Constrained data-driven controller tuning for nonlinear systems

This paper proposes a data-driven algorithm that solves an optimal control problem by iteratively tuning the controller. The data-driven algorithm solves the optimization problem for a nonlinear process with a linear controller, accounting for operational constraints and employing an interior-point barrier (IPB) algorithm. The search process in the IPB algorithm requires first-order information which is generated using identified models via neural networks in order to reduce the number of experiments. A case study which deals with the angular position control of a nonlinear aerodynamic system is included to validate the new algorithm by simulation results.

[1]  I-Jeng Wang,et al.  Stochastic optimisation with inequality constraints using simultaneous perturbations and penalty functions , 2008, Int. J. Control.

[2]  Milos Manic,et al.  Self-Organizing Fuzzy Haptic Teleoperation of Mobile Robot Using Sparse Sonar Data , 2011, IEEE Transactions on Industrial Electronics.

[3]  M. H. Wright.  The interior-point revolution in optimization: History, recent developments, and lasting consequences , 2004 .

[4]  Zhuo Wang,et al.  From model-based control to data-driven control: Survey, classification and perspective , 2013, Inf. Sci..

[5]  Mojtaba Ahmadieh Khanesar,et al.  Extended Kalman Filter Based Learning Algorithm for Type-2 Fuzzy Logic Systems and Its Experimental Evaluation , 2012, IEEE Transactions on Industrial Electronics.

[6]  Drago Matko,et al.  The design of observers for formation-flying control , 2013 .

[7]  Danwei Wang,et al.  A Data-Driven Iterative Feedback Tuning Approach of ALINEA for Freeway Traffic Ramp Metering With PARAMICS Simulations , 2013, IEEE Transactions on Industrial Informatics.

[8]  Sergio M. Savaresi,et al.  Virtual reference feedback tuning: a direct method for the design of feedback controllers , 2002, Autom..

[9]  Xinghuo Yu,et al.  High-Order Terminal Sliding-Mode Observer for Parameter Estimation of a Permanent-Magnet Synchronous Motor , 2013, IEEE Transactions on Industrial Electronics.

[10]  Chuanhou Gao,et al.  Data-Driven Time Discrete Models for Dynamic Prediction of the Hot Metal Silicon Content in the Blast Furnace—A Review , 2013, IEEE Transactions on Industrial Informatics.

[11]  R. Skelton,et al.  Markov Data-Based LQG Control , 2000 .

[12]  Yoji Yamada,et al.  Force control with safety constraints via Iterative Feedback Tuning , 2009, 2009 IEEE International Conference on Robotics and Automation.

[13]  Claudia-Adina Dragos,et al.  Data-Driven Reference Trajectory Tracking Algorithm and Experimental Validation , 2013, IEEE Transactions on Industrial Informatics.

[14]  S. Preitl,et al.  Stable Iterative Correlation-based Tuning algorithm for servo systems , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[15]  Per-Olof Gutman,et al.  Nonlinear controller tuning based on a sequence of identifications of linearized time-varying models , 2009 .

[16]  József K. Tar,et al.  Generic two-degree-of-freedom linear and fuzzy controllers for integral processes , 2009, J. Frankl. Inst..

[17]  Pierre Carrette,et al.  Synthetic generation of the gradient for an iterative controller optimization method , 1997, 1997 European Control Conference (ECC).

[18]  Simone Formentin,et al.  A Data-Driven Approach to Mixed-Sensitivity Control With Application to an Active Suspension System , 2013, IEEE Transactions on Industrial Informatics.

[19]  Hiroshi Fujimoto,et al.  RRO Compensation of Hard Disk Drives With Multirate Repetitive Perfect Tracking Control , 2009, IEEE Transactions on Industrial Electronics.

[20]  Bo Wahlberg,et al.  A primal-dual interior-point method for iterative feedback tuning , 1999 .

[21]  You Zhou,et al.  GPU-Based Parallel Multi-objective Particle Swarm Optimization , 2011 .

[22]  Brian D. O. Anderson,et al.  Iterative Controller Optimization for Nonlinear Systems , 2003 .

[23]  David Wang,et al.  Robust Data-Driven Modeling Approach for Real-Time Final Product Quality Prediction in Batch Process Operation , 2011, IEEE Transactions on Industrial Informatics.

[24]  J. Spall,et al.  Stochastic optimization with inequality constraints using simultaneous perturbations and penalty functions , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[25]  Mo-Yuen Chow,et al.  Optimal Tradeoff Between Performance and Security in Networked Control Systems Based on Coevolutionary Algorithms , 2012, IEEE Transactions on Industrial Electronics.

[26]  Hao Yu,et al.  Advantages of Radial Basis Function Networks for Dynamic System Design , 2011, IEEE Transactions on Industrial Electronics.

[27]  Radu-Emil Precup,et al.  Lorenz System Stabilization Using Fuzzy Controllers , 2007, Int. J. Comput. Commun. Control.

[28]  J. Spall,et al.  Model-free control of nonlinear stochastic systems with discrete-time measurements , 1998, IEEE Trans. Autom. Control..

[29]  Biao Huang,et al.  A data driven subspace approach to predictive controller design , 2001 .

[30]  Stefan Preitl,et al.  Application of IFT and SPSA to Servo System Control , 2011, IEEE Transactions on Neural Networks.

[31]  Z. Johanyák.  Student Evaluation Based On Fuzzy Rule Interpolation , 2010 .

[32]  Péter Baranyi,et al.  TP model transformation as a way to LMI-based controller design , 2004, IEEE Transactions on Industrial Electronics.

[33]  Jiming Chen,et al.  An Online Optimization Approach for Control and Communication Codesign in Networked Cyber-Physical Systems , 2013, IEEE Transactions on Industrial Informatics.

[34]  A. Hansson,et al.  Automatic tuning for classical step-response specifications using iterative feedback tuning , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[35]  Svante Gunnarsson,et al.  Iterative feedback tuning: theory and applications , 1998 .

[36]  Teresa Orlowska-Kowalska,et al.  Implementation of a Sliding-Mode Controller With an Integral Function and Fuzzy Gain Value for the Electrical Drive With an Elastic Joint , 2010, IEEE Transactions on Industrial Electronics.

[37]  Marian P. Kazmierkowski,et al.  DSP-Based Control of Grid-Connected Power Converters Operating Under Grid Distortions , 2011, IEEE Transactions on Industrial Informatics.

[38]  Ján Vascák,et al.  Adaptation of fuzzy cognitive maps by migration algorithms , 2012, Kybernetes.