An update algorithm design using moving Region of Attraction for SDRE based control law

Abstract State Dependent Riccati Equation (SDRE) methods have the considerable advantages over other nonlinear control methods. However, stability issues can be arisen in SDRE based control system due to the lack of the global asymptotic stability property. Therefore, the previous studies have usually shown that local asymptotic stability can be ensured by estimating a Region of Attraction (ROA) around the equilibrium point. These estimated regions for stability may become narrow or the condition to keep the states in this region may be very conservative. To resolve these issues, this paper proposes a novel SDRE method employing an update algorithm to re-estimate the ROA when the states tend to move out of the stable region. The tendency is checked using a condition which is developed based on a new theorem. The theorem proves that it is possible to redesign the previous ROA with respect to the current states lying close to its boundary for ensuring the “non-local” stability along the trajectory without the need of solving SDRE at each time instant, unlike the standard SDRE approach. Therefore, the new theorem is now able to enhance the stability of the SDRE based closed-loop control system. The feasibility of the proposed SDRE control method is tested in both simulations and experiments. A validated 3-DOF laboratory helicopter is used for experiments and the control objective for the helicopter is to realise a preplanned movement in both elevation and travel axes. The results reveal that the proposed SDRE approach enables the controlled plant to track the desired trajectory as satisfactorily as the standard SDRE approach, while only solving SDRE when needed. The proposed SDRE method reduces the computational load for practical implementation of the control algorithm whilst ensuring the stability over the operational region.

[1]  Metin U. Salamci,et al.  MRAC of a 3-DoF Helicopter with Nonlinear Reference Model , 2018, 2018 26th Mediterranean Conference on Control and Automation (MED).

[2]  Metin U. Salamci,et al.  SDRE optimal control of drug administration in cancer treatment , 2010 .

[3]  Metin U. Salamci,et al.  Mixed therapy in cancer treatment for personalized drug administration using model reference adaptive control , 2019, Eur. J. Control.

[4]  B. Kramer Solving Algebraic Riccati Equations via Proper Orthogonal Decomposition , 2014 .

[5]  Eric A. Wan,et al.  State-Dependent Riccati Equation Control for Small Autonomous Helicopters , 2007 .

[6]  Yew-Wen Liang,et al.  Control for a Class of Second-Order Systems via a State-Dependent Riccati Equation Approach , 2018, SIAM J. Control. Optim..

[7]  Tayfun Çimen,et al.  State-Dependent Riccati Equation (SDRE) Control: A Survey , 2008 .

[8]  Yisheng Zhong,et al.  Robust LQR Attitude Control of a 3-DOF Laboratory Helicopter for Aggressive Maneuvers , 2013, IEEE Transactions on Industrial Electronics.

[9]  Juan C. Cockburn,et al.  Streamlining the state-dependent Riccati Equation controller algorithm , 2007 .

[10]  Donald E. Kirk,et al.  Optimal control theory : an introduction , 1970 .

[11]  Andrew G. Alleyne,et al.  Design of a class of nonlinear controllers via state dependent Riccati equations , 2004, IEEE Transactions on Control Systems Technology.

[12]  A. Alleyne,et al.  A stability result with application to nonlinear regulation: theory and experiments , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[13]  Sangshin Kwak,et al.  Suboptimal Control Scheme Design for Interior Permanent-Magnet Synchronous Motors: An SDRE-Based Approach , 2014, IEEE Transactions on Power Electronics.

[14]  J. W. Curtis,et al.  Ensuring stability of state-dependent Riccati equation controllers via satisficing , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[15]  Metin U. Salamci,et al.  Sliding mode control for non-linear systems with adaptive sliding surfaces , 2012 .

[16]  Peng Shi,et al.  Adaptive Neural Fault-Tolerant Control of a 3-DOF Model Helicopter System , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[17]  Tayfun Çimen,et al.  Survey of State-Dependent Riccati Equation in Nonlinear Optimal Feedback Control Synthesis , 2012 .

[18]  Laura Celentano A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems , 2018 .

[19]  Luca Dieci,et al.  Numerical integration of the differential Riccati equation and some related issues , 1992 .

[20]  A. Papachristodoulou,et al.  Nonlinear control synthesis by sum of squares optimization: a Lyapunov-based approach , 2004, 2004 5th Asian Control Conference (IEEE Cat. No.04EX904).

[21]  Bahram Shafai,et al.  Stability radius for extended linearization with system uncertainty , 2010, 49th IEEE Conference on Decision and Control (CDC).

[22]  A. Alleyne,et al.  Estimation of stability regions of SDRE controlled systems using vector norms , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[23]  Metin U. Salamci,et al.  State Dependent Riccati Equation Based Model Reference Adaptive Stabilization of Nonlinear Systems with Application to Cancer Treatment , 2014 .

[24]  J. D. Pearson Approximation Methods in Optimal Control I. Sub-optimal Control† , 1962 .

[25]  J. Cloutier,et al.  Control designs for the nonlinear benchmark problem via the state-dependent Riccati equation method , 1998 .

[26]  Moharam Habibnejad Korayem,et al.  Optimal motion planning of non-linear dynamic systems in the presence of obstacles and moving boundaries using SDRE: application on cable-suspended robot , 2014 .

[27]  Joseph Bentsman,et al.  Constrained discrete-time state-dependent Riccati equation technique: A model predictive control approach , 2013, 52nd IEEE Conference on Decision and Control.

[28]  Andrew G. Alleyne,et al.  A Stability Result With Application to Nonlinear Regulation , 2002 .

[29]  Naser Babaei,et al.  Personalized drug administration for cancer treatment using Model Reference Adaptive Control. , 2015, Journal of theoretical biology.

[30]  John David Anderson,et al.  Aircraft performance and design , 1998 .

[31]  Metin U. Salamci,et al.  Suboptimal control of a 3 dof helicopter with state dependent riccati equations , 2017, 2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT).

[32]  Yisheng Zhong,et al.  Robust Attitude Regulation of a 3-DOF Helicopter Benchmark: Theory and Experiments , 2011, IEEE Transactions on Industrial Electronics.

[33]  Michael Basin,et al.  An Approach to Design Robust Tracking Controllers for Nonlinear Uncertain Systems , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[34]  Antonella Ferrara,et al.  Output tracking control of uncertain nonlinear second-order systems , 1997, Autom..

[35]  Tayfun Çimen,et al.  Systematic and effective design of nonlinear feedback controllers via the state-dependent Riccati equation (SDRE) method , 2010, Annu. Rev. Control..

[36]  Ming Xin,et al.  Alternative SDRE Scheme for Planar Systems , 2019, IEEE Transactions on Circuits and Systems II: Express Briefs.

[37]  Soon-Jo Chung,et al.  Exponential stability region estimates for the State-Dependent Riccati Equation controllers , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[38]  Peter J Seiler Stability region estimates for SDRE controlled systems using sum of squares optimization , 2003, Proceedings of the 2003 American Control Conference, 2003..

[39]  Yao Yu,et al.  Robust backstepping decentralized tracking control for a 3-DOF helicopter , 2015 .

[40]  Franck Plestan,et al.  Continuous Differentiator Based on Adaptive Second-Order Sliding-Mode Control for a 3-DOF Helicopter , 2016, IEEE Transactions on Industrial Electronics.

[41]  Ahmet Cagri Arican,et al.  Linear and nonlinear optimal controller design for a 3 DOF helicopter , 2018, 2018 19th International Carpathian Control Conference (ICCC).