Towards a Theoretical Foundation of PID Control for Uncertain Nonlinear Systems.

As is well-known, the classical PID control plays a dominating role in various control loops of industrial processes. However, a theory that can explain the rationale why the linear PID can successfully deal with the ubiquitous uncertain nonlinear dynamical systems and a method that can provide explicit design formulae for the PID parameters are still lacking. This paper is a continuation of the authors recent endeavor towards establishing a theoretical foundation of PID. We will investigate the rationale of PID control for a general class of high dimensional second order non-affine uncertain systems. We will show that a three dimensional parameter set can be constructed explicitly, such that whenever the PID parameters are chosen from this set, the closed-loop systems will be globally stable and the regulation error will converge to zero exponentially fast, under some suitable conditions on the system uncertainties. Moreover, we will show that the PD(PI) control can globally stabilize several special classes of high dimensional uncertain nonlinear systems. Furthermore, we will apply the Markus-Yamabe theorem in differential equations to provide a necessary and sufficient condition for the choice of the PI parameters for a class of one dimensional non-affine uncertain systems. These theoretical results show explicitly that the controller parameters are not necessary to be of high gain, and that the ubiquitous PID control does indeed have strong robustness with respect to both the system structure uncertainties and the selection of the controller parameters.

[1]  Peng Nian Chen,et al.  A Proof of the Jacobian Conjecture on Global Asymptotic Stability , 1996 .

[2]  Romeo Ortega,et al.  Global stabilisation of underactuated mechanical systems via PID passivity-based control , 2016, Autom..

[3]  Lawrence Markus,et al.  Global stability criteria for differential systems. , 1960 .

[4]  Tariq Samad,et al.  A Survey on Industry Impact and Challenges Thereof [Technical Activities] , 2017, IEEE Control Systems.

[5]  陈彭年,et al.  A proof of the Jacobian conjecture on global asymptotic stability , 1996 .

[6]  H. T,et al.  The future of PID control , 2001 .

[7]  Karl Johan Åström,et al.  PID Controllers: Theory, Design, and Tuning , 1995 .

[8]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[9]  Lingji Chen,et al.  Adaptive Control Design for Nonaffine Models Arising in Flight Control , 2004 .

[10]  I. Sandberg Global inverse function theorems , 1980 .

[11]  Shankar P. Bhattacharyya,et al.  PID Controllers for Time Delay Systems , 2004 .

[12]  M. Krstic,et al.  PID tuning using extremum seeking: online, model-free performance optimization , 2006, IEEE Control Systems.

[13]  Lei Guo,et al.  PID controller design for second order nonlinear uncertain systems , 2017, Science China Information Sciences.

[14]  Lei Guo,et al.  Extended PID Control of Nonlinear Uncertain Systems , 2019, 1901.00973.

[15]  A. O'Dwyer School of Electrical and Electronic Engineering 2006-0101 PI and PID controller tuning rules : an overview and personal perspective , 2017 .

[16]  Shankar P. Bhattacharyya,et al.  Controller Synthesis Free of Analytical Models: Three Term Controllers , 2008, IEEE Transactions on Automatic Control.

[17]  Lei Guo,et al.  Feedback and uncertainty: Some basic problems and results , 2020, Annu. Rev. Control..

[18]  Rey-Chue Hwang,et al.  A self-tuning PID control for a class of nonlinear systems based on the Lyapunov approach , 2002 .

[19]  C. Desoer,et al.  Global inverse function theorem , 1972 .

[20]  Hassan K. Khalil,et al.  Universal integral controllers for minimum-phase nonlinear systems , 2000, IEEE Trans. Autom. Control..

[21]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[22]  Venkat Krovi,et al.  Submitted to the Special Issue in "Novel Robotics and Control" Journal of Dynamic Systems, Measurement, and Control Transactions of the ASME , 2005 .

[23]  Suguru Arimoto,et al.  A New Feedback Method for Dynamic Control of Manipulators , 1981 .

[24]  Cheng ZHAO,et al.  PID Control for a Class of Non-Affine Uncertain Systems , 2018, 2018 37th Chinese Control Conference (CCC).

[25]  Tore Hägglund,et al.  The future of PID control , 2000 .

[26]  Shigeyuki Hosoe PID controller design for robust performance , 2013, The SICE Annual Conference 2013.

[27]  Robert Feßler,et al.  A proof of the two-dimensional Markus-Yamabe Stability Conjecture and a generalization , 1995 .

[28]  Sheng Zhong,et al.  A parameter formula connecting PID and ADRC , 2020, Science China Information Sciences.

[29]  Lei Guo,et al.  Theory and Design of PID Controller for Nonlinear Uncertain Systems , 2019, IEEE Control Systems Letters.