英文版：
Title: 2-DOF Fuzzy Controllers and Mechatronics Applications
Speaker: Academician Radu-Emil Precup
Time: 14:30-15:30, Octoober 11, 2022 (Tuesday)
Website: Teams Link
https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
Abstract: As pointed out in some classical papers on control, the extension from one-degree-of-freedom (1-DOF) controllers to two-degree-of-freedom (2-DOF) controllers enables the separate design with respect to the reference input (or the set-point) and the disturbance input (usually of load- type) in terms of a feedforward connection and transfer element inserted in the controller (and thus control system) structure. This allows the design of control systems with good dynamics performance with respect to both the reference input and the disturbance input, namely good set-point tracking and good disturbance rejection. The transition of the results specific to linear controllers to the fuzzy ones was suggested by Precup and Preitl in 1999 and 2003 leading to 2-DOF fuzzy controllers, which were first called fuzzy controlllers with non- homogenous dynamics with respect to the input channels, and further developed in 2009 and 2012 and applied to servo systems and electrical drives. This transition gives the opportunity to improve the control system performance especially when dealing with nonlinear processes.This lecture presents several issues concerning the design, tuning and implementation of 2-DOF fuzzy controllers focusing on 2-DOF PI-fuzzy controllers and 2-DOF PID-fuzzy controllers in their Mamdani and Takagi-Sugeno-Kang forms. The tuning is based on mapping the parameters of the linear PI and PID controllers to the parameters of the fuzzy controllers in terms of the modal equivalence principle. The linear controllers are tuned by Preitl’s and Precup’s Extended Symmetrical Optimum method (1999). The classical algebraic approach based on Diophantine equations and mapping the parameters of the 2-DOF linear controllers to the parameters of the 2-DOF fuzzy ones will be treated as well. This lecture highlights a part of the results obtained by the Process Control group in applications of 2-DOF fuzzy controllers. The results outlined in this lecture are related to processes in representative lab equipment in Process Control group’s labs and control systems in past and ongoing research contracts. Digital simulation results and experimental results are included.
Personal Introduction:
Radu-Emil Precup is currently a Director of the Council of Doctoral Studies of the Politehnica University of Timisoara, Romania, a member of the Council of the Doctoral School Automatic Control and Computers, Politehnica University of Bucharest, Romania, a member of the Computers, information technology and systems engineering committee as part of the CNATDCU, a director of the Automatic Systems Engineering Research Centre with the Politehnica University of Timisoara, Romania, a professor with the Department of Automation and Applied (previously named Industrial) Informatics, Faculty of Automation and Computers, Politehnica University of Timisoara, Romania, and a reviewer of the Swiss National Science Foundation (SNSF), Bern, Switzerland, CINECA, Bologna, Italy, the National Council of Science and Technology (CONACYT), Ciudad de Mexico, Mexico, and the Mobility and Reintegration Programme (MoRePro) of the Slovak Academy of Sciences, Bratislava, Slovakia, etc. He's current research fields include development and analysis of new control structures and algorithms including conventional control, fuzzy control, data-based control, model-free control, sliding mode control, neuro-fuzzy control; theory and applications of soft computing; systems modelling, identification and optimization (including nature-inspired algorithms); computer-aided design of control systems; applications to mechatronic systems (including automotive systems and mobile robots), embedded systems, control of power plants, servo systems, electrical driving systems, etc. So far, he has published nearly 30 monographs, published more than 380 high-quality papers, and was invited to give 19 academic speeches.
[Editor: Jian Wang]
中文版：
报告题目：双自由度模糊控制器及其机电一体化应用
报 告 人：Radu-Emil Precup院士
工作单位：蒂米什瓦拉理工大学（罗马尼亚）
报告时间：2022年10月11日（周二）14:30-15:30
报告链接：Teams Link
https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
内容摘要：
一些关于控制的经典论文中指出，从单自由度(1-DOF) 控制器到双自由度 (2-DOF) 控制器的扩展能够根据前馈连接和嵌入在控制器（以及控制系统）中的传递元件实现参考输入（或设定点）和扰动输入（通常是负载类型）的分离设计。这使得控制系统在参考输入和扰动输入方面都具有良好的动态性能，即良好的设定点跟踪和扰动抑制。Precup院士和 Preitl院士在 1999 年和 2003 年建议将线性控制器的具体结果转换到模糊控制器，从而提出了2-DOF 模糊控制器，它最初被命名为具有非均匀动态输入通道的模糊控制器，并在2009年和2012年得到进一步发展，应用于伺服系统和电气驱动。这种转变改善了控制系统的性能，尤其是在处理非线性过程时。本报告将介绍2-DOF模糊控制器的设计、调整和实现的几个问题，重点是 Mamdani 和 Takagi-Sugeno-Kang 形式的 2-DOF PI-模糊控制器和 2-DOF PID-模糊控制器。调整是基于模态等效原理将线性 PI 和 PID 控制器的参数映射到模糊控制器。线性控制器通过 Preitl 和 Precup 提出的扩展对称最优方法 (1999) 进行调整。基于丢番图方程和将 2-DOF 线性控制器参数映射到 2-DOF 模糊控制器的经典代数方法也将被处理。本报告将重点介绍进程控制组在 2-DOF 模糊控制器应用中获得的部分结果，这些结果与进程控制组实验室中代表性实验室设备中的进程以及过去和正在进行的研究合同中的控制系统有关，包括数字仿真结果和实验结果。
个人简介：
Radu-Emil Precup院士目前担任罗马尼亚蒂米什瓦拉理工大学博士研究委员会主任、布加勒斯特理工大学自动控制和计算机博士学院委员会委员，蒂米什瓦拉理工大学自动系统工程研究中心主任，自动化与信息应用系教授；同时兼任瑞士国家科学基金会 (SNSF)、意大利博洛尼亚CINECA、墨西哥城国家科学技术委员会 (CONACYT)以及斯洛伐克科学院流动性与重返社会计划 (MoRePro)等评委。Radu-Emil Precup 院士目前的研究领域包括新控制结构和算法的开发和分析，包括常规控制、模糊控制、基于数据的控制、无模型控制、滑模控制、神经模糊控制；软计算理论与应用；系统建模、识别和优化（包括启发算法）；控制系统的计算机辅助设计；在机电一体化系统（包括汽车系统和移动机器人）、嵌入式系统、电厂控制、伺服系统、电气驱动系统等方面的应用。迄今为止Radu-Emil Precup院士已出版专著近30部，发表高质量论文380余篇，19次受邀发表学术演讲。
【编辑：王健】