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Keywords: optimal control
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Proceedings Papers

Proc. ASME. DSCC2019, Volume 1: Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing, V001T08A005, October 8–11, 2019
Paper No: DSCC2019-9075
... the optimal control law is realistic and can be implemented in practice (e.g. there should be no regen when battery is almost full). The target vehicle intelligently controls the vehicle speed and car-following distance based on predicted traffic conditions using real-time information enabled by...
Proceedings Papers

Proc. ASME. DSCC2019, Volume 3, Rapid Fire Interactive Presentations: Advances in Control Systems; Advances in Robotics and Mechatronics; Automotive and Transportation Systems; Motion Planning and Trajectory Tracking; Soft Mechatronic Actuators and Sensors; Unmanned Ground and Aerial Vehicles, V003T21A012, October 8–11, 2019
Paper No: DSCC2019-9248
... Abstract Optimal control of wheel loaders in short loading cycles is studied in this paper. For modeling the wheel loader, the data from a validated diesel engine model is used to find a control oriented mean value engine model. The driveline is modeled as a switched system with three constant...
Proceedings Papers

Proc. ASME. DSCC2013, Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems, V002T33A006, October 21–23, 2013
Paper No: DSCC2013-4051
... equations of such robots and then study the trajectory optimization problem in order to solve for the optimal control policy. We test two different approaches for this problem, namely a shooting and a collocation method, for evaluating and optimizing a performance index. Trajectory optimization...
Proceedings Papers

Proc. ASME. DSCC2012-MOVIC2012, Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems, 703-709, October 17–19, 2012
Paper No: DSCC2012-MOVIC2012-8802
... surface modeling. This extends in a natural manner previous work by several of the authors (Hennessey and Shakiban) on both the 1D and 2D curved surface brachistochrone using optimal control and resulting in a two-point boundary value problem. DEM data permits an accurate representation of the surface in...
Proceedings Papers

Proc. ASME. DSCC2011, ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 1, 99-106, October 31–November 2, 2011
Paper No: DSCC2011-6172
... stochastic dynamic programming based optimal controller. For designing a SDP based controller, an infinite horizon problem is setup with power demand from driver modeled as random Markov process. The objective is to maximize system level efficiency by optimizing (i) the power split between engine and...
Proceedings Papers

Proc. ASME. DSCC2011, ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 2, 279-286, October 31–November 2, 2011
Paper No: DSCC2011-6138
.... The controller performance is then evaluated in the Engine-in-the-Loop (EIL) facility. Neuro dynamic programming (NDP) reinforcement learning series hydraulic hybrid power management engine-in-the-loop (EIL) transient diesel emissions online learning optimal control numerical...