Design of Fuzzy Fractional PD + I Controllers Tuned by a Genetic Algorithm

Jesus, Isabel S.; Barbosa, Ramiro S.

doi:10.1155/2014/676121

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…In some practical applications, it is verified that the FOPID controller has better disturbance rejection ability and less sensitivity to the parameter variations of the control system than the traditional PID controller [11]. As a result, the common PID controller is gradually replaced by the FOPID controller with the support of the researchers [12][13][14]. Therefore, the FOPID controller is adopted to control the road feeling of the SBW system in this paper.…”

Section: Introductionmentioning

confidence: 95%

The Fractional Order PID Method with a Fault Tolerant Module for Road Feeling Control of Steer-by-Wire System

Liu

Chen

et al. 2018

Mathematical Problems in Engineering

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To improve the road feeling of the steer-by-wire (SBW) system, a fractional order PID (proportion-integral-derivative) method with a fault tolerant module is proposed in this paper. Firstly, the overall road feeling control strategy of the SBW system is introduced, and then the mathematical model of road feeling control is established. Secondly, a fractional order PID (FOPID) controller is designed to control torque of the road feeling motor. Furthermore, genetic algorithm (GA) is applied to tune the FOPID controller’s parameters. Thirdly, a fault tolerant module aiming at potential failures of the motor’s torque sensor is studied to improve the reliability of the system. Kalman Filter (KF) algorithm is utilized in the fault tolerant module so as to detect failures of the motor’s torque sensor, and then fault tolerant module reconfigures the motor’s torque estimated by KF as a substitute when the torque sensor fails. Finally, simulations based on MATLAB are performed with the proposed control strategy to identify its performance, and the results demonstrate that the proposed control method is feasible and accurate.

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Section: Introductionmentioning

confidence: 95%

The Fractional Order PID Method with a Fault Tolerant Module for Road Feeling Control of Steer-by-Wire System

Liu

Chen

et al. 2018

Mathematical Problems in Engineering

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“…Some of the recent works that utilize the PI λ D μ controller are presented in [15]- [17]. This generalization was also utilized in the differentiation and integration actions of the conventional fuzzy logic controller, resulting in a fractional order fuzzy logic controller [18], [19]. For nonlinear controllers, such as sliding mode controllers (SMC), fractional calculus was introduced in the sliding surface by taking the fractional order derivative and/or integral of the state variables [20]- [27].…”

Section: Introductionmentioning

confidence: 99%

Implementation of a complex fractional order proportional-integral-derivative controller for a first order plus dead time system

Abdulwahhab

2022

IJRA

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<span lang="EN-US">This paper presents the implementation of a complex fractional order proportional integral derivative (CPID) and a real fractional order PID (RPID) controllers. The analysis and design of both controllers were carried out in a previous work done by the author, where the design specifications were classified into easy (case 1) and hard (case 2) design specifications. The main contribution of this paper is combining CRONE approximation and linear phase CRONE approximation to implement the CPID controller. The designed controllers-RPID and CPID-are implemented to control flowing water with low pressure circuit, which is a first order plus dead time system. Simulation results demonstrate that while the implemented RPID controller fails to stabilize the system in case 2, the implemented CPID controller stabilizes the system in both cases and achieves better transient response specifications.</span>

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“…optimization of fuzzy fractional controller using PSO algorithm improved the results for many kinds of systems, since it gives additional flexibility to the design. In this line of thought many applications of this type of controller were developed in the last few years Jesus and Barbosa, 2014).…”

Section: Introductionmentioning

confidence: 99%

Optimized fuzzy fractional PI-based MPPT controllers for a variable-speed wind turbine

2022

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In recent years, wind power has become one of the most popular sources of renewable electricity generation. However, the wind is, by its nature, a highly intermittent source of energy. To capture the maximum power, wind turbines are generally equipped with a Maximum Power Point Tracking (MPPT) Controller. This paper proposes effective and robust MPPT control strategies based on Fuzzy Logic controller PI (FPI) and Fuzzy logic Fractional Order controller PI (FFOPI). Particle Swarm Optimization (PSO) is used to optimize the membership functions of FPI and FFOPI. The proposed MPPT strategies are validated on a Permanent Magnet Synchronous Generator (PMSG)-variable-speed wind energy conversion system. The overall model of the wind turbine-PMSG and control scheme is developed in MATLAB/Simulink and SimPower Systems toolbox. The results show that the MPPT based on FFOPI control optimized by PSO leads to the best transient response performance and robustness.

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Design of Fuzzy Fractional PD + I Controllers Tuned by a Genetic Algorithm

Cited by 8 publications

References 25 publications

The Fractional Order PID Method with a Fault Tolerant Module for Road Feeling Control of Steer-by-Wire System

The Fractional Order PID Method with a Fault Tolerant Module for Road Feeling Control of Steer-by-Wire System

Implementation of a complex fractional order proportional-integral-derivative controller for a first order plus dead time system

Optimized fuzzy fractional PI-based MPPT controllers for a variable-speed wind turbine

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