Robust synthesis of a PID controller by uncertain multimodel approach

Toscano, Rosario

doi:10.1016/j.ins.2006.07.035

Cited by 25 publications

(12 citation statements)

References 20 publications

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“…The compensation of changes of the system parameters or system nonlinearities can be achieved by gain scheduling controllers [29], [30] or their advanced forms such as linear parameter varying (LPV) control methods [31] and multimodel approach [32], then by selftuning controllers [29] or by model reference adaptive control (MRAC) [29], [30], [33], [34]. System nonlinearities can be compensated for by model predictive control (MPC) as well [35], [36].…”

Section: Adaptive System Inner Control Loop Designmentioning

confidence: 99%

Adaptive Control of Peak Current Mode Controlled Boost Converter Supplied by Fuel Cell

Bjažić¹,

Ban²,

Perić³

2013

Journal of Power Electronics

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Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.

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Section: Adaptive System Inner Control Loop Designmentioning

confidence: 99%

Adaptive Control of Peak Current Mode Controlled Boost Converter Supplied by Fuel Cell

Bjažić¹,

Ban²,

Perić³

2013

Journal of Power Electronics

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“…Many robust controller design methods for multimodel systems are available in the literature. Toscano (2007) proposes a method to design PID and multi-PID to control nonlinear systems using multimodel in the state space representation. The time delay is approximated by a high order transfer function and the controller is tuned using an iterative algorithm with no convergence result.…”

Section: Introductionmentioning

confidence: 99%

Robust and Gain-Scheduled PID Controller Design for Condensing Boilers by Linear Programming

Oliveira

Karimi

2012

IFAC Proceedings Volumes

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This paper addresses the water temperature control in condensing domestic boilers. The main challenge of this process under the controller design perspective is the fact that the dynamics of condensing boilers are strongly affected by the demanded water flow rate. Two approaches are presented in this paper. First, a robust PI controller is designed that stabilizes and achieves good performance for closed-loop system for a wide range of the water flow rate. Then, it is shown that if the water flow rate information is used to update the controller gains, a technique known as gain-scheduled control, the performance can be significantly improved. Several models of a boiler in different water flow rate are identified in collaboration with Honeywell, and the effectiveness of the results are illustrated by simulation.

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“…9 And because nonlinearity is always incorporated in the original control problem, for it usually involves both the physical output and the physical input, separating the nonlinearity from the control problem therefore may lead to a decreased performance. 10 The multilinear model control approach has attracted much attention and has been studied extensively in the past years [11][12][13][14][15][16][17][18] for its potential ability to control chemical processes with highly nonlinear characteristics as a result of wide operating ranges and large set-point changes. The key concept is to represent the nonlinear system as a combination of linear systems to which classical controller design techniques can be easily applied.…”

Section: Introductionmentioning

confidence: 99%

Multilinear Model Control of Hammerstein-like Systems Based on an Included Angle Dividing Method and the MLD-MPC Strategy

Song

2009

Ind. Eng. Chem. Res.

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This article introduces the multilinear model control approach to SISO Hammerstein-like systems. An included angle dividing method is proposed to decompose the operating spaces and determine linear model banks for SISO Hammerstein-like systems through measuring the nonlinearity of the static IO curves. On the basis of the linear model bank, the MLD-MPC strategy is employed for set-point tracking control. Two chemical processes are studied using the proposed included angle dividing method and MLD-MPC strategy. Closedloop simulations demonstrate that the proposed dividing method is useful and effective for the multilinear model approach and the MLD-MPC strategy is excellent for nonlinear systems.

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Robust synthesis of a PID controller by uncertain multimodel approach

Cited by 25 publications

References 20 publications

Adaptive Control of Peak Current Mode Controlled Boost Converter Supplied by Fuel Cell

Adaptive Control of Peak Current Mode Controlled Boost Converter Supplied by Fuel Cell

Robust and Gain-Scheduled PID Controller Design for Condensing Boilers by Linear Programming

Multilinear Model Control of Hammerstein-like Systems Based on an Included Angle Dividing Method and the MLD-MPC Strategy

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