Conference Program of WCICA 2012

WCICA 2012
Book of Abstracts: Saturday Sessions
Zhang, Botao
Liu, Shirong
Hangzhou Dianzi Univ.
Hangzhou Dianzi Univ.
Chen, Zhiyong
Huang, Jie
The Univ. of Newcastle
Chinese Univ. of Hong Kong, China
In this paper, a path planning approach for finding an optimal path is
proposed to reduce the expected-time in target search by robot. This
approach employs a heuristic algorithm to generate a basic path and
minimize the expectedtime. Considering different direction may lead to
different expected-time in a same loop, a direction choosing method is
presented to improve the performance of this heuristic algorithm. Then,
based on the improved algorithm, a two-level path planning approach is
investigated. At the top level, the improved heuristic algorithm is used to
generate a sequence of observation points. At the lower level, the Artificial
Potential Field (APF) is employed to plan paths among observation
points. Simulations and experiments demonstrated that this approach
can reduce the expected time for target search.
◮ SaB09-3 16:30–16:50
Optimal Operation Strategies for Batch Distillation by Using A Fast
Adaptive Simulated Annealing Algorithm, pp.2426–2430
Wang, Lin
Pu, Zhonghao
Wen, Sufang
Inner Mongolia Univ. of Tech.
Inner Mongolia Univ. of Tech.
Inner Mongolia Univ. of Tech.
Batch distillation processes are widely used in the chemical industry.
In this work, the optimal operation strategies for such processes are
studied by using a fast adaptive simulated annealing (FASA) algorithm.
Simulated annealing algorithm is stochastic in nature, and it converges
towards a global optimum. However, its computational load is usually
much too heavy. In this study, a FASA algorithm was presented with
fast and adaptive moves in the searched neighborhood range to decrease
the computation load. According to the characteristics of batch
distillation process, a FASA-based parallelized optimization computation
approach was proposed and then it was applied to a model of a
batch distillation plant. The optimal operation strategies with respect to
minimal production time and maximal profit were studied. The results
show the effectiveness of the method.
◮ SaB09-4 16:50–17:10
PID Control of Glucose Concentration in Subjects with Type 1 Diabetes
based on a Simplified Model: An In Silico Trial, pp.5051–5055
Li, Peng
Yu, Lei
Guo, Liquan
Dong, Jixiang
Hu, Ji
Fang, Qiang
SIBET
Suzhou Inst. of Biomedical Engineering &
Tech.,CAS
SIBET
The Second Affliated Hospital Suzhou Univ.
The Second Affliated Hospital Suzhou Univ.
SIBET
An artificial pancreas system (APS) mimics the function of a real pancreas
through monitoring a diabetic’s blood glucose and administering
the right dose of insulin via an automatic control loop. It is hailed as a
promising cure of diabetes, though this technology is still years away
from commercial use due to a few technological bottlenecks. The simulation
model of insulin-glucose metabolism of type 1 diabetes mellitus
(T1DM) is an essential part of APS. In order to simplify the parameter
identification task so that the model can be implemented electronically
with ease, this paper presents a simplified model based on Routh
approximation model reduction method. The results show that the approximation
error between the simplified model and the original model
is so small that can be neglected. Based on the simplified model, a
PID controller is designed to maintain normoglycemia (90mg/dl) in subjects
with T1DM. The in silico simulation results show that the glucose
concentration is controlled well, the risk of hyperglycemia and hypoglycemia
is reduced a lot. This suggests that the simplified model describes
the insulin-glucose metabolism process accurately, and the PID
control algorithm is well-suitable to guide the further development of an
APS.
◮ SaB09-5 17:10–17:30
Parameter Convergence Analysis in Adaptive Disturbance Rejection
Problem of Rigid Spacecraft, pp.1418–1423
The asymptotic rejection of rigid spacecraft systems under multi-tone s-
inusoidal disturbances with unknown frequencies was studied recently.
It was shown that the problem can be solved via an adaptive control approach.
However, the convergence issue of the estimated frequencies
to the unknown frequencies has not been investigated. In this paper,
we further give some sufficient conditions for guaranteeing the convergence
of the estimated frequencies to the unknown frequencies.
◮ SaB09-6 17:30–17:50
H2 Performance Limitation of a Class of Nonlinear Non-minimum
Phase Systems, pp.1317–1322
Lu, Di
Fan, Guoliang
Yi, Jian-qiang
Inst. of Automation, Chinese Acad. of Sci.
Inst. of Automation, Chinese Acad. of Sci.
Inst. of automation, chinese Acad. of Sci.
In this paper, we study H2 performance limitation of the nonlinear nonminimum
phase systems with a ’new’structure that the linear combination
of all the states of the systems serves as the input of the dynamics
where the unstable zero-dynamics is. It is shown that the best
attainable tracking performance of the above system is equal as the
minimum energy of stabilizing the ’extended’dynamics which is relevant
to all the system’s states except for the state whose differential
equation contains the system’s control input explicitly. In the end, we
use two examples to illustrate our theorem. The first one is a simple
comparison between two systems with different structures and the second
one is a more practical object - the aircraft’s longitudinal motion.
For the latter one, we derive the H2 performance limitation of the nonlinear
aircraft’s longitudinal motion.
SaB10 15:50–17:50 Room 311B
Invited Session: Modeling and Control: Challenges from Automotive
Industry
Chair: Shen, Tielong
Co-Chair: OHATA, AKIRA
Sophia Univ.
Toyota Motor Corporation
◮ SaB10-1 15:50–16:20
Benchmark Problem for Nonlinear Identification of Automotive Engine,
pp.3305–3310
OHATA, AKIRA
Toyota Motor Corporation
As automotive engines have been becoming complex due to the pressures
from CO2 emission reduction, safety and drivability, the automotive
industry has encountered the issue that experiments are exponentially
increasing. Model-based calibration was introduced to the steady
state calibration area and the automotive industry succeeded to reduce
the experiments by half in the case of typical gasoline engine. According
to the success, the automotive industry intends to expand the technology
to the transient calibration area that is highly connected with
nonlinear identification. In this benchmark problem, the challengers
are asked to develop identification methods including design of experiments.
Their results will be evaluated by the accuracies and the data
sizes used in the identification.
◮ SaB10-2 16:20–16:50
JSAE-SICE Benchmark problem II: Fuel Consumption Optimization of
Commuter Vehicle Using Hybrid Powertrain, pp.606–611
Yasui, Yuji
Honda R&D CO., Ltd
The Technical Committee on Vehicle Control and Modeling was established
by JSAE (Society of Automotive Engineers of Japan) and SICE
(The Society of Instrument and Control Engineers) in order to promote
collaboration between automotive industry and academics. The committee
provides “Benchmark problem 2: Fuel Consumption Optimization
of Commuter Vehicle”for academics. This is a research to design
energy management control to minimize fuel consumption of a hybrid
electric vehicle. The vehicle is used under commuting condition with
traffic jam. This paper describes a simulation environment, a vehicle
model and driving condition of the benchmark problem. Furthermore,
the energy management control using onboard optimization algorithm
is introduced as a sample of research of benchmark problem in this
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