6. 標題範例
●Decoupled-Level Optimal Output States
Feedback Controller Design
● A Chart for Estimating the Distance
Attenuation of Flanking Sound though
Open Windows
● Simulation Model for Pedestrian Movement
in Way-Finding and Queuing for
Architectural Design Theory
9. 不良範例
A Chart for Estimating the
Distance Attenuation of
Flanking Sound Passing though
Open Windows in the Exterior
Wall of Adjoining Rooms and Its
Experimental Verification
(25 個字 )
10. 改良後範例
A Chart for Estimating the
Distance Attenuation of Flanking
Sound though Open Windows
(13 個字 )
( 估測通過通風窗口之左右兩邊聲
音的距離衰減圖表 )
11. 不良範例
Assessment of Two Laser
Doppler Velocity Measuring
System by Measuring Acoustic
Particle Velocities in Enclosed
Sound Field
( 標題太長 ,17 個字 , 但為表達
論文內容似乎均無法減少 ) ---
26. 封 面 樣 版 ( 投稿論文
)
Decoupled- Level Optimal Output States Feedback Controller Design
T.L. Huang T.Y. Hwang
Department of Computer Science National Taipei University of Education
Email: tsongliang@tea.ntue.edu.tw
ABSTRACT: This paper addresses the design of decoupled-level large system controllers using an optimal
reduced order model whose state variables are all output states. The reduced-order model retains their
physical meaning and is used to design a decoupled-level linear feedback controller that takes into account
the realities and constraints of the large systems. The decoupled-level control strategy is used and a global
control signal is generated from the output variables to minimize the effect of interactions. Effectiveness of
this controller is evaluated and example is given to illustrate the advantages of the proposed method.
Responses of the system with decoupled-level scheme and optimal reduced order scheme are included for
comparative analyses.
1. Introduction
The design of large system , can be formulated as an optimal linear regulator control problem whose
solution is a complete state control scheme [1]. Thus, the implementation requires the design of state
estimators [2]. These increase the hardware cost and reduce the reliability of the control system. These are
the reasons that a control scheme uses only some desired state variables such as output states. Upon this, a
scheme referred to as suboptimal control is obtained but only some state variables are used in the
implemented control scheme while the others are omitted for convenience [3].
29. Deutero-Eigenstructure Assignment
Output Feedback Stabilizer Design
T.Y. HWANG1 C.W. Liu2
Depertment of computer science National Taipei University of
1
Education
134, Sec. 2, Hoping E. Road, Taipei City, 106 Taiwan, R.O.C.
thwang@faculty.pccu.edu.tw
2
Department of Electrical Engineering Tamkang University
151, Ying-Chuan Road, Taipei County 251 Taiwan, R.O.C.
old_liu.tw@yahoo.com.tw
31. 摘要 (Abstract) 的寫法
● 摘要的長度最好不要超過 300 個字，摘要的意
義是即使不閱讀文章整體也能夠掌握理解全文
的內容。
關鍵字 :
目的 : The purpose of this paper is -----
方法 : using ----- 或 --- are employed to ----
結果 : As a result, ---- 或 Consequently, -----
結論 : In conclusion --- 或 We conclude that--
建議事項 : It is recommended that ---- 或
It is suggested that ----
33. 摘 要 樣 板 ( 英文 )
ABSTRACT: The purpose of this paper is to address the design of
decoupled-level large system controllers using an optimal reduced order
model whose state variables are all output states. The reduced-order model
retains their physical meaning and is used to design a decoupled-level linear
feedback controller that takes into account the realities and constraints of
the large systems. The decoupled-level control strategy is used and a global
control signal is generated from the output variables to minimize the effect
of interactions. As a result ,the effectiveness of this controller is evaluated
and considerable savings in computer memory are achieved. In conclusion,
the controllers determined at the subsystem level depend only on local
information operating to the particular machine. Example is given to
illustrate the advantages of the proposed method. Responses of the system
with decoupled-level scheme and optimal reduced order scheme are
included for comparative analyses. It is recommended that the proposed
method can be applied to supper large system
36. (1) 研究主題
(Research theme)
關鍵字 :
The work presented
here is to -------
37. 範例
1. Introduction
The work presented here is
to address the design of
decoupled-level large system
controllers using an optimal
reduced order model whose state
variables are all output states.
