Generalized pole-placement self-tuning controller Part 1, Basic algorithm

A new type of self-tuning pole-placement controller is proposed based on multi-step cost function minimization and using single-input single-output models of the controlled autoregressive moving average form. The generalized pole-placement (GPP) algorithm has advantages over standard pole-placement self-tuners in having a set of tuning knobs for improving transient response and overall control performance. The GPP is particularly suitable for programmed control in which future set-point values are known.     

广义自校正控制器及其在飞行高度控制中的应用

本文将广义最小方差控制与极点配置控制结合起来提出了具有加权项在线选择的广义自校正控制器.该控制器采用最小二乘辨识算法来辨识控制器参数,采用显式方式来实现.本控制器可以保证自适应控制系统的整体稳定性.本文还进行了广义自校正控制器应用于飞行高度控制中的仿真研究.研究结果表明,采用本控制器完全可以适应当飞行条件变化时被控对象参数的变化,从而获得令人满意的控制效果.     

Nonlinear model-state feedback control for nonminimum-phase processes

A general nonlinear controller design methodology for continuous-time nonminimum-phase systems is presented, which utilizes synthetic outputs that are statically equivalent to the original process outputs and make the system minimum-phase. A systematic procedure is proposed for the construction of statically equivalent outputs with prescribed transmission zeros. The calculated outputs are used to construct a model-state feedback controller. The proposed method is applied to a nonminimum-phase chemical reactor control problem where a series/parallel reaction is taking place.     

Generalized predictive control—Part I. The basic algorithm

Current self-tuning algorithms lack robustness to prior choices of either dead-time or model order. A novel method—generalized predictive control or GPC—is developed which is shown by simulation studies to be superior to accepted techniques such as generalized minimum-variance and pole-placement. This receding-horizon method depends on predicting the plant's output over several steps based on assumptions about future control actions. One assumption—that there is a “control horizon” beyond which all control increments become zero—is shown to be beneficial both in terms of robustness and for providing simplified calculations. Choosing particular values of the output and control horizons produces as subsets of the method various useful algorithms such as GMV, EPSAC, Peterka's predictive controller (1984, Automatica, 20, 39–50) and Ydstie's extended-horizon design (1984, IFAC 9th World Congress, Budapest, Hungary). Hence GPC can be used either to control a “simple” plant (e.g. open-loop stable) with little prior knowledge or a more complex plant such as nonminimum-phase, open-loop unstable and having variable dead-time. In particular GPC seems to be unaffected (unlike pole-placement strategies) if the plant model is overparameterized. Furthermore, as offsets are eliminated by the consequence of assuming a CARIMA plant model, GPC is a contender for general self-tuning applications. This is verified by a comparative simulation study.     

Persistency of excitation for continuous-time systems — Time-domain approach

This paper presents the time-domain approach to the analysis of the convergence of continuous-time adaptive control and estimation algorithms. The time-domain definition of persistently exciting signals is introduced and the convergence of estimation algorithms is established in the cases of open-loop and closed-loop systems. An application of the persistency of excitation theory to the design of a globally stable adaptive pole-placement controller is given.     

多输入预报自校正前馈控制器及其在高频焊管焊接过程控制中的应用

本文针对高频焊管焊接过程的控制,提出了一种适用于具有多种扰动对象的多输入预报自校正前馈控制器,其特点是综合了广义最小方差控制的最优性、极点配置控制的鲁棒性和多输入前馈控制的抗扰性等优点。该控制器采用间接算法实现,在线选择二次型性能指标中加权项。它不仅可以消除可测干扰的影响,消除稳态跟踪误差,而且即使用于非最小相位系统也具有全局收敛特性。理论分析和仿真实验表明,提出的控制器具有良好的控制性能,可以适应焊接过程环境的变化,从而获得满意的控温效果。     

一种新的预测自校正控制器

本文通过在指标函数中引入加权多项式，为由脉冲响应模型描述的系统提出一种基于多步预测的极点配置自校正控制器，这种控制器能确保控制系统的稳定性，并能消除控制系统的稳态误差，算法的计算也比其它的预测控制算法如ＭＡＣ，ＧＰＣ等小。     

新型多变量广义预测自校正控制器

本文对多变量线性系统提出了一种新的广义预测自校正控制器(MGPC).由于本算法是利用辨识结果直接求解控制器,不需要在线求解Diophantine方程,因而大大减少了计算量,并简化了控制系统的设计过程。仿真结果表明:本文提出的算法能适用于具有有色噪声干扰的不稳定和(或)非最小相位多变量随机系统。     

Adaptive control of the filling velocity of thermoplastics injection molding

Injection velocity, a key variable in injection molding, was controlled via an adaptive controller using a self-tuning regulator (STR) scheme. The pole-placement design was employed first, together with the performance enhancement techniques of anti-windup estimation, feed-forward control, and cycle-to-cycle adaptation. The pole-placement design with the enhancement techniques was found experimentally to work very well over different molding conditions. However, this design was also found to be sensitive to the model mismatch. To overcome this problem, a new adaptive controller based on a generalized predictive control (GPC) principle was designed to make the controller more robust. Experiments have shown that the adaptive GPC control of injection velocity has inherently good set-point tracking performance and excellent tolerance to model structure mismatch.     

