基于闭环耦合度的大系统常规PID控制回路的投用规则

化工过程全流程为具有高维输入输出的多变量大系统,内部存在一定程度的耦合作用,因此其底层常规PID控制系统的设计、投用和整定也必然与整个系统的耦合程度有关。首先,提出了闭环相对增益和耦合度的概念,分析闭环相对增益在理想控制条件下与开环相对增益的等效性,发现闭环控制回路的反馈作用引起操纵变量和被控变量的关联,由此加剧整个系统的耦合程度,因此闭环控制回路并非投用得越多越好。然后,提出了基于闭环耦合度的化工过程大系统常规PID控制回路的投用规则,根据被控过程开环相对增益阵确定控制回路变量配对和投用顺序,依次投用各控制回路并计算控制回路的耦合度,当耦合度超过阈值时停止剩余控制回路的投用。最后,以典型多变量TE过程为例验证了该投用规则的有效性。     

基于幅值最优化的二自由度PID控制器参数自整定研究

通过两次继电反馈，测得被控对象两个关键信息点的频率特性，从而辨识得到二阶纯滞后模型；然后引入一种二自由度PID控制器结构，根据幅值最优化原理整定PID控制器的参数。仿真实验表明该整定方法使闭环系统具有很好的稳定性和鲁棒性。     

一种简单实用的自校正PID调节器

本文介绍一种自校正PID调节器。这种调节器的控制结构是一种改进的不完全微分型PID算法。其设计思想是通过系统辨识,估计被控对象的数学模型,将闭环系统校正为二阶振荡环节。操作人员所要做的工作只是根据工艺要求设定控制系统阶跃响应的上升时间t_r,调节器自动整定控制参数。一.对象模型已知时PID控制器设计设被控过程的传递函数为:     

基于PID对角优势补偿阵的过程多变量控制系统设计

化工过程一般为多变量系统,输入输出变量之间往往存在耦合作用,常规分散PID控制系统难以保证控制质量。为了削弱多变量系统的耦合作用,基于对角优势的设计准则,通过在若干频率点加权优化,设计PID动态预补偿阵。然后利用正Nyquist阵列设计法对补偿后的系统设计控制器,基于对角优势系统的Nyquist稳定判据,通过绘制优势度曲线和Gershgorin带判断系统的优势程度,初步确定反馈矩阵的稳定参数范围,再按照单输入单输出系统设计动态补偿器,使得系统满足动态控制品质要求。最后通过示例说明,该方法设计的集中控制系统与分散控制相比,控制性能具有一定的优势,且方法简便,容易实现。     

基于PID对角优势补偿阵的过程多变量控制系统设计

化工过程一般为多变量系统,输入输出变量之间往往存在耦合作用,常规分散PID控制系统难以保证控制质量。为了削弱多变量系统的耦合作用,基于对角优势的设计准则,通过在若干频率点加权优化,设计PID动态预补偿阵。然后利用正Nyquist阵列设计法对补偿后的系统设计控制器,基于对角优势系统的Nyquist稳定判据,通过绘制优势度曲线和Gershgorin带判断系统的优势程度,初步确定反馈矩阵的稳定参数范围,再按照单输入单输出系统设计动态补偿器,使得系统满足动态控制品质要求。最后通过示例说明,该方法设计的集中控制系统与分散控制相比,控制性能具有一定的优势,且方法简便,容易实现。     

基于神经网络的非线性时变对象自适应控制方法研究

针对工业控制中的非线性、时变和滞后被控对象,将神经网络辨识器和PID控制技术有机结合,构建自适应PID控制器,并引入知识先导学习算法,提高时间效率。仿真分析表明:该自适应PID控制器能够自动辨识被控对象模型、自整定控制参数,在辨识误差、响应时间及超调量等指标上均有良好表现。     

基于模糊自整定PID燃气锅炉仿真研究

针对燃气热水锅炉具有非线性、大惯性及多变量等特点,借助经验公式分析并用MATLAB系统辨识工具箱完成了系统数学模型的辨识,确定了燃气锅炉温度控制系统的模型结构可等效为一阶惯性加滞后环节,在此基础上确立了基于MATLAB的系统SIMULINK仿真框图,设计了模糊自整定PID控制器.通过模糊自整定PID与常规PID算法的仿真对比分析,得出模糊自整定PID不仅在调节时间、超调量等动态性能上的控制效果明显优于常规PID控制效果,而且增强了系统的鲁棒性和适应性,具有良好的动、静态性能.     