38. (2) 研究主題的必要性、
重要性
(Need/Importance of research theme)
敘述是什麼理由選擇此
研究主題、以及關於此研
究主題到目前為止 , 已進
行過的研究歷史等等。
39. 關鍵語
Recent interest in -----
In recent years -----
-----is well known -----
----- have gained considerable
attention in -----
----- has been recognized as
-----
40. 範例
1. Introduction
The work presented here is to address the
design of decoupled-level large system
controllers using an optimal reduced order
model whose state variables are all output
states. Recent interest in designing the
stabilizer of large system , can be formulated as
an optimal linear regulator control problem
whose solution is a complete state control
scheme [1].
42. 關鍵語
It is well known that -----
----- some papers [3 and 4] have
discussed -----
Recent studies have suggested ----
Various methods ----have been examined
by other researchers [6,7,8,9,and 10].
A number of strategies have been
developed in recent years to ------
43. 範例
1. Introduction
The work presented here is to address the design of
decoupled-level large system controllers using an optimal
reduced order model whose state variables are all output
states. Recent interest in designing the stabilizer of large
system , can be formulated as an optimal linear regulator
control problem whose solution is a complete state control
scheme [1]. Thus, the implementation requires the design of
state estimators [2]. These increase the hardware cost and
reduce the reliability of the control system. These are the
reasons that a control scheme uses only some desired state
variables such as output states. It is well known that a
scheme referred to as suboptimal control is obtained but only
some state variables are used in the implemented control
scheme while the others are omitted for convenience [3].
44. (4) 歷年來研究未解決之
點 (Unresolved points in conventional
research)
關鍵語
● However, ----
● Unlike the studies made extensively
on ----,very little attention was given
to ----
45. ● To the best of the authors’
knowledge, no research has yet
been carried out to ----
● In contract, there is little data
available concerning ----
46. 範例
It is well known that a scheme referred to as
suboptimal control is obtained but only some state
variables are used in the implemented control
scheme while the others are omitted for
convenience [3]. Obviously, this approach is
arbitrary and cannot be accepted on faith.
Performance degradation is not evaluated for
general system sunder different conditions. The
recent approach using optimal reduced order model
is obtained [4] [5].However, the optimal control
strategy is also used for the reduced order model of
the large system, the computation of an optimal
controller becomes extremely difficult and time
consuming as the order of the system increases.
48. 關鍵語
● The purpose (goal) of the study is
to ----
● In this study, ----have been
evaluated in comparison with ----
● This paper presents (discusses,
suggests, deals with) ----
49. 範例
However, the optimal control strategy is also
used for the reduced order model of the large
system, the computation of an optimal
controller becomes extremely difficult and time
consuming as the order of the system
increases. This paper presents the method
that the overall system is decomposed
into separate subsystems, each
subsystem comprising one machine.
51. 關鍵語
● by employing methods
such as ----
● by using ----
● by incorporating ---
52. 範例
This paper presents the method that the
overall system is decomposed into
separate subsystems, each subsystem
comprising one machine. By using the
optimal reduced order model method at
the subsystem level, an optimal
feedback controller is derived by output
feedback of each machine.
54. 關鍵語
● As a result, ----- the proposed
method is much better than
before .
● As a result, ----- shows good
agreement with -----
● It is found that -----
55. 範例
By using the optimal reduced order model
method at the subsystem level, an optimal
feedback controller is derived by output
feedback of each machine. The order of this
model is obviously lower than that of the
overall system and the method proposed in ref
[6]. Thus, considerable savings in computer
memory are achieved. It is found that the
controllers thus determined at the subsystem level
depend only on local information operating to the
particular machine.
57. 關鍵語
● From our results, we conclude
that ----
● We, thus, conclude that ----
● The results indicate that ----
● Experimental results indicate
that ----
58. ● In Conclusion, ----
● In summary, these investigations
suggest that ----
● It is concluded from the simulation
that ----
59. 範例
In conclusion, the attractive features of the
two-level optimal output feedback stabilizers
design are as follows:
(1) The output state variables are some
desired or available variables, thus, the state
variables of the reduced order model retain
their physical meaning.
61. ● In the following, ---- is explained
in Chapter 4; ---- is explained in
Chapter 5; ----
● In Section 1 we recall ----.
In Section 2 and 3 we derive ----.
Section 4 and 5 deal with ----.
