Antenna Azimuth Position Control Using Fractional Order PID Controller Based on Genetic Algorithm

Mahmood, Ali Majeed; Almaged, Mohammed; Abdulla, Abdulla I.

doi:10.1088/1757-899x/1152/1/012016

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…From the plot and equations ( 21) to (23), it is evident that the highest interactive effectiveness is for φ "1. This is a criterion for design; the driver response time should always be much less than the specified threshold.…”

Section: Resultsmentioning

confidence: 98%

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Effect of Human Response on the Effectiveness of Advanced Vehicle Control Systems (HRAVCS)

Iskandarani¹

2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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This work aims to investigate the effect of driver response to relayed messages through Human Machine Interface (HMI) on the effectiveness of Human-Vehicle Interface (HVI) and to enable the optimized design of HMI. The investigation and mathematical modeling cover vehicles with Advanced Vehicle Assistant System (ADAS), which operates using Advanced Vehicle Control System (AVCS). The presented model uses driver response time and machine (electronics, sensors, processors) processing time to measure vehicular efficiency and driver interaction, which is also a function of the HMI design, and the way messages are passed to the driver. The produced model uses a probability function that can be used in the design and testing process to assess the effect of failure on the designed interface and relates the function to the driver's response time ratio and the vehicle electronics' processing time. The presented work concluded that as the driver response time increases, effective interaction decreases as a probability function. Also, as the driver response time deviates from the specified threshold, the effective interaction decreases, which also applies to the processing time. In addition, as the time ratio between the driver responses to the machine processing (Time Ratio) increases, the effective interaction parameter (R) value decreases. The work also proved that a more adaptive model is possible using a probability function correlated to the response time ratio to processing time.

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Section: Resultsmentioning

confidence: 98%

“…Optimized HMI, together with AVCS, can provide drivers with an interactive, proactive system that supports their decisions by informing them, advising them of the best course of action to be taken, and under critical conditions to act on behalf of the driver to avoid traffic incidents and fatal accidents [21], [22], [23].…”

Section: Introductionmentioning

confidence: 99%

Effect of Human Response on the Effectiveness of Advanced Vehicle Control Systems (HRAVCS)

Iskandarani¹

2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…The motor and the load are combined into a single system, and its formula includes all of the required parameters. Finally, the gearbox increases the applied torque while decreasing the speed and vice-versa by changing the gear ratio [3]. Figure 2 depicts the schematic diagram of the physical subsystems with their parameters and internal connections [3].…”

Section: Modeling Of the Systemmentioning

confidence: 99%

“…Using the state-space representation, the state feedback controller was derived, and the pole placement method was utilized to guarantee that the controlled system met the requirements for the transient response. Mahmood et al [3] have proposed a genetic algorithm-based FOPID controller for the position control of the antenna azimuth system. The genetic algorithm is used with different types of cost functions, including Integral Time Square Error (ITSE), Integral Square Error (ISE), and Mean Square Error (MSE).…”

Section: Introductionmentioning

confidence: 99%

Performance of the optimal nonlinear pid controller for position control of antenna azimuth position system

Rasheed¹,

Yousif²,

Al-Wais³

2023

MMEP

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This study presents the improvement in the performance of the Proportional-integral-derivative (PID) controller for position control of antenna azimuth position system subjected to external disturbance. The design of the PID controller is developed by adding the arc tan function of error instead of the direct error in an integral part of the PID controller, yielding a Nonlinear PID controller (NPID). A Particle Swarm Optimization (PSO) is used in this study to tune the parameters of the PID and NPID controllers using the Root Mean Square Error (RMSE) cost function. The simulations have been accomplished under the MATLAB/Simulink environment. The simulation results show that a PSO-based NPID controller provides superior steady and transient state performance compared to a PSO-based PID controller. In addition, the effectiveness of the proposed controller is verified via numerical simulation compared to the performance of other controllers with and without external disturbance.

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“…Recently, with the realization of a significant milestone in the design of fractional order controller by Podlubny [12], the concept of traditional PID controller has been extended to a more flexible structure, making the fractional order PID controller more suitable for various control objects, such as antenna azimuth position control system [13], photovoltaic power generation system [14], intelligent pneumatic actuator system [15] and pH neutralization process [16]. Therefore, the research and application of fractional order PID controller and its related controllers receive the increasing attention.…”

Section: Introductionmentioning

confidence: 99%

Fractional order zero phase error tracking control of a novel decoupled 2-DOF compliant micro-positioning stage

Wu¹,

Lai²,

Zhang³

et al. 2021

J. Micromech. Microeng.

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This study focuses on a piezo-actuated two-degrees-of-freedom (2-DOF) decoupled compliant micro-positioning stage driven by a novel compound bridge-type amplification mechanism embedded with Scott-Russell mechanism. According to the system identification, the transfer functions of two working directions are obtained. Both of the measured dynamic cross couplings between them are also lower than −40 dB, demonstrating that the single-input-single-output control strategy can be adopted reasonably. Based on the identified frequency response, a fractional order proportional-integral (FOPI) controller is designed for the 2-DOF compliant micro-positioning stage. Compared with the integer order proportional-integral (IOPI) controller using same parameters, the amplitude error of the FOPI controller is 2% lower than that of IOPI controller. Additionally, a fractional order zero phase error controller (FOZPETC) is designed by obtaining the inverse of the fractional order closed-loop system in a large frequency range. And the gain of the corrected control system is 1 in a wide frequency band to eliminate the phase error in the close-loop control system. Finally, using the compound control strategy of FOZPETC+FOPI, a series of trajectory tracking tests are carried out on the proposed novel 2-DOF compliant micro-positioning stage. All the experimental results prove that the designed controller can achieve good positioning and tracking performance of the micro-positioning stage, and confirm the effectiveness of the compound control strategy of FOZPETC+FOPI.

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Antenna Azimuth Position Control Using Fractional Order PID Controller Based on Genetic Algorithm

Cited by 3 publications

References 11 publications

Effect of Human Response on the Effectiveness of Advanced Vehicle Control Systems (HRAVCS)

Effect of Human Response on the Effectiveness of Advanced Vehicle Control Systems (HRAVCS)

Performance of the optimal nonlinear pid controller for position control of antenna azimuth position system

Fractional order zero phase error tracking control of a novel decoupled 2-DOF compliant micro-positioning stage

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