Variable Gain Output Feedback Control of A Networked Temperature Control System Based on Online Delay Estimation

In this paper, a gradient descent method based delay estimator is proposed for use with a variable gain control strategy for networked control systems. The delay estimator is developed in such a way that its boundedness is ensured. The performance of the estimator with variable gain controller is evaluated on a temperature control plant with network in the feedback loop.     

Observer-based H-infinity output feedback control with feedback gain and observer gain variations for Delta operator system

Considering that the controller feedback gain and the observer gain are of additive norm-bounded variations, a design method of observer-based H-infinity output feedback controller for uncertain Delta operator systems is proposed in this paper. A sufficient condition of such controllers is presented in linear matrix inequality （LMI） forms. A numerical example is then given to illustrate the effectiveness of this method, that is, the obtained controller guarantees the closed-loop system asymptotically stable and the expected H-infinity performance even if the controller feedback gain and the observer gain are varied.     

基于回路成形的鲁棒增益调度控制器设计

针对目前基于线性变参数系统的增益调度控制设计中存在的控制结构复杂性问题，提出一种基于回路成形的简单且易实现的增益调度控制结构.在此基础上，提出一个鲁棒增益调度控制设计方法.设计过程首先采用补偿器函数使得被控对象奇异值具有期望的形状，以保证被控对象的性能要求，然后利用小增益定理设计一个鲁棒控制器，得到具有良好性能的、结构简单的鲁棒增益调度控制器.最后针对一个化工过程，说明此方法的有效性.     

Gain scheduling control of nonlinear systems based on approximate input-output linearization

The gain scheduling control mostly has been developed based on Jacobian linearization around the operating points related with scheduling variables. In this paper, We introduce a gain scheduling control method based on approximate input-output linearization. First, the nonlinear system is approximately input-output linearized via a diffeomorphism. Then, a gain scheduling controller with derivative information is developed. The proposed controller consists of two parts. The outer loop controller is like a feedback linearizing controller and the internal controller is a gain scheduling controller. It is shown that the overall resulting controller has a simple structure and at the same time achieves better tracking performance over the existing Jacobian-based gain scheduling controller.     

New recursive-least-squares algorithms for nonlinear active controlof sound and vibration using neural networks

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.     

Intelligent control of static synchronous series compensator via an adaptive self-tuning PID controller for suppression of torsional oscillations

In this paper, an intelligent controller is proposed to control a static synchronous series compensator (SSSC) in order to mitigate subsynchronous resonance (SSR) oscillations in a power system. This intelligent controller is an adaptive self-tuning PID controller. To train the PID controller, the gradient descent method is employed where the learning rate is adapted in every iteration in order to accelerate the speed of convergence. This control scheme also requires a wavelet neural network (WNN) to identify the controlled system dynamic. To update the parameters of WNN, the gradient descent (GD) along with the adaptive learning rates derived by the Lyapunov method is used. The computer simulations are used to show the ability of the proposed controller. In addition, the performance of the proposed controller is compared with another self-tuning PID controller. The results demonstrate that the proposed controller has a successful performance in minimizing the SSR.     

Performance improvement of robust controllers for polynomially uncertain systems

This paper is concerned with the high-performance robust control of discrete-time linear time-invariant (LTI) systems with semi-algebraic uncertainty regions. It is assumed that a robustly stabilizing static controller is given whose gain depends polynomially on the uncertain variables. The problem of tuning this parameter-dependent gain with respect to a prescribed quadratic cost function is formulated as a sum-of-squares (SOS) optimization. This method leads to a near-optimal controller whose performance is better than that of the initial controller. It is shown that the results derived in the present work encompass the ones obtained in a recent paper. The efficacy of the results is elucidated by an example.     

New robust stability criterion and robust controller synthesis

In this paper, a new robust stability criterion for linear systems is proposed by combining the passivity and small gain theorems in different frequency bands. A controller synthesis method based on the new criterion is also developed. The controller can achieve both good performance and robustness in the same frequency band, if the uncertainty in that frequency band is passive or near passive. For processes with near passive lumped uncertainties with large gain in the frequency region in which good performance is required, the proposed controller can have better performance than that of H_∞ control for the same robustness specification. © 1998 John Wiley & Sons, Ltd.     

基于幅值裕度和相位裕度的PID参数最优整定方法

给出一种基于幅值裕度和相位裕度的PID参数最优整定方法.首先,基于改进的D–分割法确定满足幅值裕度和相位裕度要求的控制参数稳定域,然后根据最大灵敏度函数、超调和调节时间定义控制器设计的目标函数,在所得到的控制参数稳定域中计算出一组最优的控制参数值.仿真结果表明,该整定方法能够保证闭环系统具有强鲁棒性、良好的跟踪性能和抗干扰性能.它不仅适用于稳定时滞对象,而且还适用不稳定时滞对象.     

