Page 43 - ASME DSCC 2015 Program

Technical Program

sus. We validate the main results using Monte Carlo simulations and study Robust Gain-Scheduling output feedback Control With noisy
the consensus conditions for Erdos-Renyi networks. We find that, for certain Scheduling Parameters
selections of system parameters, the presence of antagonistic interactions Contributed regular paper. DSCC2015-9710
permits consensus in systems that would not reach accordance otherwise. Ali Khudhair Al-jiboory, Guoming Zhu, Michigan State University, East
Average Bridge Consensus: Dealing With Active-Passive Sensors Lansing, MI, United States
Contributed short paper. DSCC2015-9656 Robust Gain-Scheduling (RGS) H2 control strategy has been considered in
David W. Casbeer, Air Force Research Lab Aerospace Systems Directorate, this paper. In contrast to the conventional gain-scheduling synthesis meth-
Wright-Patterson AFB, OH, United States, Eloy Garcia, Infoscitex Corp., ods, the scheduling parameters are assumed to be inexactly measured. This
Dayton, oH, united States, Yongcan Cao, Air Force Research Lab, Dayton, is a practical assumption since measurement noise is inevitable even with
OH, United States, Dejan Milutinovic, UC Santa Cruz, Santa Cruz, CA, very accurate sensors. Multi-simplex modeling approach was used to model
United States the scheduling parameters and their uncertainties in a convex domain. Suf-
In network average consensus problems, a failure, in which a node cannot ficient conditions in terms of Parametrized Linear Matrix Inequalities (PLMIs)
provide the initial value, but can communicate with its neighbors gives rise for synthesizing dynamic output-feedback controllers are derived. The
to the bridge consensus problem. In its formulation, the failed node serves resulting controller not only guarantees robust stability and H2 performance
as a bridge which maintains the network communication connectivity, and but also ensures robustness against scheduling parameters uncertainties.
its failure to provide the value does not impact the capability of the rest of The effectiveness of the proposed approach is demonstrated through nu-
the network nodes to reach a consensus. The proposed bridge consensus merical example with simulation and comparisons with existing approaches
solution can deal with multiple failing nodes and large networks in a scalable from literature. The comparison results confirm that the developed approach
manner. The solution properties are proven and illustrated by a numerical outperforms the existing ones considerably.
example. Application of Integrated Control Structure Design using BMI Theory
and Robust feedback linearization to Excavator Bucket level Control
ConTRIBuTED SESSIon
1-3-1 TA3 Advances in Control Design Methods Contributed regular paper. DSCC2015-9797
George Bellows E 10:00am–12:00pm Daniel Kassen, Atul Kelkar, Iowa State University, Ames, IA, United States,
Hui Zhou, Muyang Corporation Ltd., Yangzhou, Jiangsu, China,
Session Chair: Quize Zhou, XYZ Punit Tulpule, The Ohio State University, Columbus, OH, United States
Session Co-Chair: William Singhose, Georgia Tech Integrated design of controlled mechanical systems - wherein structure
and controls are designed concurrently as opposed to sequentially - has
Continuous-time feedback Control with finite-time Boundedness and proven to yield a better optimal design. Early work in this area from the
h_infinity performance criteria
co-authors has led to the development of a novel design tool: Integrated
Contributed regular paper. DSCC2015-9709
Robust Optimal
jacob hostettler, xin Wang, Southern Illinois University Edwardsville, Design (IROD). IROD offers an integrated design framework that can be
Edwardsville, IL, United States applied to a variety of robust optimal design problems. This paper presents
For advanced control applications, research into the use of linear matrix the addition of feedback linearization control strategy to the robust design
inequalities has yielded a notable amount of work in the area of nonlinear framework and demonstrates its application to an excavator bucket leveling
systems. Linear Matrix Inequalities can be formed through the application of control system design problem. The excavator dynamic model is highly non-
desired performance criteria to a general system. By proper selection of a linear and it includes both the multibody linkage dynamics and the hydraulic
Lyapunov energy function, sufficient conditions to satisfy the performance actuator dynamics. The hydraulic system consists of a pump, four way spool
objectives can be realized. The performance criteria, typically chosen for valve, and pistons. The performance, robustness, and required control ener-
the application, define the objectives associated with the control. This work gy of the IROD design are compared with traditional sequential design using
presents a control method for discrete-time systems with finite-time bound- a full SimScape model. The results clearly demonstrate the effectiveness of
edness and H_infinity performance criteria. The design of the controller IROD over traditional design methodologies.
corresponds to a system existing with bounded model uncertainties, and in
the presence of L_2 type external disturbances. Through the use of a linear
state feedback control, sufficient conditions which guarantee the finite-time
stability and H_infinity performance objectives are achieved via the solution
of a Linear Matrix Inequality. MATLAB application and simulation is carried
out using the field oriented control of a permanent magnet synchronous
generator in order to effectively demonstrate the effectiveness of this con-
trol strategy in the wind energy conversion system application.

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