Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Iswanto, Iswanto; Ahmad, Irfan

doi:10.18196/26142

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…The main reason behind using fuzzy logic controller instead of classical control technique is that the current wind turbine system is considered highly nonlinear and hence requires a control approach that can deal well with such nonlinearity. In addition, fuzzy logic controller eliminates the need for any linearization procedure [50]- [53]. However, traditional control method, such as PID controller, will not be able to work without linearizing the system around some operating points.…”

Section: Fig 4 Matlab Drive Train Modelmentioning

confidence: 99%

Design of an Integral Fuzzy Logic Controller for a Variable-Speed Wind Turbine Model

Almaged,

Mahmood,

Alnema

2023

Journal of Robotics and Control

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The demand for electricity is continuously growing around the world and thus the need for renewable and long-lasting sources of energy has become an essential challenge. Wind turbines are considered one of the major sources of renewable electricity generation. Therefore, there is a crucial demand for wind turbine model and control systems that are capable of precisely simulating the actual wind power systems. In this paper, an advanced fuzzy logic controller is proposed to control the speed of a wind turbine system. Initially, aero dynamical, mechanical and electrical models of two mass wind turbines models are derived. Analytical calculation of the power coefficient is adopted through a nonlinear function of six coefficients that mainly depends on pitch angle and tip speed ratio. The ultimate power output from the turbine can reach up to 50 % which is achieved at zero pitch angle with an approximately tip speed ratio of eight. This is then followed by designing a hybrid fuzzy-plus I pitch controller to regulate the speed of the wind turbine shaft. In general, fuzzy logic control strategy have the advantages over traditional control techniques especially when the system is highly non-linear and has to deal with strong disturbances such as wind turbulence. To evaluate the reliability and robustness of the controller, the response of the wind turbine system is tested under several types of disturbances including wind fluctuation, sudden disturbances on high and low speed shafts. Simulation findings reveals that the performance of fuzzy-integral control technique outweighs that of conventional fuzzy approach in terms of multiple performance evaluation indexes such as zero overshoot and steady state error, rise time and a settling time of (32.9 s) (44.7 s) respectively. The reliability and robustness of the controller is tested by applying speed and torque disturbances of 25% of their maximum ranges. Results have revealed that the controller was able to reject all disturbances efficiently with a change in pitch angle up to a maximum of 10 degrees in order to retain a constant rotor speed at 1000 rpm.

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Section: Fig 4 Matlab Drive Train Modelmentioning

confidence: 99%

Design of an Integral Fuzzy Logic Controller for a Variable-Speed Wind Turbine Model

Almaged,

Mahmood,

Alnema

2023

Journal of Robotics and Control

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“…Fuzzy logic appears to be a good choice for autopilot. A similar algorithm was applied by Iswanto et al [76] for the efficient control of UUVs. Du et al [77] also presented a similar control algorithm for the control system design of UUV.…”

Section: Fuzzy Control Algorithmmentioning

confidence: 99%

A Review of the Various Control Algorithms for Trajectory Control of Unmanned Underwater Vehicles

Bashir,

Khan,

Iqbal

et al. 2023

Sustainability

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Unmanned underwater vehicles (UUVs) have become increasingly popular in recent years due to their use in various applications. The motivations for using UUVs include the exploration of difficult and dangerous underwater environments, military tasks in mine detection, intelligence gathering and surveillance, the inspection of offshore oil and gas infrastructure in the oil and gas industry, scientific research for studying marine life, and the search and rescue of missing persons or submerged airplanes or boats in underwater environments. UUVs offer many advantages in achieving the desired applications with increased safety, efficiency, and cost-effectiveness. However, there are also several challenges associated with their communication, navigation, power requirements, maintenance, and payload limitations. These types of vehicles are also prone to various disturbances caused by currents of the ocean, propulsion systems, and unmolded uncertainties. Practically, it is a challenging task to design a controller that will ensure optimal performance under these conditions. Therefore, the control system design is of prime importance in the overall development of UUVs. Also, the UUV controller receives input from different sensors, and the data from these sensors are used by the controller to perform different tasks. The control systems of UUVs should take into account all uncertainties and make them stable so that all sensors can perform optimally. This paper presents a complete review of different control system design algorithms for UUVs. The basic logic designs of several control system algorithms are also presented. A comparison is made based on reliability, robustness, precession, and the ability of the controller to handle the nonlinearity that is faced by UUVs during their missions. Simulation and experimental results are thoroughly studied to gain insight into each algorithm. The advantages and disadvantages of each algorithm are also presented, which will facilitate the selection of a suitable algorithm for the control system design of UUVs.

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