RBF-ARX model-based MPC strategies with application to a water tank system

A hybrid pseudo-linear RBF-ARX model that combines Gaussian radial basis function (RBF) networks and linear ARX model structure is utilized for representing the dynamic behavior of a class of smooth nonlinear and non-stationary systems. This model is locally linear at each working point and globally nonlinear within whole working range. Based on the structural characteristics of the RBF-ARX model, three receding horizon predictive control (RBF-ARX-MPC) strategies are designed: (1) the RBF-ARX-MPC algorithm based on single-point linearization (MPC-SPL); (2) the RBF-ARX-MPC algorithm based on multi-point linearization (MPC-MPL); and (3) the RBF-ARX-MPC algorithm based on globally nonlinear optimization (MPC-GNO). In the MPC-SPL, the future multi-step-ahead predictive output of the system is obtained based on the local linearization of the RBF-ARX model at only current working-point, while in the MPC-MPL the future long-term output prediction is obtained according to the future local characteristics from previous online optimization results of the RBF-ARX model based MPC. In the MPC-GNO, the globally nonlinear characteristics of the RBF-ARX model are fully used for online getting control variables of the MPC. Real-time control experiments for the three type MPCs are carried out on a water tank system, which are also compared with a classical PID control and a traditional linear ARX model-based MPC. The results verify that the modeling method and the model-based predictive control strategies are realizable and effective for the nonlinear and unstable system. Moreover, it is also shown that the MPC-GNO can obtain better control performance but need more computation time compared to the other MPCs, which makes it possible to be applied into some slowly varying processes.     

基于遗传算法的预测自整定P I D 控制器

提出一种基于遗传算法的预测自整定ＰＩＤ控制算法。利用预测技术克服时滞,利用遗传算法优化ＰＩＤ控制器参数。对工业过程中典型的大时滞被控过程的仿真表明,这种控制算示鲁棒性强,响应速度快,抗干扰能力强,可构成较实用的工程控制器。     

A DESIGN OF MULTILOOP PID CONTROLLERS WITH A NEURAL‐NET BASED DECOUPLER

In process industries, PID control schemes have been widely used due to their simple structures and easiness of comprehending the physical meanings of control parameters. However, the good control performance cannot be obtained by simply using PID controlschemes, since most processes are considered as nonlinear multivariable systems with mutual interactions. In this paper, a design method of multiloop PID controllers neural‐net based decoupler is proposed for nonlinear multivariable systems with mutual interactions. The proposed method consists of a decoupler given by the sum of a static decoupler and a neural‐net based decoupler, and multi‐loop PID controllers. Finally, the effectiveness of the proposed control scheme is evaluated on the simulation examples.     

电加热炉系统预测函数PID控制算法的研究

由于电加热炉系统具有大时滞、时变性、非线性等特点,提出了一种新型预测函数PID控制算法.该算法将PID控制算法和预测函数控制算法结合起来,通过预测被控对象的未来输出值,得到一个新的优化目标函数,实时优化控制参数,得到控制量的解析解.仿真结果表明,与常规PID控制和预测函数PID串级控制相比,所设计的控制器满足系统对快速性和稳态精度的要求,系统具有较强的抗干扰性和鲁棒性,能够实现对电加热炉系统的有效控制.     

网络控制系统的自整定PID 控制器设计

结合广义预测控制（GPC）方法和PID反馈结构,设计了一种具有预测功能的PID控制器,PID参数根据未来时刻的预计输出误差进行整定.控制器导出多步控制序列,置于执行器端的延迟补偿器根据网络时延从控制序列中选择控制信息并作用于控制对象,从而对时延进行补偿,使控制性能得到极大改善.控制器结合了PID控制和预测控制的优点,具有较强的鲁棒性和工程意义.最后通过构造Lyapunov函数对闭环系统的稳定性进行了分析,并通过仿真验证了该算法的有效性.     

一种基于DMC的新型预测PID控制器及其整定(英文)

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.     

A robust distributed model predictive control algorithm

Although distributed model predictive control (DMPC) has received significant attention in the literature, the robustness of DMPC with respect to model errors has not been explicitly addressed. In this paper, a novel online algorithm that deals explicitly with model errors for DMPC is proposed. The algorithm requires decomposing the entire system into N subsystems and solving N convex optimization problems to minimize an upper bound on a robust performance objective by using a time-varying state-feedback controller for each subsystem. Simulations examples were considered to illustrate the application of the proposed method.     

水泥生料立磨压差的广义预测PID控制

针对立磨粉磨系统的非线性、大滞后、慢时变问题,设计了广义预测PID控制器(GPC-PID).通过构造广义预测控制目标函数中的控制加权序列使广义预测控制具有PID控制算法的结构,通过广义预测控制和PID的相互递推关系计算PID参数.仿真结果表明,广义预测PID控制能较好地稳定磨内压差,并且具有响应速度快、抗干扰性强、鲁棒性好等优点.     

