Virtual reference feedback tuning: a direct method for the design of feedback controllers

This paper considers the problem of designing a controller for an unknown plant based on input/output measurements. The new design method we propose is direct (no model identification of the plant is needed) and can be applied using a single set of data generated by the plant, with no need for specific experiments nor iterations. It is shown that the method searches for the global optimum of the design criterion and that, in the case of restricted complexity controller design, the achieved controller is a good approximation of the restricted complexity global optimal controller. A simulation example shows the effectiveness of the method.     

一种基于DMC的新型预测PID控制器及其整定

本文提出一种基于动态矩阵控制(DMC)算法预测特性的新型PID控制方法.在考虑将来的输出期望偏差罚函数最小的前提下,由DMC计算出控制变量的值.继而构造基于DMC的预估器用以预测将来时刻的系统输出.根据将来时刻的多步预测偏差,PID控制器产生当前时刻的实际控制增量.文中也给出了基于DMC的预估器及PID控制器的参数整定方法.仿真结果表明,与常规的PID控制和DMC控制相比,所提方法具有良好的控制性能,扰动抑制尤其优良.     

The Mimo Predictive Pid Controller Design

This paper is concerned with the design of Multi‐Inputs and Multi‐Outputs (MIMO) predictive PID controllers, which have similar performance to that obtainable from model‐based predictive controllers. A new PID control structure is defined which incorporates the prediction of future outputs and uses future set point. A method is proposed to calculate the optimal values of the PID gains from generalised predictive control results. A decentralized version of the predictive PID controllers is presented and the stability of the closed loop system is studied. Simulation studies demonstrate the superior performance of the proposed controller compared with a conventional PID controller. The results are also compared with generalised predictive control solutions.     

Extensions to “virtual reference feedback tuning: A direct method for the design of feedback controllers”

The papers [Campi, Lecchini & Savaresi (2002). Automatica, 38(8), 1337-1346; (2003). European Journal of Control, 9(1), 66-76] present a direct controller synthesis procedure that uses identification algorithms applied to filtered input-output plant data. This contribution discusses variations that, in some cases, may alleviate noise-induced correlation (in the open-loop case) and allow the applicability of the approach to unstable plants. Importantly, it also introduces an invalidation test step based on the available data (i.e., prior to experimental controller testing), to check if the flexibility of the controller parameterisation and the approximations involved are suitable for the design objectives or, on the contrary, the resulting closed loop may be unstable.     

Integrating virtual reference feedback tuning into a unified closed-loop identification framework

This paper compares particular instances of control-relevant identification, closed-loop identification, and controller identification (either in an actual loop or in a virtual reference feedback tuning approach, VRFT) problems. Significant similarities appear between them which allow, in particular, alternative formulations of the VRFT methodology in a differentiable setting.     

Robust tuning for machine-directional predictive control of MIMO paper-making processes

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.     

具有比例积分结构的广义预测自校正控制器

本文通过对一般预测控制中目标函数的改进，导出了具有比例积分结构的广义预测自校正控制器，从而极大地改善了控制器性能。仿真结果表明了该算法的有效性，对促进自校正控制器在工业中的应用具有一定意义。     

Fast calculation of stabilizing PID controllers

A fast method for the computation of stabilizing PID controllers is proposed. It is shown, in particular, that for a fixed value of the proportional term (K_p) the resulting stabilizing PID compensators form a finite set of disjoint polyhedral sets in the parameter space. A complete characterization and a practical way of finding such stabilizing regions are given. Moreover, the bounds on stabilizing K_p parameters are derived. The method, therefore, has several advantages over recent results, and is very promising for real time and/or robust control applications.     

A receding horizon control approach to sampled-data implementation of continuous-time controllers

We propose a novel way for sampled-data implementation (with the zero order hold assumption) of continuous-time controllers for general nonlinear systems. We assume that a continuous-time controller has been designed so that the continuous-time closed-loop satisfies all performance requirements. Then, we use this control law indirectly to compute numerically a sampled-data controller. Our approach exploits a model predictive control (MPC) strategy that minimizes the mismatch between the solutions of the sampled-data model and the continuous-time closed-loop model. We propose a control law and present conditions under which stability and sub-optimality of the closed loop can be proved. We only consider the case of unconstrained MPC. We show that the recent results in [G. Grimm, M.J. Messina, A.R. Teel, S. Tuna, Model predictive control: for want of a local control Lyapunov function, all is not lost, IEEE Trans. Automat. Control 2004, to appear] can be directly used for analysis of stability of our closed-loop system.     

PID controller frequency-domain tuning for stable, integrating and unstable processes, including dead-time

In the present paper a new tuning procedure is proposed for the ideal PID controller in series with the first-order noise filter. It is based on the recently proposed extension of the Ziegler-Nichols frequency-domain dynamics characterization of a process G_p(s). Measured process characteristics are the ultimate frequency and ultimate gain, the angle of the tangent to the Nyquist curve of the process at the ultimate frequency, and G_p(0). For a large class of processes the same tuning formulae can be effectively applied to obtain closed-loop responses with predictable properties. Load disturbance step responses without the undershoot and reference step responses with negligible overshoot are obtained by analyzing a test batch consisting of stable, integrating and unstable processes, including dead-time and oscillatory dynamics. The proposed tuning makes possible to specify the desired sensitivity to the high frequency measurement noise and the desired maximum sensitivity. Comparison with the optimal ideal PID controller in series with the first-order noise filter is presented and discussed. The extension of the proposed method to the PI controller tuning is direct. Comparison with the optimal PI controller is presented and discussed.     

双电机同步控制系统的设计与仿真

针对双电机同步控制问题,首先建立双电机同步控制系统的数学模型,在分析同步控制的各种控制方式和控制算法优缺点的基础上,提出了在偏差耦合控制方式下采用模糊PID控制算法对偏差进行调节的双电机同步控制方案,并与采用常规PID算法的进行了比较。仿真结果和实验表明,采用模糊PID控制算法的偏差耦合系统优于采用常规PID的系统。     

Performance assessment using a model predictive control benchmark

Model predictive control (MPC) technology has been widely implemented throughout the petroleum, chemical, metallurgical and pulp and paper industries over the past three decades. The focus of this paper is the assessment of single-input, single-output MPC schemes against a new performance standard. The proposed MPC benchmark is shown to be useful both as a model diagnostic and as a tuning guide during commissioning. A formal assessment procedure is presented which emphasizes the use of routine operating data plus knowledge of the deadtime to determine when it becomes worthwhile to invest in re-identification of the plant dynamics and re-installation of the MPC application.     

基于CMAC的PID控制在换热器中的应用设计及仿真

本文介绍了小脑模型神经网络CMAC的原理及基于CMAC与PID的并行控制设计，以及该设计在换热器控制中的应用，并对该设计在MATLAB下进行了仿真．得到了较好的控制效果。     

Neural networks in virtual reference tuning

This paper discusses the application of the virtual reference tuning (VRT) techniques to tune neural controllers from batch input-output data, by particularising nonlinear VRT and suitably computing gradients backpropagating in time. The flexibility of gradient computation with neural networks also allows alternative block diagrams with extra inputs to be considered. The neural approach to VRT in a closed-loop setup is compared to the linear VRFT one in a simulated crane example.