A New Tuning of PID Controllers Based on LQR Optimization

Argelaguet, Rosa; Pons, Montserrat; Quevedo, Joseba; Aguilar, Josep Gisbert

doi:10.1016/s1474-6670(17)38256-3

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…In this work, the proportional gains were firstly LQR optimised (Argelaguet et al, 2000;Glattfelder and Schufelberger, 2003), then tuned to meet desired specifications. In this work, the proportional gains were firstly LQR optimised (Argelaguet et al, 2000;Glattfelder and Schufelberger, 2003), then tuned to meet desired specifications.…”

Section: Pi Controlmentioning

confidence: 99%

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers

2013

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Hydro turbines have complex non-linear dynamics, especially in the presence of large or abrupt load disturbances. In this work, the implementation of a weighted multiple model adaptive control (WMMAC) scheme on a hydro turbine plant was studied. To ensure stability, the system was designed in accordance with the virtual equivalence system and adaptive mixing control criteria. Four candidate linear estimator models were chosen representing 25%, 50%, 75% and 100% load conditions. For each candidate estimator model, a compensator was designed to meet performance requirements under the corresponding candidate load conditions. The performance of three different control structures; the H ∞ , LQG/LTR and PI controllers, used in the WMMAC scheme, were simulated under abruptly changing and smoothly varying load conditions. To account for the transients before reaching synchronous speed, in the first 50 seconds, a no-load compensator was used. From the results, the PI controller produced the best performance.

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Section: Pi Controlmentioning

confidence: 99%

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers

2013

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“…Devido a sua simplicidade, robustez e estabilidade,é até hoje alvo de pesquisas no intuito de sintetizar mecanismosótimos de sintonia Bari et al (2019), Arya and Pachauri (2019) A otimização, no contexto de sistemas de controle, está relacionada a minimização de algum critério que normalmente reflete performance ou economia de energia. O Regulador Linear Quadrático (LQR)é um controladorótimo clássico e possui diversas formulações para síntese PID Argelaguet et al (1997), e Harshavardhana Reddy et al (2016.É utilizado para aplicações em sistemas lineares, ou linearizados em um ponto de operação.…”

Section: Introductionunclassified

Controlador PID Ótimo Baseado em PSO Aplicado a um Aeropêndulo

Barros

Lima

2020

Anais Do Congresso Brasileiro De Automática 2020

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Nesse artigo está sendo proposta a utilização de um algoritmo de enxame de partículas para otimizar a sintonia de um controlador PID, aplicado a um aeropêndulo. O problema de otimização é calculado iterativamente a partir do modelo não linear do sistema, para tal, foi proposta a formulação de uma função de custo como uma combinação do critério ITSE (Integral time Squared Error) e TV (Total Variation) ponderando assim o erro de rastreamento, assim como o esforço de controle. A sintonia resultante foi comparada com um LQR e um PID derivado deste, ambos baseados no modelo do sistema linearizado em um ponto de operação.

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“…The basic method is the timedomain method. Many modern control methods such as adaptive control [4,5] , robust control [6,7] , optimal control [8] , and other methods [9] have been applied in the control of the gimbal. Modern control theory uses different control methods for specific problems of the system, which can improve a certain performance index of the system.…”

Section: Introductionmentioning

confidence: 99%

Interval Type-2 Fuzzy Sliding-Mode Control of Three-Axis Stabilization Gimbal

Yan

Shi

et al. 2020

IEEE Access

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Aiming at the attitude control problem of three-axis stabilization gimbal, an algorithm combining interval type-2 fuzzy control and sliding-mode control was designed. Firstly, the mathematical model of the three-axis stabilization gimbal actuator was established after analyzing the mechanical structure of the three-axis stabilization gimbal. Then, a sliding-mode controller was designed based on the position ring of the actuator of three-axis stabilization gimbal. An interval type-2 control was used to reduce chattering in sliding-mode control. The switching function and its derivative are taken as the input of fuzzy control, and the rate of change of the approach law is taken as the output of fuzzy control. Fuzzy control can adjust the gain of sliding-mode surface dynamically, enhance the adaptability on external random disturbance, improve the speed of convergence and weaken chattering. The simulation results show that the output of the controller designed in this paper is more stable, and the tracking of the three-axis stabilization gimbal is more rapid and accurate.INDEX TERMS Interval type-two fuzzy control; sliding-mode control; three-axis Stabilization gimbal; position ring

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A New Tuning of PID Controllers Based on LQR Optimization

Cited by 4 publications

References 3 publications

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers

Controlador PID Ótimo Baseado em PSO Aplicado a um Aeropêndulo

Interval Type-2 Fuzzy Sliding-Mode Control of Three-Axis Stabilization Gimbal

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A New Tuning of PID Controllers Based on LQR Optimization

Cited by 4 publications

References 3 publications

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">&infin;, LQG and PI controllers

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">&infin;, LQG and PI controllers

Controlador PID Ótimo Baseado em PSO Aplicado a um Aeropêndulo

Interval Type-2 Fuzzy Sliding-Mode Control of Three-Axis Stabilization Gimbal

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Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers

Multiple model adaptive control of a hydro turbine plant - performance of H<SUB align="right">∞, LQG and PI controllers