基于AMESim和Matlab／Simulink的注塑机合模液压伺服系统的仿真研究

利用AMEsim和Matlab／simulink的各自特点,以电液伺服阀闭环PID控制的注射机合模液压系统为研究对象,建立了液压系统的动态模型。再利用遗传算法对PID控制参数进行了整定。同肘分析了开环比例控制和闭环比例控制的注射机合模液压系统。结果表明：PID闭环控制的注射机合模液压伺服系统具有较好的响应速度、稳定性与精度。     

基于常数对角优势补偿阵的多变量控制系统逆Nyquist阵列设计

化工过程中的多变量系统变量之间往往存在耦合作用,在控制系统设计时一般将传递函数阵对角优势化,对角优势化后按多个单变量系统进行设计。由于传递函数逆阵的对角优势化更容易实现,本文采用伪对角化方法设计常数对角优势补偿阵实现传递函数逆阵的对角优势化,在一个或多个频率点上通过使开环传递函数逆阵每行的非对角项元素模平方之和最小,实现对角优势。然后,利用逆Nyquist阵列设计法对补偿后的系统设计控制器,基于逆Nyquist稳定判据,通过绘制优势度曲线和Gershgorin带判断系统的优势程度,根据Gershgorin带选定反馈矩阵的参数范围,按照单变量控制系统的方法设计动态补偿器,使系统满足动态控制品质的要求。最后通过3个示例说明本文的设计方法简便,且具有良好的控制性能。     

基于常数对角优势补偿阵的多变量控制系统逆Nyquist阵列设计

化工过程中的多变量系统变量之间往往存在耦合作用,在控制系统设计时一般将传递函数阵对角优势化,对角优势化后按多个单变量系统进行设计。由于传递函数逆阵的对角优势化更容易实现,本文采用伪对角化方法设计常数对角优势补偿阵实现传递函数逆阵的对角优势化,在一个或多个频率点上通过使开环传递函数逆阵每行的非对角项元素模平方之和最小,实现对角优势。然后,利用逆Nyquist阵列设计法对补偿后的系统设计控制器,基于逆Nyquist稳定判据,通过绘制优势度曲线和Gershgorin带判断系统的优势程度,根据Gershgorin带选定反馈矩阵的参数范围,按照单变量控制系统的方法设计动态补偿器,使系统满足动态控制品质的要求。最后通过3个示例说明本文的设计方法简便,且具有良好的控制性能。     

Decentralized fault-tolerant control system design for unstable processes

Fault-tolerant control is an important issue in control of mission critical processes. In this paper, a new approach to fault-tolerant control of unstable processes is proposed based on the Passivity Theorem. The control system is designed in two sequential steps: A multi-loop proportional controller is used to stabilize the unstable process; a passivity-based decentralized unconditionally stabilizing (DUS) controller is then applied to the stabilized process. While the multi-loop stabilizing controllers need to be built with redundancy, the DUS controller is inherently fault tolerant and can maintain closed-loop stability when any of its loops fail. By using a stabilizing proportional controller with the fewest loops, control redundancy can be reduced to the minimum level.     