A self-tuning regulator based on optimal output feedback theory

Self-tuning control of stochastic systems is considered. The underlying control problem is a parametric linear quadratic problem for fixed structure controllers. An explicit self-tuning regulator is described based on optimal output feedback theory. The proposed self-tuner is a generalization of state-space LQG self-tuners to parametric LQ problems. Two interesting application areas of parametric LQ self-tuners are autotuning of parameters of low-order regulators, such as PID-regulators, and adaptive decentralized control.     

隐式多变量广义自校正控制器

本文提出了具有在线选择加权阵的两种多变量自校正控制器.加权阵的在线选择和自校 正控制算法都采用隐式方案来实现.本文还证明了该自校正控制器具有全局收敛性.     

Predictive pole-placement control with linear models

The predictive pole-placement control method introduced in this paper embeds the classical pole-placement state feedback design into a quadratic optimisation-based model-predictive formulation. This provides an alternative to model-predictive controllers which are based on linear-quadratic control. The theoretical properties of the controller in a linear continuous-time setting are presented and a number of illustrative examples are given. These results provide the foundation for novel linear and nonlinear constrained predictive control methods based on continuous-time models.     

Constrained predictive pole-placement control with linear models

Predictive pole-placement (PPP) control is a continuous-time MPC using a particular set of basis functions leading to pole-placement behaviour in the unconstrained case. This paper presents two modified versions of the PPP controller which are each shown to have desirable stability properties when controlling systems with input, output and state constraints.     

Pole assignment self-tuning controller for robotic manipulators

This paper presents an effective adaptive controller for robotic manipulators. A perturbation difference model of the manipulator is established for the first time, based on which a modified pole assignment self-tuning control algorithm is developed. The controller is designed such that the variance of a generalized cost function is minimized and the controller parameters are estimated directly. Closed-loop pole assignment is achieved by adjusting on-line the weighting factors in the cost function. Simulations to a manipulator with three degrees of freedom are given to demonstrate the effectiveness of this self-tuning controller.     

A multivariable self-tuning controller

A multivariable self-tuning controller is derived extending the scalar version of Clarke and Gawthrop (1975). Because the control terms are penalized in the cost function, fluctuations and peaking in control signals are reduced compared with the multivariable minimum variance self-tuning controller (Borisson, 1979). Time-varying reference signals as well as certain nonminimum-phase systems can be handled without difficulty with the proposed controller. Several examples illustrate the power of the derived self-tuning controller.     

广义最小方差自校正重置PID控制器及其在压力系统中的应用研究

针对压力系统的纯延迟、大惯性、非线性、时变等特点,本文将重置控制和以广义最小方差为性能指标的自校正PID控制相结合,提出一种广义最小方差自校正重置PID控制方法。该方法首先根据被控对象的数学模型,以广义最小方差为目标设计广义最小方差控制器,通过选择该控制器的分母多项式,求解Diophantine方程,得到具有PID结构形式的广义最小方差控制器,再在该控制器的积分项中引入重置控制,构成广义最小方差重置PID控制;对于模型未知或参数慢时变的被控对象,通过采用带遗忘因子的递推最小二乘法构建系统的自适应机制,增强控制系统的自适应能力和鲁棒性。最后,将该控制方法应用于压力容器的恒值控制中,获得了比较满意的控制效果。     

具有在线选择加权项的隐式自校正控制器*

本文将自校正控制器和零极点配置策略结合起来提出了具有在线选择加权项的两种自校正控制器。采用隐式方式来实现加权项的选择和自校正控制器。本文还证明了这两种控制器具有整体稳定性和收敛性,并给出了仿真实例。     

Regularized pole-placement adaptive control of a liquid-liquid extraction column

Some critical computations in pole-placement design and in that of many model reference adaptive systems are described. These numerical problems are associated with the resolution of the diophantine equation. They occur when the assumption of no common poles and zeros is violated. Regularization techniques which cope with ill-conditioning are presented. The resulting algorithm combines a standard indirect pole-placement adaptive control algorithm and a dimension-free regularization procedure of the design equations, thus avoiding the pole-zero cancellation problem and yet retaining the other properties of the algorithm. The application of this control scheme in a pulsed liquid-liquid extraction column is described. The control objective is to optimize the column behaviour. Extraction columns are subject to changes in feed compositions, feed flow-rates, physical properties of the solvent (the extractor) and the solute (liquid mixture) and various disturbances. The column exhibits highly non-linear and time-varying dynamics. The conductivity measured at a specific place in the column and the pulse frequency have been selected as control variables. Experimental results demonstrate the usefulness and the robustness of this regularized pole-placement adaptive control algorithm.