基于观测器的具有反馈增益变化的广义系统H∞控制

介绍了一类广义系统H∞控制器的设计过程.通过设计基于观测器的具有反馈增益变 化的广义控制器,借助于带有广义约束的广义代数Riccati不等式(GARI),给出闭环广义系统 容许且传递函数的H∞范数有界的充要条件.通过解带有广义约束的GARI得到该控制器的设 计方法,并且控制器的参数矩阵只需使观测器容许.     

Performance improvement of the PD-based bilateral teleoperators with time delay by introducing relative D-control

In a force-reflecting bilateral teleoperator with a time delay, teleoperator stability is a serious problem. We have studied a bilateral teleoperator system with a time delay. We obtained stable conditions using proportional derivative-based (PD-based) control law. In this paper, PD-based control law is further studied. First, we study a PD control law with relative damping gain and its stabilizing effect that previously has not been studied quantitatively. A stable condition is derived with this PD-based controller with relative damping gain. Next, teleoperator performance by the PD control law with relative damping is evaluated and compared to PD control laws with only grounded damping using transparency analysis with a hybrid matrix. We showed that, the performance of the PD-based controller can be improved by introducing relative damping gain into the controller. As a controller design example, numerical simulations and 1-DOF experiments were conducted. Finally, peg-in-hole experiments and performance evaluations in realistic multi-DOF environments were conducted to demonstrate performance improvements by introducing the relative damping. A controller design that guarantees both stability and performance was achieved by iterating stable gain setting and performance evaluation.     

Optimal-tuning PID controller design in the frequency domain with application to a rotary hydraulic system

In this paper a new PID controller design scheme that uses optimisation in the frequency domain is proposed for industrial process control. An optimal-tuning PID controller is designed to satisfy a set of frequency-domain performance requirements: gain margin, phase margin, crossover frequency and steady-state error. Using an estimated process frequency response, the method can provide optimal PID parameters even in cases where the process dynamics are time variant. This scheme is demonstrated through its application to a rotary hydraulic system and its performance is compared with six alternative PID tuning rules.     

Chaos synchronization of nonlinear gyros using self-learning PID control approach

Since chaotic systems are important nonlinear deterministic systems that display complex, noisy-like and unpredictable behavior, synchronizing chaotic systems has become an important issue in the engineering community. Due to the proportional-integral-derivative (PID) controller has a simple architecture and easily designed, it was widely used in the industrial applications. However, the traditional PID controller usually needs some manual retuning before being used to practically application. To tackle this problem, this paper proposes a self-learning PID control (SLPIDC) system which is composed of a PID controller and a fuzzy compensator. The PID controller which is used to online approximate an ideal controller is the main controller. The controller gain factors of the PID controller can automatically tune based on the gradient descent method. The fuzzy compensator is designed to dispel the approximation error between the ideal controller and PID controller upon the system stability in the Lyapunov sense. From the simulation results, it is verified that the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized by the proposed SLPIDC scheme without the chattering phenomena in the control effort after the controller parameters learning.     

基于频域近似的线性系统自抗扰参数整定

采用带宽法进行线性自抗扰控制器 (Linear active disturbance rejection control, LADRC)参数整定是目前被普遍接受的调参方法,便于工程人员理解,但由于控制器阶数和相对增益的选择问题限制了其推广。现有的很多基于模型的控制算法都有相对成熟且便于理解的整定方法,同时可以获得满意的控制性能,因此,本文提出基于频域近似的LADRC参数整定方法。该方法通过基于模型的（本文以广义自抗扰控制为例）控制算法求得反馈控制器,然后通过在一定频域内将二阶LADRC与其近似,通过求解非线性方程组的解来得到相应的LADRC参数整定：b0、ωc和ωo。实验仿真表明,通过该方法整定的控制器既保持了LADRC的特性同时继承了反馈控制器的部分优良特性,其结构简单,便于工程实现,为工程人员提供了一种新的参数整定思路。     

Robust mixed H 2 /H ∞ control of time-varying delay systems

This paper describes the mixed H 2 /H X controller design method of linear systems with time-varying delays in both state and control input. More specifically, the proposed mixed H 2 /H X controller minimizes the H 2 performance measure when satisfying a prescribed H X norm bound on the closed loop system. The sufficient conditions for the existence of controller, the mixed H 2 /H X controller design method and the upper bound of performance measure are presented using the linear matrix inequality (LMI) technique. Also, all solutions including controller gain and the upper bound of performance measure are obtained simultaneously. Furthermore, the proposed controller design method can be easily extended into the problem of robust mixed H 2 /H X controller design method for parameter uncertain systems with time-varying delays in both state and control input.     