基于神经网络和多模型的非线性自适应PID控制及应用

针对一类未知的单输入单输出离散非线性系统,提出了基于神经网络和多模型的非线性自适应PID控制方法。该方法由线性自适应PID控制器、神经网络非线性自适应PID控制器以及切换机构组成。采用线性自适应PID控制器可保证闭环系统所有信号有界;采用神经网络非线性自适应PID控制器可改善系统性能;通过引入合理的切换机制,能够在保证闭环系统稳定的同时,提高系统性能。理论分析表明,该方法能够保证闭环系统所有信号有界,如果适当地选择神经网络的结构和参数,系统的跟踪误差将收敛于任意给定的紧集。将所提出的方法应用于连续搅拌反应釜,仿真结果验证了所提出方法的有效性。由于该方法基于增量式数字PID控制器,在工业过程中有着广阔的应用前景。     

复合控制器及其在连消中的应用

由于常规PID控制方式对非线性、大滞后对象难以进行有效的控制,模糊控制具有很好的动态特性,所以结合常规PID和模糊控制的优势设计了参数自调整Fuzzy-PID复合控制器。通过模糊推理实现参数自调整,以使控制器能够适应不同对象和对象的不同状态。采用模糊推理的方法完成两种控制方式的平稳过渡。对某制药厂连消温度的控制表明,该控制器可以大幅度提高控制精度和缩短系统响应时间,从而避免了染菌事故的发生,提高了发酵单位。     

Performance assessment of cascade controllers for nitrate control in a wastewater treatment process

A cascade control strategy is proposed to the benchmark simulation model 1 (BSM1) to enhance the treatment performance of nitrogen removal in a biological wastewater treatment plant. The proposed control approach consists of two control loops, a primary outer loop and a secondary inner loop. The method has two controllers of which the primary loop has a model predictive control (MPC) controller and the secondary loop has a proportional-integralderivative (PID) controller, which is a cascade MPC-PID controller. The primary MPC controller is to control the nitrate concentration in the effluent, and the secondary PID controller is to control the nitrate concentration in the final anoxic compartment. The proposed method controls the nitrate concentrations in the effluent as well as in the final anoxic reactor simultaneously to strictly satisfy the quality of the effluent as well as to remove the effects of disturbances more quickly by manipulating the external carbon dosage rate. Because the control performance assessment (CPA) technique has the features of determining the capability of the current controller and locating the best achievable performance, the other novelty of this paper is to suggest a relative closed-loop potential index (RCPI) which updates the CPA technology into a closed-loop cascade controller. The proposed method is compared with a cascade PID-PID control strategy and the original PID controller in BSM1 and an improved performance of the suggested cascade MPC-PID controller is obtained by using the CPA approach.     

一种比例因子自调整的模糊预测函数控制

针对由主、副被控对象级联而成的大纯滞后系统,提出一种内回路采用PI控制、外回路采用具有比例因子自调整的模糊增量型预测函数控制策略,它将预测函数控制和具有比例因子自调整的模糊控制进行综合来共同控制由内回路和主被控对象构成的广义被控对象。大量的仿真实验表明:本方法较其他方法控制效果更好,即使在模型严重失配时,本方法仍具有很强的鲁棒性和抗干扰能力。     

Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes

This paper proposes a switching multi-objective model predictive control (MOMPC) algorithm for constrained nonlinear continuous-time process systems. Different cost functions to be minimized inMPC are switched to satisfy different performance criteria imposed at different sampling times. In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system, the dual-mode control method is used to design the switching MOMPC controller. In this method, a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC. The correction termis computed if the states are out of the terminal set and the free-parameters of the local control laware computed if the states are in the terminal set. The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions. Finally, implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.     

ENHANCED IMC-PID CONTROLLER DESIGN WITH LEAD-LAG FILTER FOR UNSTABLE AND INTEGRATING PROCESSES WITH TIME DELAY

In this article, a design method for a PID controller is proposed based on IMC principles for control of open loop integrating and unstable first-order processes with time delay. The design is based on H₂ optimal closed-loop transfer function for set point changes and step input disturbances. The method has one tuning parameter, and systematic guidelines are provided for the selection of this tuning parameter based on peak value of the sensitivity function. The performance of the designed controller is verified on various integrating and unstable processes, and it is observed that nominal and robust control performance is achieved with the proposed design method. Improved closed-loop performance was obtained when compared to other methods recently reported in the literature. Further, the proposed method provides good closed-loop performance even when there are large uncertainties in the process parameters.