Abstract

This article is concerned with the assessment of nonlinearity in nonlinear dynamic systems to determine the feasibility of controlling a nonlinear system with either a single linear controller or a multimodel controller. The nonlinear system is decomposed into a bank of linear models, resulting in exploiting the gap metric and the maximum stability margin value of these linear models to introduce two key attributes. The first attribute, termed “slavery quality,” quantifies the behavior of the linear models by examining the feasibility of stabilizing each linear model using other local controllers. In contrast, the second attribute, referred to as “mastery quality,” assesses the ability of each local controller to stabilize the linear systems. The collaboration of the mastery and the slavery qualities not only facilitates assessing the nonlinearity degree of a nonlinear system but also supports the selection of nominal linear models. Three nonlinear systems with different characteristics are investigated. The simulations validate the effectiveness and benefits of the proposed method in understanding the adequacy of a single linear controller or a multimodel controller for a given nonlinear system.

References

1.
Harris
,
K. R.
,
Colantonio
,
M. C.
, and
Palazoğlu
,
A.
,
2000
, “
On the Computation of a Nonlinearity Measure Using Functional Expansions
,”
Chem. Eng. Sci.
,
55
(
13
), pp.
2393
2400
.10.1016/S0009-2509(99)00514-X
2.
Xavier
,
J.
,
Patnaik
,
S.
, and
Panda
,
R. C.
,
2021
, “
Nonlinear Measure for Nonlinear Dynamic Processes Using Convergence Area: Typical Case Studies
,”
ASME J. Comput. Nonlinear Dyn.
,
16
(
5
), p.
051002
.10.1115/1.4050553
3.
Liu
,
J.
,
Meng
,
Q.
, and
Fang
,
F.
,
2013
, “
Minimum Variance Lower Bound Ratio Based Nonlinearity Measure for Closed Loop Systems
,”
J. Process Control
,
23
(
8
), pp.
1097
1107
.10.1016/j.jprocont.2013.06.012
4.
Nikolaou
,
M.
, and
Misra
,
P.
,
2003
, “
Linear Control of Nonlinear Processes: Recent Developments and Future Directions
,”
Comput. Chem. Eng.
,
27
(
8–9
), pp.
1043
1059
.10.1016/S0098-1354(03)00036-X
5.
Guay
,
M.
,
McLellan
,
P.
, and
Bacon
,
D.
,
1995
, “
Measurement of Nonlinearity in Chemical Process Control Systems: The Steady State Map
,”
Can. J. Chem. Eng.
,
73
(
6
), pp.
868
882
.10.1002/cjce.5450730611
6.
Du
,
J.
,
Song
,
C.
, and
Li
,
P.
,
2009
, “
Multilinear Model Control of Hammerstein-Like Systems Based on an Included Angle Dividing Method and the MLD-MPC Strategy
,”
Ind. Eng. Chem. Res.
,
48
(
8
), pp.
3934
3943
.10.1021/ie8009395
7.
Liu
,
Y.
, and
Li
,
X. R.
,
2015
, “
Measure of Nonlinearity for Estimation
,”
IEEE Trans. Signal Process.
,
63
(
9
), pp.
2377
2388
.10.1109/TSP.2015.2405495
8.
Schweickhardt
,
T.
, and
Allgöwer
,
F.
,
2007
, “
Linear Control of Nonlinear Systems Based on Nonlinearity Measures
,”
J. Process Control
,
17
(
3
), pp.
273
284
.10.1016/j.jprocont.2006.10.012
9.
Schweickhardt
,
T.
, and
Allgower
,
F.
,
2009
, “
On System Gains, Nonlinearity Measures, and Linear Models for Nonlinear Systems
,”
IEEE Trans. Autom. Control
,
54
(
1
), pp.
62
78
.10.1109/TAC.2008.2009569
10.
Stack
,
A. J.
, and
Doyle
,
F. J.
, III
,
1997
, “
The Optimal Control Structure: An Approach to Measuring Control-Law Nonlinearity
,”
Comput. Chem. Eng.
,
21
(
9
), pp.
1009
1019
.10.1016/S0098-1354(96)00339-0
11.
Tan
,
G. T.
,
Huzmezan
,
M.
, and
Kwok
,
K. E.
,
2003
, “
Vinnicombe Metric as a Closed-Loop Nonlinearity Measure
,”
European Control Conference (ECC)
, Cambridge, UK, Sept. 1–4, pp.
751
756
.10.23919/ECC.2003.7085047
12.
Du
,
J.
, and
Johansen
,
T. A.
,
2017
, “
Control-Relevant Nonlinearity Measure and Integrated Multi-Model Control
,”
J. Process Control
,
57
, pp.
127
139
.10.1016/j.jprocont.2017.07.001
13.
Hosseini
,
S.
,
Fatehi
,
A.
,
Johansen
,
T. A.
, and
Sedigh
,
A. K.
,
2012
, “
Multiple Model Bank Selection Based on Nonlinearity Measure and H-Gap Metric
,”
J. Process Control
,
22
(