不确定时滞系统非脆弱鲁棒H∞控制研究

针对不确定时滞系统,应用鲁棒稳定与鲁棒性能准则约束条件,设计鲁棒性较强的非脆弱鲁棒控制器,使得当控制器本身在一定范围内变化时,仍能保证状态反馈闭环系统的稳定性和鲁棒性能指标,进而有效抑制扰动输入信号以及控制器参数变化对系统性能的影响.该控制器的设计过程充分考虑时滞的 影响,进而克服已有时滞无关型结论的保守性.最后...     

Transient performance and robustness of direct adaptive control

It is shown that a discrete adaptive controller with a fixed gain gradient estimator can be applied to linear systems that are undermodeled provided that the mismatch is small and the estimated parameters are projected into a compact convex set which contains stabilizing control parameters and excludes the possibility of dividing with small numbers. The latter implies that the sign and a lower bound for the high-frequency gain of the modeled part of the system are known. The performance of the adaptive system is related to the size of the external perturbations, and the ideal result as these tend to zero is obtained. The main conclusion is that while convergence, stability, and robustness may be achieved, the transient performance may not be acceptable and the gradient estimator should probably not be used unless modifications are added. Design guidelines are established. The results extend readily to indirect adaptive laws like pole assignment, linear quadratic optimal, and predictive controllers     

智能微电网分布式云储能系统安全稳定控制

针对目前智能微电网分布式云储能系统运行架设成本较高且难寻行之有效整体控制规律的问题,引入一种基于观测器的 控制器设计方法,用以处理数学模型体现为具有范数有界时变参数不确定性的一类分段式储能系统。通过采用广义分段仿射Lyapunov函数、投影定理以及几个基本引理,提出了对于由所设计控制器构成的闭环系统基于观测器且满足鲁棒 性能指标的反馈控制器设计方法。通过求解一组包含参变量的LMIs,可以得到保证广义分段仿射系统具有 性能的反馈控制器增益和观测器增益,数值仿真得到干扰抑制度 =6.5896,通过将云储能供电系统与传统电力系统进行比较,在证明所提设计方法有效性的同时也验证了该方法的卓越性。     

An experimental study on the optimization of controller gains for an electro-hydraulic servo system using evolution strategies

This paper deals with an experimental optimization problem of the controller gains for an electro-hydraulic position control system through evolution strategies (ESs)-based method. The optimal controller gains for the control system are obtained by maximizing fitness function designed specially to evaluate the system performance. In this paper, for an electro-hydraulic position control system which would represent a hydraulic mill stand for the roll-gap control in plate hot-rollings, the time delay controller (TDC) is designed, and three control parameters of this controller are directly optimized through a series of experiments using this method. It is shown that the near-optimal value of the controller gains is obtained in about 5th generation, which corresponds to approximately 150 experiments. The optimal controller gains are experimentally confirmed by inspecting the fitness function topologies that represent system performance in the gain spaces. It is found that there are some local optimums on a fitness function topology so that the optimization of the three control parameters of a TDC by manual tuning could be a task of great difficulty. The optimized results via the ES coincide with the maximum peak point in topologies. It is also shown that the proposed method is an efficient scheme giving economy of time and labor in optimizing the controller gains of fluid power systems experimentally.     

Robust reliability method for non-fragile guaranteed cost control of parametric uncertain systems

The problem of non-fragile guaranteed cost control of uncertain systems is studied from a new point of view of reliability against uncertainties. An efficient robust reliability method for the analysis and design of non-fragile guaranteed cost controller of parametric uncertain systems is presented systematically. By the method, a robust reliability measure of an uncertain control system satisfying required robust performance can be obtained, and the robustness bounds of uncertain parameters such that the control cost of a system is guaranteed can be provided. The optimal non-fragile guaranteed cost controller obtained in the paper may possess optimal guaranteed cost performance satisfying the precondition that the system is robustly reliable with respect to uncertainties occurring in both the controlled plant and controller gain. The presented formulations are in the framework of linear matrix inequality and thus can be carried out conveniently. The presented method provides an essential basis for the tradeoff between reliability and control cost in controller design of uncertain systems. Two numerical examples are provided to demonstrate the efficiency and feasibility of the presented method. It is shown that the coordination and simultaneous realization of the system performance, control cost, and robust reliability in control design of uncertain systems are significant.