance models is investigated preserving certain basic statistical properties. A linear matrix inequality (LMI) approach is developed to calculate the optimal controllers for DR and SSR loops. The theoretical results are illustrated by two simulation examples. Copyright © 2005 John Wiley & Sons, Ltd.     

Recursive Gauss–Seidel algorithm for direct self‐tuning control

A recursive algorithm based on the use of Gauss–Seidel iterations is introduced to adjust the parameters of a self‐tuning controller for minimum phase and a class of nonminimum phase discrete‐time systems. The proposed algorithm is called the Recursive Gauss–Seidel (RGS) algorithm and is used to update the controller parameters directly. The use of the RGS algorithm with a generalized minimum variance control law is also given for nonminimum phase systems, and a forgetting factor is used to track the time‐varying parameters. Furthermore, the overall stability of the closed‐loop system is proven by using the Lyapunov stability theory. Using computer simulations, the performance of the RGS algorithm is examined and compared with the widely used recursive least squares algorithm.Copyright © 2011 John Wiley & Sons, Ltd.     

火电厂过热汽温控制系统性能评价

以火电厂典型过热汽温拉制系统为研究对象,推导了串级控制系统最小方差性能评价指标的计算方法,利用MATLAB平台搭建仿真模型,理论推导反馈不变项得到控制系统的最小方差;通过模型输出计算等价单回路PID控制器的最小方差和时间序列分析最小方差,结果表明等价单回路PID控制器的最小方差能够实现最小方差性能评价,并利用某电厂实际...     

Direct design from input/output data of a fault‐tolerant control system based on GIMC structure

This paper deals with a method for the design of a fault‐tolerant control system based on the Generalized Internal Model Control (GIMC) structure, consisting of a standard outer loop feedback controller and an extra inner loop controller. The distinguishing feature of the GIMC structure is that controller design for performance and robustness may be performed separately. The outer loop controller is designed for nominal performance using some controller synthesis to meet the (nominal) control specification, while the inner loop controller is designed to make a trade‐off between robustness and performance. This feature is suitable for fault‐tolerant control. The outer loop controller is designed for the fault‐free case, and the inner loop controller for the fault‐time case. In the conventional methods, the inner loop controller is designed to maximize the robust stability margin without fault information. Therefore, the performance in the fault‐time case tends to become conservative. In this paper, the inner loop controller is directly designed from experimental data collected from the faulty system. Since the collected data contains information on the fault, conservativeness in the conventional methods is decreased. The inner loop controller is designed by Virtual Reference Feedback Timing (VRFT). VRFT is a method of direct design from input‐output data without identifying any models. Since the complexity of the controller can be specified by the designer, no complexity reduction is necessarily required, which is advantageous in implementation. The effectiveness of the proposed design method is confirmed by an experiment. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(4): 53–62, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20929     

Adaptive PI secondary control for smart autonomous microgrid systems

In this paper, the authors present a neural‐network‐based distributed secondary control to regulate the output voltage and frequency of a smart autonomous microgrid system. Generally, the secondary controller is implemented in a centralized manner using a fixed‐gain proportional‐plus‐integral controller which may perform well under certain operating conditions only. Also the failure of centralized controller implies no secondary control action for the entire system. The control technique proposed in this paper is a distributed one and makes use of neural network (NN) concept to improve the performance of system. A well‐trained NN supplies the controller with suitable gains according to each operating point. Before training the NN, evolutionary optimization technique, differential evolution, is employed to obtain the optimal gains of controller at each operating load condition which forms the training set for NN. Simulation results show that the proposed controller damps the oscillations caused by load changes, restores the output voltage and frequency of the system to their nominal values, and maintains proper load sharing property of the baseline controller. The performance of the controller is also compared with fixed‐gain controller. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust observer‐based control design for uncertain singular systems with time‐delay

This paper is concerned with the stability analysis and robust dynamic output feedback controller synthesis for uncertain continuous singular systems with time‐delay. First, on the basis of the Lyapunov functional method and by resorting to the delay‐partition technique, improved delay‐dependent sufficient conditions are presented to ensure the nominal unforced system to be admissible (i.e., to be regular, impulse‐free, and stable). Second, with the help of the obtained admissibility criterion, an observer‐based controller is designed by solving a set of LMIs. Finally, the validity and applicability of the proposed approach is shown by examples. Copyright © 2013 John Wiley & Sons, Ltd.     

