TY - JOUR
T1 - Fast and global optimal energy-efficient control allocation with applications to over-actuated electric ground vehicles
AU - Chen, Yan
AU - Wang, Junmin
N1 - Funding Information:
Manuscript received October 06, 2010; revised February 20, 2011; accepted July 05, 2011. Date of publication August 12, 2011; date of current version June 28, 2012. This work was supported by Office of Naval Research (ONR) Young Investigator Award under the Grant N00014-09-1-1018, Honda-OSU Partnership Program, and OSU Transportation Research Endowment Program. Recommended by Associate Editor F. Basile.
PY - 2012
Y1 - 2012
N2 - This paper presents a fast and global optimization algorithm for an energy-efficient control allocation (CA) scheme, which was proposed for improving the operational energy efficiency of over-actuated systems. For a class of realistic actuator power and efficiency functions, a Karush-Kuhn-Tucker (KKT)-based algorithm was devised to find all the local optimal solutions, and consequently the global minimum through a further simple comparison among all the realistic local minima and boundary values for such a non-convex optimization problem. This KKT-based algorithm is also independent on the selections of initial conditions by transferring the standard nonlinear optimization problem into classical eigenvalue problems. Numerical examples for electric vehicles with in-wheel motors were utilized to validate the effectiveness of the proposed global optimization algorithm. Simulation results, based on the parameters of an electric ground vehicle actuated by in-wheel motors (whose energy efficiencies were experimentally calibrated), showed that the proposed global optimization algorithm was at least 20 times faster than the classical active-set optimization method, while achieving better control allocation results for system energy saving.
AB - This paper presents a fast and global optimization algorithm for an energy-efficient control allocation (CA) scheme, which was proposed for improving the operational energy efficiency of over-actuated systems. For a class of realistic actuator power and efficiency functions, a Karush-Kuhn-Tucker (KKT)-based algorithm was devised to find all the local optimal solutions, and consequently the global minimum through a further simple comparison among all the realistic local minima and boundary values for such a non-convex optimization problem. This KKT-based algorithm is also independent on the selections of initial conditions by transferring the standard nonlinear optimization problem into classical eigenvalue problems. Numerical examples for electric vehicles with in-wheel motors were utilized to validate the effectiveness of the proposed global optimization algorithm. Simulation results, based on the parameters of an electric ground vehicle actuated by in-wheel motors (whose energy efficiencies were experimentally calibrated), showed that the proposed global optimization algorithm was at least 20 times faster than the classical active-set optimization method, while achieving better control allocation results for system energy saving.
KW - Electrical ground vehicles (EGVs)
KW - Karush-Kuhn-Tucker (KKT) conditions
KW - energy-efficient control allocation (EECA)
KW - global optimality
KW - in-wheel motors
KW - over-actuated systems
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U2 - 10.1109/TCST.2011.2161989
DO - 10.1109/TCST.2011.2161989
M3 - Article
AN - SCOPUS:84863520519
SN - 1063-6536
VL - 20
SP - 1202
EP - 1211
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 5
M1 - 5981409
ER -