Luis A. Rodriguez, Ph.D.
Assistant Professor | Milwaukee School of Engineering
Milwaukee, WI, UNITED STATES
Dr. Luis Rodriguez’s areas of expertise include nonlinear control and motion planning of robot manipulators.
Education, Licensure and Certification (3)
Ph.D.: Mechanical Engineering, University of California-Irvine 2010
M.S.: Mechanical Engineering, University of Wisconsin-Madison 2004
B.S.: Mechanical Engineering, University of California-San Diego 2000
Biography
Dr. Luis Rodriguez is an assistant professor in MSOE's Mechanical Engineering Department. He teaches Intro to Engineering Design, Engineering Dynamics, Instrumentation, Mechanics III, Automatic Control Systems, and advises Senior Design. He earned his bachelor's degree in mechanical engineering from the University of California, San Diego, his master's in mechanical engineering from the University of Wisconsin-Madison, and his Ph.D. in mechanical engineering from the University of California-Irvine. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) Control Systems Society, IEEE Robotics and Automation Society, American Society for Engineering Education (ASEE), and the Society for the Advancement of Chicanos and Native American Indians in Science (SACNAS).
Areas of Expertise (5)
Optimal Control
Robot Control
Robotics and Multibody Dynamics
Design of Mechatronics Systems
Motion Planning
Accomplishments (4)
Protracted Leave Award, MSOE
2018
Falk Engineering Educator Award, MSOE
Finalist 2014-15
Bridge to the Doctorate Program Fellow, UCI
2004
National GEM Consortium Program Fellow
2001
Affiliations (3)
- Institute of Electrical and Electronics Engineers (IEEE) Control Systems Society : Member
- IEEE Robotics and Automation Society : Member
- American Society for Engineering Education (ASEE) : Member
Event and Speaking Appearances (2)
Robot Racing from Targeted Kit-based Components to a Functional System
ASEE’s Virtual Conference
2020-06-21
Development of a Motion Control Laboratory Focusing on Control Design and Fluid Power Education
ASEE’s 126th Annual Conference & Exposition Tampa, Florida
2019-06-16
Research Grants (1)
Teaching Grant Award
National Fluid Power Asssociation $3000
2014-15
Selected Publications (6)
Promoting Open-source Software and Hardware Platforms in Mechatronics and Robotics Engineering Education
ASEE’s Virtual ConferenceLotfi, N., Mbanisi, K.C., Auslander, D.M., Berry, C.A., Rodriguez, L.A., and Molki, M.
2020
A New Development of Powered Orthotic for Deficient Push-off Power
SDRP Journal of Biomedical EngineeringRizza, R., Liu, X., Rodriquez, L. A., Luo, R., Yang, Z., Wang, Q.
2017 Background: During the gait cycle, power generated during the push-off stage by individuals with Cerebral Palsy (CP) is deficient. Associated with this power is a deficient moment about the ankle. Current ankle and foot orthotics (AFO) can restrain abnormal joint motion, improve the kinematics, and stabilize gait and posture but cannot provide augmented moment and power during push-off phase. Thus gait of CP patients is not im-proved during push-off by traditional orthotics.
A Riccati Approach for Constrained Linear Quadratic Optimal Control
International Journal of ControlSideris, A., Rodriguez, L. A.
2011 An active-set method is proposed for solving linear quadratic optimal control problems subject to general linear inequality path constraints including mixed state-control and state-only constraints. A Riccati-based approach is developed for efficiently solving the equality constrained optimal control subproblems generated during the procedure. The solution of each subproblem requires computations that scale linearly with the horizon length. The algorithm is illustrated with numerical examples.
A Sequential Linear Quadratic Approach for Constrained Nonlinear Optimal Control
Proceedings of the American Control ConferenceSideris, A., Rodriguez, L. A.
2011 A sequential quadratic programming method is proposed for solving nonlinear optimal control problems subject to general path constraints including mixed state-control and state-only constraints. The proposed algorithm formulates linear quadratic optimal control subproblems with a solution that provides a descent direction for a non-differentiable exact penalty function. A set of conditions is given under which the minimization of the merit function produces a sequence of controls with limit points that satisfy the first order necessary conditions of the optimal control problem. The subproblems solved at each step of the algorithm inherit the structure of the nonlinear optimal control problem and can be solved efficiently via Riccati methods.
A Riccati Approach to Equality Constrained Linear Quadratic Optimal Control
Proceedings of the American Control ConferenceSideris, A., Rodriguez, L.A.
2010 A Riccati based approach is proposed to solve Linear Quadratic Optimal control problems subject to linear equality path constraints including mixed state-control and state-only constraints. The proposed algorithm requires computations that scale linearly with the horizon length. It can be used as the key sub-problem to build effective iterative methodologies that tackle general inequality constrained and nonlinear optimal control problems.
An Active-set Method for Constrained Linear Quadratic Optimal Control
Proceedings of the American Control ConferenceRodriguez, L.A., Sideris, A.
2010 An active-set method is proposed for solving Linear Quadratic Optimal control problems subject to general linear inequality path constraints including mixed state-control and state-only constraints. The proposed algorithm uses a Riccati based approach to efficiently solve the equality constrained optimal control subproblems generated during the procedure and it is illustrated with two numerical examples.
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