A semi‐adaptive control approach to closed‐loop medication infusion

This paper presents a semi‐adaptive control approach to closed‐loop medication infusion problems. The rationale underlying this approach is to design a controller that can adapt model parameters with a large impact on the model's fidelity while fixing the remaining parameters at nominal values. In this paper, a control‐oriented model for this purpose is derived via system identification and sensitivity analysis of a low‐order model capturing the direct dose‐response relationship Using the model thus derived, a model‐reference adaptive controller and a composite adaptive controller are designed and compared with each other. In‐silico simulation results using remifentanil's effect on respiratory rate as an example indicate that both controllers can regulate the output at commanded set points. Copyright © 2016 John Wiley & Sons, Ltd.     

A study of decoupling with skeleton matrix in two‐degree‐of‐freedom generalized minimum variance control

There are many multi‐input multi‐output (MIMO) systems in chemical plants, and they have multiple time delays of different length in each input and output pair. This paper explains a two‐degree‐of‐freedom (2DOF) control system based on generalized minimum variance control (GMVC) for MIMO systems. It can improve the tracking performance with respect to the reference signals and the response properties for the disturbance. The states between the sampling period can be expressed by using the modified z transform to take account of multiple time delays. Additionally, a tracking controller is designed to decouple the plant. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(1): 28–36, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21046     

Maximum power tracking control for a wind energy conversion system based on a quasi‐ARX neural network model

By itself, a wind turbine is already a fairly complex system with highly nonlinear dynamics. Changes in wind speed can affect the dynamic parameters of wind turbines, thus rendering the parameters uncertain. However, we can identify the dynamics of the wind energy conversion system (WECS) online by a quasi‐ARX neural network (QARXNN) model. A QARXNN presents a problem in searching for the coefficients of the regression vector (input vector). A multilayer perceptron neural network (MLPNN) is an embedded system that provides the unknown parameters used to parameterize the input vector. Fascinatingly, the coefficients of the input vector from prediction model can be set as controller parameters directly. The stability of the closed‐loop controller is guaranteed by the switching of the linear and nonlinear parts of the parameters. The dynamic of WECS is derived with given parameters, and then a wind speed signal created by a random model is fed to the system causing uncertainty parameters and reducing the power that can be absorbed from wind. By using a minimum variance controller, the maximum power is tracked from WECS. From the simulation results, it is observed that the proposed controller is effective in tracking the maximum power of WECS. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A weighted adaptive one-step-ahead minimum variance controller based on the ELS algorithm

This paper deals with the design of a weighted adaptive one-step-ahead minimum variance controller based on the extended least squares (ELS) algorithm for a discrete time stochastic system. The stability of the closed-loop system and the convergence rates of the general adaptive tracking and estimation errors are respectively established under strictly positive real and minimum phase conditions. The best possible convergence rate of the average error between the predicted and desired outputs is obtained given some identifying condition and the above-stated conditions. No modification of the adaptive controller is made. © 1997 by John Wiley & Sons, Ltd.     

Design of an Implicit GMV‐PID Controller Using Closed Loop Data

In industrial processes, PID control has been applied in many real systems. The control performance strongly depends on the PID parameters. Although some schemes for tuning PID parameters have been proposed, these schemes need system parameters which are estimated by system identification in order to calculate the PID parameters. On the other hand, model‐free controller design schemes represented by virtual reference feedback tuning (VRFT) or FRIT have received much attention in the last few years. These methods can calculate control parameters using closed loop data and are expected to reduce computational costs. In this paper, a type of implicit PID controller using closed loop data is proposed. In the proposed method, the PID parameters are calculated on the basis of the implicit generalized minimum variance control. The control performance can be suitably adjusted by means of only a user‐specified parameter. The effectiveness of the proposed method is numerically and experimentally evaluated.     

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

In this paper, we present a control design framework wherein an adaptive‐based corrective signal is augmented to the output of the nominal controller in order to suppress or counteract the effect of malicious actuator attacks. Due to the unavailability of full‐state measurements, a nonminimal controllable realization of the nominal closed‐loop system is used to design the corrective signal predicated on partial state information. Two illustrative numerical examples are given to demonstrate the efficacy of the proposed adaptive control architecture.     