一种新的PID自校正调节器

提出了一种新的ＰＩＤ自校正调节器，这种调节器是基于Ｓｃｈｗａｒｚｅ的系统辨别方法和Ｌａｔｚｅｌ的参数整定方法基础上设计的、仿真实例和实际运行表明该控制器是可行的。     

A model-based supervisory energy management strategy for a 12 V vehicle electrical system

This paper describes the development, implementation, and experimental verification of a supervisory energy management strategy for the vehicle electrical system of a passenger car. The control strategy commands the alternator duty cycle such that vehicle fuel economy is optimized whilst the instantaneous load current demand is met and constraints on the system voltage and battery state of charge are satisfied.The work is based on a control-oriented model of the vehicle electrical system, experimentally validated against vehicle data. Then, a constrained global optimal control problem is formulated for the energy management of the electrical system, and analytically solved using the Pontryagin׳s Minimum Principle (PMP). The optimal solution obtained is evaluated for a range of different driving cycles and electrical load current profiles, leading to the formulation of an adaptive supervisory control strategy that is implemented and tested in vehicle.     

NMPS基于DCS的预测PID控制器鲁棒稳定性分析

针对基于DCS的预测PID的控制系统,利用Kharitonov定理和边缘理论分析其在参数不确定情况下输入输出鲁棒稳定性。具体对NMPS（非最小相位系统）给出了系统保持稳定的最大过程参数区间。理论和分析仿真结果表明,当过程参数偏离标称值时,该算法能使系统保持很好的鲁棒稳定性。     

预测-PID串级控制在发酵过程中的应用

本文介绍一种用动态矩阵预测-PID串级控制在抗生素发酵过程中的应用。阐明了系统的控制策略和控制算法。系统具有良好的跟踪性和鲁棒性。     

一种新型非线性PID控制器

将非线性函数与简单的PID控制器相级联，构成一种新型的非线性PID控制器，以提高现有PID控制器的性能，新型PID控制器的设计过程十分简单，只要适当构造非线性函数，并与原PID控制器级联起来便可实现，数值仿真结果表明，所提出的PID控制器比简单的PID控制器具有更好的动静态性能。     

一种新型模糊非线性PID控制器

采用一维输入一维输出的模糊映射关系与传统PID控制器相级联的方式，构成一个模糊非线性PID控制器以提高现有PID控制器的性能．一维模糊控制器无需选择与调整量化因子和比例因子，采用五条规则，易于实现．数值仿真和误差泛函积分评价指标表明，所提出的模糊非线性PID控制器比现有控制器具有更好的动静态性能．     

A novel optimal PID controller autotuning design based on the SLP algorithm

A novel optimal proportional integral derivative (PID) autotuning controller design based on a new algorithm approach, the “swarm learning process” (SLP) algorithm, is proposed. It improves the convergence and performance of the autotuning PID parameter by applying the swarm and learning algorithm concepts. Its convergence is verified by two methods, global convergence and characteristic convergence. In the case of global convergence, the convergence rule of a random search algorithm is employed to judge, and Markov chain modelling is used to analyse. The superiority of the proposed method, in terms of characteristic convergence and performance, is verified through the simulation based on the automatic voltage regulator and direct current motor control system. Verification is performed by comparing the results of the proposed model with those of other algorithms, that is, the ant colony optimization with a new constrained Nelder–Mead algorithm, the genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, and a neural network (NN). According to the global convergence analysis, the proposed method satisfies the convergence rule of the random search algorithm. With respect to the characteristic convergence and performance, the proposed method provides a better response than the GA, the PSO, and the NN for both control systems.     

基于专家控制规则的PID控制器

综合了专家系统和ＰＩＤ控制两者的优点，提出一种基于专家控制规则的ＰＩＤ控制算法。仿真及实验研究均证明了该方法的可行性和有效性。     

基于RBF神经网络与Smith预估补偿的智能PID控制

针对工业控制中普遍存在的大滞后现象,提出了一种将RBF神经网络算法和Smith预估补偿算法与传统的PID控制器相结合的智能RBF-Smith-PID控制策略。该方法利用RBF神经网络的在线学习、控制参数自整定能力,和Smith预估补偿对纯滞后系统的良好控制,有效地克服了常规PID控制的缺陷,提高了系统的鲁棒性和自适应性,对纯滞后系统起到了良好的控制。     

纸浆浓度专家PID控制

本文简要的分析了普通PID控制的不足，在这一基础上介绍了专家PID控制的特点，并提出了一种新的控制方案——专家PID控制，通过与普通PID浓度控制曲线相比，该方案具有较好的动态性能和鲁棒性。     

DeltaV控制系统中PID不同联锁类型的应用实现

本文介绍了DeltaV控制系统中PID不同联锁类型的应用实现。并根据某工厂生产实际中三种不同联锁类型的要求．应用DeltaV系统提供的多种功能模块，搭建相应的控制策略以满足过程控制的需要。