Epsilon-Trig Regularization Method for Bang-Bang Optimal Control Problems

Bang-bang control problems have numerical issues due to discontinuities in the control structure and require smoothing when using optimal control theory that relies on derivatives. Traditional smooth regularization introduces a small error into the original problem using error controls and an error parameter to enable the construction of accurate smoothed solutions. When path constraints are introduced into the problem, the traditional smooth regularization fails to bound the error controls involved. It also introduces a dimensional inconsistency related to the error parameter. Moreover, the traditional approach solves for the error controls separately, which makes the problem formulation complicated for a large number of error controls. The proposed Epsilon-Trig regularization method was developed to address these issues by using trigonometric functions to impose implicit bounds on the controls. The system of state equations is modified such that the smoothed control is expressed in sine form, and only one of the state equations contains an error control in cosine form. Since the Epsilon-Trig method has an error parameter only in one state equation, there is no dimensional inconsistency. Moreover, the Epsilon-Trig method only requires the solution to one control, which greatly simplifies the problem formulation. Its simplicity and improved capability over the traditional smooth regularization method for a wide variety of problems including the Goddard rocket problem have been discussed in this study.

[1]  Robert D. Braun,et al.  Rapid Indirect Trajectory Optimization for Conceptual Design of Hypersonic Missions , 2015 .

[2]  Jing Li,et al.  Fuel-Optimal Low-Thrust Reconfiguration of Formation- Flying Satellites via Homotopic Approach , 2012 .

[3]  M. Kim,et al.  Continuous Low-Thrust Trajectory Optimization: Techniques and Applications , 2005 .

[4]  Thomas Haberkorn,et al.  Low thrust minimum-fuel orbital transfer: a homotopic approach , 2004 .

[5]  Yaobin Chen,et al.  A Continuation Method for Singular Optimal Control Synthesis , 1993, 1993 American Control Conference.

[6]  James M. Longuski,et al.  Optimal Control with Aerospace Applications , 2013 .

[7]  R. Epenoy,et al.  New smoothing techniques for solving bang–bang optimal control problems—numerical results and statistical interpretation , 2002 .

[8]  Shurong Li,et al.  Optimization method for solving bang-bang and singular control problems , 2012 .

[9]  Anil V. Rao,et al.  GPOPS-II , 2014, ACM Trans. Math. Softw..

[10]  Dinh Van Huynh,et al.  Algebra and Its Applications , 2006 .

[11]  K. B. McAuley,et al.  On the computation of optimal singular controls , 1995, Proceedings of International Conference on Control Applications.

[12]  Leon Lapidus,et al.  The computation of optimal singular bang‐bang control I: Linear systems , 1972 .

[13]  Hexi Baoyin,et al.  Practical Techniques for Low-Thrust Trajectory Optimization with Homotopic Approach , 2012 .

[14]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .

[15]  Cristiana J. Silva,et al.  Smooth Regularization of Bang-Bang Optimal Control Problems , 2010, IEEE Transactions on Automatic Control.

[16]  I. Kolmanovsky,et al.  Enhanced Smoothing Technique for Indirect Optimization of Minimum-Fuel Low-Thrust Trajectories , 2016 .

[17]  Michael J. Grant,et al.  Trigonomerization of Optimal Control Problems with Bounded Controls , 2016 .

[18]  Junfeng Li,et al.  Homotopic approach and pseudospectral method applied jointly to low thrust trajectory optimization , 2012 .