Optimization of Two Degree of Freedom PID Controller for Quadrotor with Stochastic Fractal Search Algorithm

Mandala, I G. N. A. Indra; Franky, Franky; Nazaruddin, Yul Y.

doi:10.1109/ccta.2019.8920540

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…These are the reasons why the SFS algorithm is popularly applied for solving various optimization problems. [22] Tracking state estimation of power systems [23], [24] Optimal design of Kalman filter [25] Frequency control application of an islanded microgrid [26] Economic dispatch application [27] Control application of DC motors [28] Control parameter optimization of conventional PID and FL-based PI controllers [29], [30],…”

Section: Siaw-pso Algorithmmentioning

confidence: 99%

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

2022

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The performance of a photovoltaic (PV) power generation system could be improved through the optimal control and operation of a PV module which is one of the fundamental components of this system. Thus, an appropriate PV module model along with precise knowledge of its parameters is necessary. This paper proposes a novel technique to estimate the source current, the saturation current of diodes, the shunt resistance, the series resistance, the ideality coefficient of diodes and the maximum power points (MPPs) of PV modules at the same time. This estimation problem can be described by the minimization of the root mean squared error (RMSE) of the powers obtained from the PV module through estimation and experiment. The improved stochastic fractal search (ISFS) algorithm is proposed to solve this minimization with two modifications. The first replaces the logarithmic function with the exponential function in the standard deviation of the diffusion technique to improve the exploration ability efficiently in the search space. The second utilizes the sine map instead of the uniform distribution in both the diffusion and update techniques for improving the performance of the ISFS algorithm. Numerical results demonstrate the remarkable ability of the ISFS algorithm in obtaining both the model parameters and MPPs of the PV module with high accuracy. The comparison shows that the ISFS algorithm outperforms other meta-heuristic algorithms such as a stochastic fractal search (SFS) algorithm, a particle swarm optimization (PSO) algorithm, and an improved particle swarm optimization (IPSO) algorithm in the proposed parameter estimation application.INDEX TERMS Estimation, maximum power point, meta-heuristic algorithms, model parameter, photovoltaic modules

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Section: Siaw-pso Algorithmmentioning

confidence: 99%

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

2022

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“…The 2DOFPID controller is utilized due to its aptitude for simultaneously handling the set point tracking and disturbance rejection. Several researchers have evaluated this control scheme in different fields of engineering [31][32][33][34]. For the inner current loop, a nonlinear higher-order super-twisting integral sliding controller (STISM) [35] is adopted to achieve a robust and fast reference current regulation.…”

Section: Introductionmentioning

confidence: 99%

A Two-Degree-of-Freedom PID Integral Super-Twisting Controller Based on Atom Search Optimizer Applied to DC-DC Interleaved Converters for Fuel Cell Applications

Saadi,

Hammoudi,

Salah

et al. 2023

Electronics

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This paper focuses on the real-time implementation of an optimal high-performance control applied to an interleaved nonisolated DC/DC converter designed for fuel cell applications. Three-phase interleaved boost converters are utilized to minimize input current undulation, increase efficiency, and provide a high output voltage in order to ensure the performance of the FC stack. The proposed control strategy contains an outer loop that generates the reference current based on a two-degree-of-freedom PID controller. This controller provides a robust setpoint tracking and disturbance rejection, which improves the system’s response and efficiency. A fast inner regulation loop based on a super-twisting integral sliding mode (STISM) algorithm is developed to achieve a fixed converter output voltage, equitable phase current sharing, and fast regulation against load disturbances in failure operation. The STISM algorithm exhibits a rapid convergence property of the sliding mode and effectively avoids the chattering phenomena frequently observed in conventional sliding modes. The proposed controller’s gains are determined using the atom search optimization algorithm, which ensures exceptional reliability and a high degree of robustness and stability of the controllers under a variety of operational conditions. This method is inspired from the behavior of atoms and their electrons during the excitation process leading to a one-of-a-kind optimization technique which contributes to the controller’s reliability. Using Matlab-Simulink simulation tools, the efficacy and performance of the designed control have first been evaluated and assessed and compared with other optimization algorithms, and then with a dual loop based on a PID controller. Then, they have been verified by real-time hardware implementation on a 1.2 KW prototype FC converter driven by the dSPACE-1104 card under a variety of tests. The suggested approach offers impressive experimental results in dynamic and steady states.

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“…In recent years, scientists and researchers have developed multiple control strategies to enhance and improve the stability and movement of unmanned aerial systems [6], [7]. Most of these methods involve the use of conventional PID controllers [8]- [11] which are easy to implement. However, they are not recommended for applications requiring precision during maneuvers such as inspection drones carrying on-board cameras.…”

Section: Introductionmentioning

confidence: 99%

Flight parameters improvement for an unmanned aerial vehicle using a lookup table based fuzzy PID controller

Benbouali

Chabni

Taleb

et al. 2021

IJEECS

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In this paper, a control scheme based on lookup table fuzzy proportionalintegral-derivate (PID) controller for the quadrotor unmanned aerial vehicle (UAV) movement control is proposed. This type of control provides enhanced quadrotor movement control beyond what can be achieved with conventional controllers and has a less computational burden on the processor. The proposed control scheme uses three lookup table based fuzzy logic controllers to control the different movement ranges of a quadrotor (i.e. roll, pitch, and yaw) to achieve stability. The mathematical model of a quadrotor, used to design the proposed controller, is derived based on the Lagrange approach. The processor in the loop (PIL) technique was used to test and validate the proposed control scheme. MATLAB/Simulink environment was used as a platform for the quadrotor model, whereas a low cost and high-performance STM32F407 microcontroller was used to implement the controllers. Data transfer between the hardware and software is via serial communication converter. The control system designed based on simulation is tested and validated using “processor in the loop” techniques.

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Optimization of Two Degree of Freedom PID Controller for Quadrotor with Stochastic Fractal Search Algorithm

Cited by 5 publications

References 8 publications

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

A Two-Degree-of-Freedom PID Integral Super-Twisting Controller Based on Atom Search Optimizer Applied to DC-DC Interleaved Converters for Fuel Cell Applications

Flight parameters improvement for an unmanned aerial vehicle using a lookup table based fuzzy PID controller

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