A Conjugate Gradient-based BPTT-like Optimal Control Algorithm
Proc. of 2009 IEEE Multi-conference on Systems and Control, St. Petersburg, Russia2009The paper presents a conjugate gradient-based numerical algorithm for optimal control of nonlinear multivariable systems with control and state vectors constraints. The algorithm has a backward-in-time recurrent structure similar to the backpropagation-through-time (BPTT) algorithm. The emphasis is on implementation and testing of various conjugate gradient methods. A vehicle dynamics control example demonstrates that the use of conjugate gradient algorithm leads to substantial reduction of computational time when compared to the standard gradient algorithm with a constant learning rate. optimal control; backpropagation algorithms; control systems; cost function; vehicle dynamics; nonlinear control systems; nonlinear equations; testing; gradient methods; automotive engineering
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Proc. of 2009 IEEE Multi-conference on Systems and Control, St. Petersburg, Russia
2009
Cited by 29
▾
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[2] Accuracy Evaluation of a Lightweight Analytic Vehicle Dynamics Model for Maneuver Planning* 🔗International Conference Robotics and Automation Engineering, 2020
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[3] Two-phase A*: A real-time global motion planning method for non-holonomic unmanned ground vehicles 🔗Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, 2020
-
[4] Guided Motion Planning for Snake-like Robots Based on Geometry Mechanics and HJB Equation 🔗IEEE transactions on industrial electronics (1982. Print), 2019
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[6] Comparison of seven backpropagation algorithms for three phase power quality assessment 🔗IEEE Region 10 Conference, 2017
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[7] Electromagnetic Compatibility Estimator Using Scaled Conjugate Gradient Backpropagation Based Artificial Neural Network 🔗IEEE Transactions on Industrial Informatics, 2017
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[12] A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles 🔗IEEE Transactions on Intelligent Vehicles, 2016
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[13] Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles 🔗International Journal of Systems Science, 2014
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[14] A computational approach to parameter identification of spatially distributed nonlinear systems with unknown initial conditions 🔗IEEE Workshop on Robotic Intelligence In Informationally Structured Space, 2014
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[16] Sliding-mode control of a wheeled vehicle using neural network estimator 🔗Asian Control Conference, 2013
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[18] A numerical algorithm for nonlinear L2-gain optimal control with application to vehicle yaw stability control 🔗IEEE Conference on Decision and Control, 2012
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[19] Optimization of control variables of a series-parallel hybrid electric power train 🔗International Conference on Computability and Complexity in Analysis, 2012
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[20] Optimal control of automated transmission engagement process 🔗International Conference on Computability and Complexity in Analysis, 2012
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[21] Numerical algorithm for nonlinear state feedback ℌ∞ optimal control problem 🔗2012 20th Mediterranean Conference on Control & Automation (MED), 2012
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[22] Initial conditions optimization of nonlinear dynamic systems with applications to output identification and control 🔗2012 20th Mediterranean Conference on Control & Automation (MED), 2012
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[27] Global convergence properties of conjugate gradient methods for optimal control problems 🔗Cybersecurity and Cyberforensics Conference, 2016
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[29] A conjugate gradient-based BPTT-like optimal control algorithm 🔗2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC), 2009