A nonlinear robust PI controller for an uncertain system

This paper presents a smooth control strategy for the regulation problem of an uncertain system, which assures uniform ultimate boundedness of the closed-loop system inside of the zero-state neighbourhood. This neighbourhood can be made arbitrarily small. To this end, a class of nonlinear proportional integral controllers or PI controllers was designed. The behaviour of this controller emulates very close a sliding mode controller. To accomplish this behaviour saturation functions were combined with traditional PI controller. The controller did not need a high-gain controller or a sliding mode controller to accomplish robustness against unmodelled persistent perturbations. The obtained closed-solution has a finite time of convergence in a small vicinity. The corresponding stability convergence analysis was done applying the traditional Lyapunov method. Numerical simulations were carried out to assess the effectiveness of the obtained controller.

[1]  Pierre Bernhard,et al.  SURVEY OF LINEAR QUADRATIC ROBUST CONTROL , 2002, Macroeconomic Dynamics.

[2]  L. Fridman,et al.  Observation and Identification of Mechanical Systems via Second Order Sliding Modes , 2006 .

[3]  A. Levant Universal SISO sliding-mode controllers with finite-time convergence , 2001 .

[4]  J. Humberto Pérez-Cruz,et al.  Robust Adaptive Neurocontrol of SISO Nonlinear Systems Preceded by Unknown Deadzone , 2012 .

[5]  Jose de Jesus Rubio,et al.  Modified optimal control with a backpropagation network for robotic arms , 2012 .

[6]  M. Yazdanpanah,et al.  A novel low chattering sliding mode controller , 2004, 2004 5th Asian Control Conference (IEEE Cat. No.04EX904).

[7]  Zhihua Qu,et al.  Robust tracking control of robot manipulators , 1996 .

[8]  Xiaoou Li,et al.  Pd Control of robot with velocity estimation and uncertainties compensation , 2006, Int. J. Robotics Autom..

[9]  Leonid M. Fridman,et al.  Two-Stage Neural Observer for Mechanical Systems , 2008, IEEE Transactions on Circuits and Systems II: Express Briefs.

[10]  Antonella Ferrara,et al.  APPLICATIONS OF A SUB‐OPTIMAL DISCONTINUOUS CONTROL ALGORITHM FOR UNCERTAIN SECOND ORDER SYSTEMS , 1997 .

[11]  Hebertt Sira-Rami ' rez A DYNAMICAL VARIABLE STRUCTURE CONTROL STRATEGY IN ASYMPTOTIC OUTPUT TRACKING PROBLEMS , 1991 .

[12]  Wen Yu,et al.  Robust Visual Servoing of Robot Manipulators with Neuro Compensation , 2005, J. Frankl. Inst..

[13]  Alexander S. Poznyak,et al.  Multilayer dynamic neural networks for non-linear system on-line identification , 2001 .

[14]  Hebertt Sira-Ramírez,et al.  A dynamical variable structure control strategy in asymptotic output tracking problems , 1993, IEEE Trans. Autom. Control..

[15]  Plamen P. Angelov,et al.  Uniformly Stable Backpropagation Algorithm to Train a Feedforward Neural Network , 2011, IEEE Transactions on Neural Networks.

[16]  M. Spong,et al.  Robust Control Design Techniques for a Class of Nonlinear Systems , 1986, 1986 American Control Conference.

[17]  Alexander S. Poznyak,et al.  Lyapunov function design for finite-time convergence analysis: "Twisting" controller for second-order sliding mode realization , 2009, Autom..

[18]  Alexander S. Poznyak,et al.  Indirect adaptive control via parallel dynamic neural networks , 1999 .

[19]  L. Fridman,et al.  Observation and Identification of Mechanical Systems via Second Order Sliding Modes , 2006, International Workshop on Variable Structure Systems, 2006. VSS'06..

[20]  R. Ortega,et al.  A semiglobally stable output feedback PI2D regulator for robot manipulators , 1995, IEEE Trans. Autom. Control..

[21]  Ilyas Eker Sliding mode control with PID sliding surface and experimental application to an electromechanical plant. , 2006, ISA transactions.

[22]  A. Levant Sliding order and sliding accuracy in sliding mode control , 1993 .

[23]  Jean-Pierre Barbot,et al.  Sliding Mode Control In Engineering , 2002 .

[24]  M. Grimble Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems , 1994 .

[25]  Bijnan Bandyopadhyay,et al.  Non-linear sliding surface: towards high performance robust control , 2012 .

[26]  F.-T. Cheng,et al.  Robust Control of Manipulators Using the Computed Torque plus H∞ Compensation Method , 1996 .

[27]  Alessandro Astolfi,et al.  Nonlinear PI control of uncertain systems: an alternative to parameter adaptation , 2002, Syst. Control. Lett..

[28]  Wen Yu,et al.  Stability Analysis of Nonlinear System Identification via Delayed Neural Networks , 2007, IEEE Transactions on Circuits and Systems II: Express Briefs.

[29]  A. Benabdallah,et al.  On the Practical Output Feedback Stabilization for Nonlinear Uncertain Systems , 2009 .

[30]  P. Kokotovic,et al.  Adaptive nonlinear design with controller-identifier separation and swapping , 1995, IEEE Trans. Autom. Control..

[31]  Luis Arturo Soriano,et al.  An asymptotic stable proportional derivative control with sliding mode gravity compensation and with a high gain observer for robotic arms , 2010 .

[32]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[33]  P. Dorato,et al.  Survey of robust control for rigid robots , 1991, IEEE Control Systems.

[34]  Víctor Santibáñez,et al.  A New Saturated Nonlinear PID Global Regulator for Robot Manipulators1 1Work partially supported by CONACyT (grant 45826) and DGEST, Mexico. , 2008 .

[35]  A. Zinober,et al.  Continuous approximation of variable structure control , 1986 .

[36]  Marco H. Terra,et al.  Robust Control of Robots: Fault Tolerant Approaches , 2011 .

[37]  Yuri B. Shtessel,et al.  Higher order sliding modes , 2008 .

[38]  Vicente Parra-Vega,et al.  Second Order Sliding Mode Control for Robot Arms with Time Base Generators for Finite-Time Tracking , 2001 .

[39]  J. Humberto Pérez-Cruz,et al.  Evolving intelligent system for the modelling of nonlinear systems with dead-zone input , 2014, Appl. Soft Comput..

[40]  Leonid Fridman,et al.  Finite-time convergence analysis for “Twisting” controller via a strict Lyapunov function , 2010, 2010 11th International Workshop on Variable Structure Systems (VSS).