Page 69 - ASME DSCC 2015 Program

Technical Program

An lMI-Based Hedging Approach to Model Reference Adaptive Control ConTRIBuTED SESSIon
with Actuator Dynamics 1-26-1 fA4 Powertrain Systems
Contributed regular paper. DSCC2015-9894 Geroge Bellows f 10:00am–12:00pm
Benjamin Gruenwald, Daniel Wagner, Tansel Yucelen, Missouri University
of Science and Technology, Rolla, MO, United States, Jonathan A. Muse, Session Chair: Giorgio Rizzoni, Ohio State University
Air Force Research Lab, Wright-Patterson AFB, OH, United States Session Co-Chair: Qadeer Ahmed, Ohio State University
Although model reference adaptive control has been used in numerous
Hybrid System Based Analytical Approach for optimal Gear Shifting
applications to achieve system performance without excessive reliance on
Schedule Design
dynamical system models, the presence of actuator dynamics can seriously
Contributed regular paper. DSCC2015-9943
limit the stability and the achievable performance of adaptive controllers.
In this paper, an linear matrix inequalities-based hedging approach is Chaozhe He, Wubing Qin, necmiye ozay, Gabor orosz, University of
Michigan, Ann Arbor, MI, United States
developed and evaluated for model reference adaptive control of uncertain
dynamical systems in the presence of actuator dynamics. The hedging In this paper, we present a systematic design for gear shifting using a hybrid
method modifies the ideal reference model dynamics in order to allow cor- system approach. The longitudinal motion of the vehicle is regulated by
rect adaptation that does not get affected due to the presence of actuator a PI-controller that determines the required axle torque. The gear sched-
dynamics. Specifically, we first generalize the hedging approach to cover uling problem is modeled as a hybrid system and an optimization-based
cases in which actuator output and is known and unknown. We next show gear shifting strategy is introduced, which guarantees that the propulsion
the stability of the closed-loop dynamical system using tools from Lyapunov requirements are delivered while minimizing fuel consumption. The resulting
stability and linear matrix inequalities. Finally, an illustrative numerical exam- dynamics is proved to be stable theoretically. In a case study, we compare
ple is provided to demonstrate the efficacy of the proposed linear matrix- our strategy with a standard approach used in the industry and demonstrate
inequalities-based hedging approach to model reference adaptive control. the advantages of our design for class 8 trucks.
Event Triggered Adaptive Control optimal Slip control of a Torque converter clutch
Contributed regular paper. DSCC2015-9724 Contributed regular paper. DSCC2015-9840
Ali Albattat, Benjamin Gruenwald, Tansel Yucelen, Missouri University of Yaoying Wang, Zongxuan Sun, University of Minnesota, Minneapolis, MN,
Science and Technology, Rolla, MO, United States United States
In this paper, we present a new adaptive control methodology that allows a Slip control of a torque converter clutch (TCC) has been developed for years
desirable command performance while the proposed controller exchanges but most approaches are focused on time-based methods without offering
data with the physical system through a real-time network. Specifcally, a systematic approach for dealing with the time-varying signals associated
we utilize tools and methods from event-triggering control theory to with the engine torque pulsation. As one of the major vibration sources of a
schedule data exchange dependent upon errors exceeding user-defned vehicle, engine torque is periodic in the crankshaft rotational angle but
thresholds and show the boundedness of the overall closed-loop system aperiodic in time as the engine speed changes in real-time. This paper
using Lyapunov stability. An illustrative numerical example is provided to first presents a powertrain vibration analysis based on the transient engine
demonstrate the efficacy of the proposed adaptive control approach. torque input and the conventional TCC slip control. Simulation results show
Model Structure Adaptation: A Gradient-Based Approach that the conventional time-based TCC slip control does not settle the
periodic nature of the engine torque vibration with respect to crankshaft
Contributed regular paper. DSCC2015-9658
angle. However, a time-varying angle-based control method can solve this
William G. la Cava, Kourosh Danai, University Massachusetts, Amherst, issue. The paper then proposes an optimal TCC torque trajectory by using
MA, United States
dynamic programming for this time-varying angle-based control method.
A gradient-based method of symbolic adaptation is introduced for a class Simulation results demonstrate the energy saving potential of the optimal
of continuous dynamic models. The proposed Model Structure Adaptation trajectory over the conventional method.
Method (MSAM) starts with the first-principles model of the system and
adapts its structure after adjusting its individual components in symbol-
ic form. A key contribution of this work is its introduction of the model’s
parameter sensitivity as the measure of symbolic changes to the model.
This measure, which is essential to defining the structural sensitivity of the
model, not only accommodates algebraic evaluation of candidate models in
lieu of less reliable simulation-based evaluation but also makes possible the
implementation of gradient-based optimization in symbolic adaptation. The
applicability of the proposed method is evaluated in application to several
models which demonstrate its potential utility.

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