9
), pp.
1732
1742
.10.1016/j.jprocont.2012.07.006
14.
Helbig
,
A.
,
Marquardt
,
W.
, and
Allgöwer
,
F.
,
2000
, “
Nonlinearity Measures: Definition, Computation and Applications
,”
J. Process Control
,
10
(
2–3
), pp.
113
123
.10.1016/S0959-1524(99)00033-5
15.
Elkhalil
,
K.
, and
Zribi
,
A.
,
2023
, “
Linear Controller Design Approach for Nonlinear Systems by Integrating Gap Metric and Stability Margin
,”
Proc. Inst. Mech. Eng., Part I J. Syst. Control Eng.
,
237
(
10
), pp.
1800
1811
.10.1177/09596518231173756
16.
Du
,
J.
, and
Johansen
,
T. A.
,
2014
, “
Integrated Multimodel Control of Nonlinear Systems Based on Gap Metric and Stability Margin
,”
Ind. Eng. Chem. Res.
,
53
(
24
), pp.
10206
10215
.10.1021/ie500035p
17.
Du
,
J.
,
Song
,
C.
,
Yao
,
Y.
, and
Li
,
P.
,
2013
, “
Multilinear Model Decomposition of MIMO Nonlinear Systems and Its Implication for Multilinear Model-Based Control
,”
J. Process Control
,
23
(
3
), pp.
271
281
.10.1016/j.jprocont.2012.12.007
18.
Du
,
J.
, and
Johansen
,
T. A.
,
2015
, “
Integrated Multilinear Model Predictive Control of Nonlinear Systems Based on Gap Metric
,”
Ind. Eng. Chem. Res.
,
54
(
22
), pp.
6002
6011
.10.1021/ie504170d
19.
Ahmadi
,
M.
, and
Haeri
,
M.
,
2017
, “
A New Structured Multimodel Control of Nonlinear Systems by Integrating Stability Margin and Performance
,”
ASME J. Dyn. Syst. Meas. Control
,
139
(
9
), p.
091014
.10.1115/1.4036069
20.
Ahmadi
,
M.
, and
Haeri
,
M.
,
2021
, “
A Systematic Decomposition Approach of Nonlinear Systems by Combining Gap Metric and Stability Margin
,”
Trans. Inst. Meas. Control
,
43
(
9
), pp.
2006
2017
.10.1177/0142331221989009
21.
Ahmadi
,
M.
, and
Haeri
,
M.
,
2021
, “
An Integrated Best–Worst Decomposition Approach of Nonlinear Systems Using Gap Metric and Stability Margin
,”
Proc. Inst. Mech. Eng., Part I J. Syst. Control Eng.
,
235
(
4
), pp.
486
502
.10.1177/0959651820949654
22.
Zribi
,
A.
,
Chtourou
,
M.
, and
Djemel
,
M.
,
2019
, “
Models' Bank Selection of Nonlinear Systems by Integrating Gap Metric, Margin Stability, and MOPSO Algorithm
,”
Iran. J. Sci. Technol., Trans. Electr. Eng.
,
43
(
4
), pp.
857
869
.10.1007/s40998-019-00210-w
23.
Rikhtehgar
,
P.
, and
Haeri
,
M.
,
2024
, “
Closed-Loop Stability Analysis of a Linear Matrix Inequalities Based Reduced Multiple-Model Control Algorithm
,”
Int. J. Dyn. Control
,
12
(
7
), pp.
2341
2350
.10.1007/s40435-023-01354-8
24.
Tao
,
X.
,
Li
,
D.
,
Wang
,
Y.
,
Li
,
N.
, and
Li
,
S.
,
2015
, “
Gap-Metric-Based Multiple-Model Predictive Control With a Polyhedral Stability Region
,”
Ind. Eng. Chem. Res.
,
54
(
45
), pp.
11319
11329
.10.1021/ie5042758
25.
El-Sakkary
,
A.
,
1985
, “
The Gap Metric: Robustness of Stabilization of Feedback Systems
,”
IEEE Trans. Autom. Control
,
30
(
3
), pp.
240
247
.10.1109/TAC.1985.1103926
26.
Du
,
J.
, and
Johansen
,
T. A.
,
2014
, “
A Gap Metric Based Weighting Method for Multimodel Predictive Control of MIMO Nonlinear Systems
,”
J. Process Control
,
24
(
9
), pp.
1346
1357
.10.1016/j.jprocont.2014.06.002
27.
Ahmadi
,
M.
,
Rikhtehgar
,
P.
, and
Haeri
,
M.
,
2020
, “
A Multi-Model Control of Nonlinear Systems: A Cascade Decoupled Design Procedure Based on Stability and Performance
,”
Trans. Inst. Meas. Control
,
42
(
7
), pp.
1271
1280
.10.1177/0142331219888368
28.
Tan
,
W.
,
Marquez
,
H. J.
,
Chen
,
T.
, and
Liu
,
J.
,
2004
, “
Multimodel Analysis and Controller Design for Nonlinear Processes
,”
Comput. Chem. Eng.
,
28
(
12
), pp.
2667
2675
.10.1016/j.compchemeng.2004.08.005
29.
Al-Araji
,
A. S.
,
2016
, “
Cognitive Non-Linear Controller Design for Magnetic Levitation System
,”
Trans. Inst. Meas. Control
,
38
(
2
), pp.
215
222
.10.1177/0142331215581639
30.
Ahmadi
,
M.
, and
Haeri
,
M.
,
2018
, “
Multimodel Control of Nonlinear Systems: An Improved Gap Metric and Stability Margin-Based Method
,”
ASME J. Dyn. Syst., Meas. Control
,
140
(
8
), p.
081013
.10.1115/1.4039086
You do not currently have access to this content.