In Section 6 and 7 ---- are discussed.
Finally, we comment on ---
62. 範例
As a matter of fact this paper is an extension of
optimal reduced order method proposed by Ali
Feliachi et. a1 [4][5] and the two-level optimal
stabilization method proposed by Y.L. Abdel-Magid
and Gama1 M. Aly [6]. In Section 1 we recall the
background of optimal reduced order model. In
Section 2 and 3 we derive the control strategy
and control structure. Section 4 and 5 deal
with system study . In Section 6 and 7
simulation and computation results are
discussed. Finally, we comment on overall
control structure and effectiveness of the
controller.
63. 前 言 樣 板 ( 英文 )
1. Introduction
The work presented here is to address the design of
decoupled-level large system controllers using an optimal
reduced order model whose state variables are all output
states. Recent interest in designing the stabilizer of large
system , can be formulated as an optimal linear regulator
control problem whose solution is a complete state control
scheme [1]. Thus, the implementation requires the design of
state estimators [2]. These increase the hardware cost and
reduce the reliability of the control system. These are the
reasons that a control scheme uses only some desired state
variables such as output states. It is well known that a scheme
referred to as suboptimal control is obtained but only some
state variables are used in the implemented control scheme
while the others are omitted for convenience [3].
64. Obviously, this approach is arbitrary and
cannot be accepted on faith. Performance
degradation is not evaluated for general system
sunder different conditions. The recent
approach using optimal reduced order model is
obtained [4] [5].However, the optimal control
strategy is also used for the reduced order
model of the large system, the computation of
an optimal controller becomes extremely
difficult and time consuming as the order of the
system increases.
65. For an nth-order system it is necessary
to solve an n(n+1)/2 Riccati equations in
order to calculate the controller gain. And
the problem formulation itself is not straight
forward as it is complex to determine the
design parameters in the performance
criterion as the order of the system
increases. To overcome these difficulties,
the former paper concerned with the
development of multi-level optimal
stabilization of interconnected power
system in ref. [6] is applied to the proposed
approach.
66. This paper presents the method that
the overall system is decomposed into
separate subsystems, each subsystem
comprising one machine. By using the
optimal reduced order model method at
the subsystem level, an optimal feedback
controller is derived by output feedback of
each machine. The order of this model is
obviously lower than that of the overall
system and the method proposed in ref
[6]. Thus, considerable savings in
computer memory are achieved.
67. It is found that the controllers thus determined at
the subsystem level depend only on local information
operating to the particular machine. And, since only
the output feedback is used via optimal reduced order
model, the control strategy can be implemented
easily. In order to take into account the interaction
between the different subsystems, a global controller
is designed at a higher level [7]. At this level, all
subsystems will transfer the necessary information to
achieve the global objectives. In this paper, the global
gain is obtained from the optimal reduced order model
of the whole system by using only output feedback.
68. The evaluation of the global gain is much
easier than the overall system optimal state
feedback gains because the optimal reduced
order model is used. The control strategy
proposed here is applied to a, two-machine
system. The effectiveness of the two-level
optimal output feedback controller are
presented. A comparison between the
performance of the proposed controller and
that of the optimal reduced order method
and the two-level control strategy is also
included.
69. In conclusion, the attractive features of
the two-level optimal output feedback
stabilizers design are as follows:
(1) The output state variables are some
desired or available variables, thus, the
state variables of the reduced order model
retain their physical meaning.
(2) Local controllers determined depend
only on local output information pertaining
to the subsystem and a considerable
70. savings in computation effort at the (machine)
subsystem level is achieved and no estimator
is needed.
(3) Interaction between the different
subsystem is minimized by the use of the
global controller gain at a higher level using
the output state variables of the overall system
via optimal reduced order model. The
evaluation process is much easier than the
optimal control strategy and the transient
response is much better also.
71. As a matter of fact this paper is an extension of
optimal reduced order method proposed by Ali
Feliachi et. a1 [4][5] and the two-level optimal
stabilization method proposed by Y.L. Abdel-
Magid and Gama1 M. Aly [6]. In Section 1 we
recall the background of optimal reduced
order model. In Section 2 and 3 we derive
the control strategy and control structure.
Section 4 and 5 deal with system study .
In Section 6 and 7 simulation and
computation results are discussed. Finally,
we comment on overall control structure
and effectiveness of the controller.
