Graphical Robust PID Tuning Based on Uncertain Systems for Disturbance Rejection Satisfying Multiple Objectives

Tuning parameters of the PID controller which satisfying certain requirements is the key goal in uncertain systems. However, most studies ignored the disturbance rejection performance of the controller. This study investigated a novel graphical design method of improving disturbance rejection performance for uncertain system. The proposed method evaluates the disturbance rejection performance by analyzing reference to disturbance ratio (RDR). At the same time, the parameters of the controller which can stabilize the system and meet the robustness specification for the uncertain system are determined by specifications-oriented Kharitonov region (SOKR). Thus, the intersection region satisfying multiple objectives can be found by using this graphical method. Examples are given to demonstrate the flexibility and effectiveness of the proposed method.

[1]  Huang,et al.  Robust PID tuning strategy for uncertain plants based on the Kharitonov theorem , 2000, ISA transactions.

[2]  Yuanqing Xia,et al.  Active disturbance rejection control for power plant with a single loop , 2012 .

[3]  Lei Guo,et al.  Disturbance-Observer-Based Control and Related Methods—An Overview , 2016, IEEE Transactions on Industrial Electronics.

[4]  Cemal Keles,et al.  Disturbance rejection performance analyses of closed loop control systems by reference to disturbance ratio. , 2015, ISA transactions.

[5]  Shihua Li,et al.  Disturbance observer based multi-variable control of ball mill grinding circuits , 2009 .

[6]  Balarko Chaudhuri,et al.  Wide-area measurement-based stabilizing control of power system considering signal transmission delay , 2004 .

[7]  Jeang-Lin Chang Robust output feedback disturbance rejection control by simultaneously estimating state and disturbance , 2011 .

[8]  Jianbo Su,et al.  Composite disturbance rejection control based on generalized extended state observer. , 2016, ISA transactions.

[9]  C. A. Gómez-Pérez,et al.  Reference Trajectory Design Using State Controllability for Batch Processes , 2015 .

[10]  M. Chidambaram,et al.  Robust controller design for First order Plus Time Delay systems using Kharitonov Theorem , 2014 .

[11]  Youxian Sun,et al.  Robust Digital PI Control for Uncertain Time‐delay Systems in Process Industry , 2008 .

[12]  John Matthew Santosuosso,et al.  Dynamic optimization of batch processing , 2003 .

[13]  Shang-Hong Shih,et al.  Graphical computation of gain and phase margin specifications-oriented robust PID controllers for uncertain systems with time-varying delay , 2010, Proceedings of the 29th Chinese Control Conference.

[14]  Qibing Jin,et al.  Analytical IMC-PID design in terms of performance/robustness tradeoff for integrating processes: From 2-Dof to 1-Dof , 2014 .

[15]  Jun Yang,et al.  Disturbance rejection of ball mill grinding circuits using DOB and MPC , 2010 .

[16]  Baris Baykant Alagoz,et al.  Implicit disturbance rejection performance analysis of closed loop control systems according to communication channel limitations , 2015 .

[17]  Ramon Vilanova,et al.  On the model matching approach to PID design: Analytical perspective for robust Servo/Regulator tradeoff tuning , 2010 .

[18]  Saurabh Srivastava,et al.  A PI/PID controller for time delay systems with desired closed loop time response and guaranteed gain and phase margins , 2016 .

[19]  Edward J. Davison,et al.  Control of time delay processes with uncertain delays: Time delay stability margins , 2006 .

[20]  Caixia Liu,et al.  Hybrid feedback stabilization of fuzzy nonlinear systems , 2011 .

[21]  De-Jin Wang A PID controller set of guaranteeing stability and gain and phase margins for time-delay systems , 2012 .