Improved evolutionary algorithm and its application in PID controller optimization

Qiao, Dewen; Mu, Nankun; Liao, Xiaofeng; Le, Junqing; Yang, Fan

doi:10.1007/s11432-019-9924-7

Cited by 9 publications

(4 citation statements)

References 9 publications

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“…ACO computing can found the optimal parameters of the PID controller after several iterations. Other studies have proposed and applied a novel limited evaluation evolutionary optimization algorithm (LEEA) to adapt PID controllers [28]. The method that utilizes an adaptive genetic algorithm (AGA) for tuning parameters of the PID controller was proposed in [48].…”

Section: Adaptive Control In Industry Systemsmentioning

confidence: 99%

Heuristic Adaptive Control of Waste Gas Exhausting in Coke Making

Kačur¹,

Flegner²,

Durdán³

et al. 2020

Adv. Sci. Technol. Res. J.

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Stabilization of the carbon monoxide (CO) in the waste gas is a common technical problem in many industrial plants. Stabilization can be performed continuously by regulating the fuel input or by regulating the exhaust gas draught. This paper proposes an adaptive control system for CO stabilization in waste gases based on a discrete controller. Heuristic adaptation of a discrete controller is based on continuous optimization of controller parameters. The advantage of this solution is that the control system does not need to perform the identification of the controlled system repeatedly. The parameters of the controller are dynamically optimized during the production process. By regulating the under-pressure, we change the amount of air supplied to the combustion chambers, which affects the combustion of gaseous fuel and also the concentration of CO in the waste flue gas. The control algorithm was verified for the combustion process in coke making. The proposed control achieved good stabilization quality when verified in simulation and also in an industry operation. The CO level at which the waste gas temperature was highest was selected as the setpoint. It was found that the stabilization of CO in waste gas to lower values is possible to achieve higher waste gas temperature and by that, higher temperatures in heating chambers.

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Section: Adaptive Control In Industry Systemsmentioning

confidence: 99%

Heuristic Adaptive Control of Waste Gas Exhausting in Coke Making

Kačur¹,

Flegner²,

Durdán³

et al. 2020

Adv. Sci. Technol. Res. J.

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“…The PID controller is widely used because of its simple operation, strong applicability, and low cost. 17 While the initial parameters of PID controllers require manual tuning. Therefore, fuzzy control is introduced due to its self-adaptive advantage.…”

Section: Introductionmentioning

confidence: 99%

Particle swarm optimized fuzzy proportional-integral-derivative controller-based transverse leaf spring active suspension for vibration control

Zhang,

Long,

Lin

et al. 2023

Journal of Low Frequency Noise, Vibration and Active Control

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The transverse leaf spring (TLS) suspensions are a promising option for van vehicles due to their high load-carrying capacity and excellent handling stability. However, its ride comfort remains a major challenge. This paper investigates and compares the effects of semi-active and active control strategies to enhance the ride comfort of TLS suspensions. Firstly, a four-degree-of-freedom (4-DOF) half-car model and a multi-body dynamics (MBD) model of the TLS suspensions are established. The MBD model has higher accuracy and can describe the medium and high frequency characteristics of the TLS suspensions, such as the suspension offset frequency and the frequency response function of the body vertical acceleration (BVA). Therefore, based on the MBD half-car model with TLS suspensions, this paper proposes an optimal fuzzy PID active control strategy considering the left and right suspension coupling. The optimization objectives are the BVA, the left and right suspensions dynamic deflection, and the left and right wheels dynamic displacement. The integral absolute error is used as the evaluation criterion. The left and right fuzzy PID controllers’ parameters are obtained through particle swarm optimization. Simulation results demonstrate that the particle swarm optimization fuzzy PID active control strategy effectively controls the low-frequency vibration of the TLS suspensions and suppresses the medium- and high-frequency vibration characteristics compared with the traditional skyhook semi-active control strategy. This technology provides a reference for improving the ride comfort of the TLS suspensions.

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“…Such an approach requires expertise in the field of automatic control and electric drives [7]. In addition, such an approach can be time-consuming and error-prone [8].…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm-Based Parametrization of a PI Controller for DC Motor Control

Mavrinac

Lorencin

Car

et al. 2022

Teh. glas. (Online)

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This paper analyses the application of a genetic algorithm (GA) for the purpose of designing the control system with separately excited DC motor controlled according to the rotor angle. The presented research is based on the utilization of a mathematical model designed with separate electrical and mechanical sub-systems. Such an approach allows fine-tuning of PID controllers by using an evolutionary procedure, mainly GA. For purpose of PID tuning, the new fitness function which combines several step response parameters with the aim of forming a unique surface which is then minimized with a genetic algorithm. From the results, it can be seen that the elitism-based algorithm achieved better results compared to the eligibility-based selection. Such an algorithm achieved a fitness value of 0.999982 resulting in a steady-state error of 0.000584 rad. The obtained results indicate the possibility of applying a GA in the parameterization of the PID controller for DC motor control.

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Improved evolutionary algorithm and its application in PID controller optimization

Cited by 9 publications

References 9 publications

Heuristic Adaptive Control of Waste Gas Exhausting in Coke Making

Heuristic Adaptive Control of Waste Gas Exhausting in Coke Making

Particle swarm optimized fuzzy proportional-integral-derivative controller-based transverse leaf spring active suspension for vibration control

Genetic Algorithm-Based Parametrization of a PI Controller for DC Motor Control

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