Research Papers

A New Structured Multimodel Control of Nonlinear Systems by Integrating Stability Margin and Performance

[+] Author and Article Information
Mahdi Ahmadi

Advanced Control Systems Lab,
Electrical Engineering,
Sharif University of Technology,
Tehran 11155-4363, Iran
e-mail: mahdiahmadi@ee.sharif.edu

Mohammad Haeri

Advanced Control Systems Lab,
Electrical Engineering,
Sharif University of Technology,
Tehran 11155-4363, Iran
e-mail: haeri@sharif.ir

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 26, 2016; final manuscript received February 7, 2017; published online June 5, 2017. Assoc. Editor: Dumitru I. Caruntu.

J. Dyn. Sys., Meas., Control 139(9), 091014 (Jun 05, 2017) (10 pages) Paper No: DS-16-1416; doi: 10.1115/1.4036069 History: Received August 26, 2016; Revised February 07, 2017

This paper deals with a new systematic multimodel controller design for nonlinear systems. The design of local controllers based on performance requirements is incorporated with the concept of local models selection as an optimization problem. Gap metric and stability margin are used as measuring tool and operation space dividing criterion, respectively. The developed method provides support to design a simple structured multiple proportional-integral (PI) controller which guarantees both robust stability and time-domain performance specifications. The main advantages of the proposed method are avoiding model redundancy, not needing a priori knowledge about system, having simple structure, and easing the implementation. To evaluate the presented multimodel controller design procedure, three benchmark nonlinear systems are studied. Both simulations and experimental results prove the effectiveness of the proposed method in set point tracking and disturbance rejection.

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Grahic Jump Location
Fig. 1

The standard feedback system

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Fig. 2

(a) The steady-state curve and (b) the gaps between the local models

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Fig. 3

Set point tracking test of the pH system in Eq. (23)

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Fig. 4

Disturbance rejection in the closed-loop pH system

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Fig. 5

(a) Steady-state description of nonlinear CSTR (24) and (b) gap between linearized models

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Fig. 6

Set point tracking test of the nonlinear CSTR in Eq. (24)

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Fig. 7

Set point tracking test of the uncertain nonlinear CSTR in Eq. (24) with Cb2=8 kmol/m3

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Fig. 8

Set point tracking test of the uncertain nonlinear CSTR in Eq. (24) with ω2=0.2 l/min

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Fig. 9

Laboratory two tanks implementation setup

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Fig. 10

Reference tracking control of real two tanks plant

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Fig. 11

Disturbance rejection in the two-tank system



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