A design method of a generalized predictive control system based on parametrization of two‐degree‐of‐freedom integral controllers

A new design method for a generalized predictive control (GPC) system based on parametrization of two‐degree‐of‐freedom integral controllers has been proposed. The objective is to guarantee stability of the control system without depending on the design parameters and to achieve low sensitivity against the plant perturbation and the disturbance. The design procedure consists of two steps. First, we design a basic integral controller for a nominal plant using the linear quadratic Gaussian (LQG) method and parametrize a class of two‐degree‐of‐freedom stabilizing controllers. Next, we tune the feedforward controller to incorporate the GPC method into our control structure. A numerical example is presented to show the effectiveness of the proposed method by comparing it with the conventional GPC method. © 1999 Scripta Technica, Electr Eng Jpn, 129(2): 62–70, 1999     

Design and implementation of a digitally controlled single‐inductor dual‐output (SIDO) buck converter

This paper describes design and implementation of a digitally controlled single‐inductor dual‐output (SIDO) buck converter operating in discontinuous conduction mode. This converter adopts time‐multiplexing control in providing two independent output voltages using only an inductor. The design issues of the digital controller are discussed, including static and dynamic characteristics. Implementation of the controller, a modified hybrid digital pulse width modulator and a single look‐up table are developed. The digital controller was implemented on a field‐programmable gate array‐based control board. Experimental results demonstrating system validity are presented for a SIDO buck converter with nominal 3.6 V input voltage, and the outputs are regulated at 1.8 and 2.2 V. Copyright © 2012 John Wiley & Sons, Ltd.     

Design of a near‐optimal adaptive filter in digital signal processor for active noise control

Adaptive filter has been applied in adaptive feedback and feedforward control systems, where the filter dimension is often determined by trial‐and‐error. The controller design based on a near‐optimal adaptive filter in digital signal processor (DSP) is developed in this paper for real‐time applications. The design integrates the adaptive filter and the experimental design such that their advantages in stability and robustness can be combined. The near‐optimal set of controller parameters, including the sampling rate, the dimension of system identification model, the dimension (order) of adaptive controller in the form of an FIR filter, and the convergence rate of adaptation is shown to achieve the best possible system performance. In addition, the sensitivity of each design parameter can be determined by analysis of means and analysis of variance. Effectiveness of the adaptive controller on a DSP is validated by an active noise control experiment. Copyright © 2007 John Wiley & Sons, Ltd.     

Intelligent control using multiple models and neural networks

Most adaptive control algorithms for nonlinear discrete time systems become invalid when the controlled systems have non‐minimum phase properties and large uncertainties. In this paper, an intelligent control method using multiple models and neural networks (NN) is developed to deal with those problems. The proposed control method includes a set of fixed controllers, a re‐initialized neural network (NN) adaptive controller and a free‐running NN adaptive controller. The bounded‐input‐bounded‐output (BIBO) stability and performance convergence of the system are guaranteed by the free‐running adaptive controller, while the multiple fixed controllers and the re‐initialized adaptive controller are used to improve the transient response. Simulation results are presented to demonstrate the effectiveness of the proposed method. Copyright © 2007 John Wiley & Sons, Ltd.     

极点配置广义最小方差控制器

本文对多变量系统给出了一种具有极点配置的广义最小方差控制器。它能够消除稳态偏差且有扰可测干扰能力，可在线亦可离线配置闭环极点，可用于非最小相位系统的控制。     

H‐infinity controller for frequency and voltage regulation in grid‐connected and islanded microgrid

This paper presents a study on a grid‐connected and islanded multiple distributed generation (DG) system for frequency and voltage regulation. The multiple DG system includes solar cells, wind turbine, fuel cell, and battery storage. The H‐infinity controller is used whose weighting parameters are optimized to minimize voltage and frequency deviation. The performance of the system is analyzed under different conditions for both grid‐connected and islanded modes of operation. In case of the load variations, the inner voltage and current loop react based on the H‐ infinity control strategies. The outer power loop uses the droop characteristic controller. The design is simulated using MATLAB/SIMULINK. The simulation results show that the multiple DG system can supply high‐quality power both in grid‐connected and islanded modes. Also, we show that the proposed control methodology will make the system to transit smoothly between the islanded mode and the grid‐connected mode. The results indicate that the frequency and voltage deviations meet the nominal values as per IEEE standard. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A design of multivariable,self‐tuning PID controllers with an internal model structure

Self‐tuning control schemes (STC) are useful for systems with unknown or slowly time‐varying parameters. Some single‐input/single‐output PID control schemes based on STCs have been proposed for such systems. However, there are a lot of multivariable systems in real process industries. And these systems often have relatively large time delays. In this paper, a design scheme of self‐tuning PID control system is proposed for multivariable systems with unknown parameters and time delays. The controlled object is equipped with an internal model in order to compensate the time delay and also unstable zeros. Subsequently, a multivariable PID controller is designed for the augmented or compensated system. The PID parameters are calculated recursively based on the relationship between the minimum variance control law and the PID control law. A simulation example is presented to demonstrate the effectiveness of the proposed scheme. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 146(4): 58–64, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10241