PID Control for a Class of Non-Affine Uncertain Systems

Although the classical PID controller is the most widely used ones in industrial processes which are typically nonlinear with uncertainties, almost all of the design methods for PID control are focused on linear systems. Recently, we have presented a mathematical theory for the design of linear PID control of nonlinear uncertain systems in [15], [16], where the input signal is assumed to be additive with no uncertainties in the input channel. The purpose of this paper is to establish a theory for the PID control of a class of second order non-affine uncertain systems, where the input channel may have uncertainties and is not necessarily additive. We will show that a 3-dimensional manifold can be constructed from which the three PID parameters can be arbitrarily chosen to make the closed-loop control system globally stable and the regulation error approaches to zero asymptotically. Moreover, for the case where the setpoint is also an equilibrium of the open-loop nonlinear system, we give a simple necessary and sufficient condition for the choice of the PD controller parameters by using the Markus- Yamabe theorem in differential equations.

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

[2]  Ming-Tzu Ho,et al.  PID controller design for robust performance , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[3]  Lei Guo,et al.  Further results on limitations of sampled-data feedback , 2014, J. Syst. Sci. Complex..

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

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

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

[7]  Shankar P. Bhattacharyya,et al.  A linear programming characterization of all stabilizing PID controllers , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[8]  Lei Guo,et al.  Decentralized PID control of multi-agent systems with nonlinear uncertain dynamics , 2017, 2017 36th Chinese Control Conference (CCC).

[9]  Neil Munro,et al.  Fast calculation of stabilizing PID controllers , 2003, Autom..

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

[11]  Lei Guo,et al.  On the Capability of PID Control for Nonlinear Uncertain Systems , 2016 .

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

[13]  Lei Guo,et al.  How much uncertainty can be dealt with by feedback? , 2000, IEEE Trans. Autom. Control..

[14]  Franco Blanchini,et al.  Characterization of PID and lead/lag compensators satisfying given H/sub /spl infin// specifications , 2004, IEEE Transactions on Automatic Control.

[15]  S. Hara,et al.  Robust PID control using generalized KYP synthesis: direct open-loop shaping in multiple frequency ranges , 2006, IEEE Control Systems.