UAV Control Based on Dual LQR and Fuzzy-PID Controller

Al-Isawi, Malik M. A.; Attiya, Adnan Jabbar; Adoghe, Julius O.

doi:10.22153/kej.2020.08.001

Cited by 3 publications

(3 citation statements)

References 20 publications

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“…Since the controller needs to change variables and control inputs to convert the nonlinear model to a linear model, resulting in a loss of accuracy. Thus, feedback linearization requires a more accurate model to achieve [5]. In addition, although the feedback linearization has a good tracking effect, it is more sensitive to sensor noise.…”

Section: Nonlinear Controller 321 Feedback Linearizationmentioning

confidence: 99%

The development status and analysis of motion control algorithms applied to UAVs

Qin

2023

ACE

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Due to the high mobility and longer durability, UAVs are widely used in military and various civilian fields. The control system of the UAVs is a key part of ensuring that the UAVs fulfil various instructions and complete the tasks. In response to the above issues, this paper summarizes and analyses the current status of motion control algorithms for unmanned aerial vehicles based on existing data. Firstly, the mainstream control technology of UAVs is divided into linear control technology, nonlinear control technology and machine learning-based control technology, and they are discussed separately. Subsequently, the performance of three technologies is evaluated and compared, and the advantages, disadvantages and the applicable environment of each controller are introduced. Finally, the future development direction of UAVs controller is analysed and prospected.

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Section: Nonlinear Controller 321 Feedback Linearizationmentioning

confidence: 99%

The development status and analysis of motion control algorithms applied to UAVs

Qin

2023

ACE

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“…In the literature, it is possible to find documents in which the LQR technique is combined with other types of controllers, such as fuzzy controllers. For example, in [13], Malik presents the development of a longitudinal controller design for an autonomous unmanned aerial vehicle (UAV). In this work, the researchers proposed a dual-loop (innerouter loop) control method based on intelligent algorithms.…”

Section: Introductionmentioning

confidence: 99%

Discrete Integral Optimal Controller for Quadrotor Attitude Stabilization: Experimental Results

Godinez-Garrido,

Santos-Sánchez,

Romero-Trejo

et al. 2023

Applied Sciences

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The Unmanned Aerial Vehicle (UAV) attitude stabilization problem has been dealt with in many previous works through applying a vast range of philosophies of control strategies. In this paper, a discrete controller based on a Linear Quadratic Regulator (LQR) plus integral action is synthesized to stabilize the attitude and altitude of a quadrotor helicopter. This kind of control strategy allows us to reduce the energy consumption rate, and the desired UAV behavior is properly achieved. Experimental tests are conducted with external disturbances such as crosswinds deliberately added to affect the performance of the aerial vehicle. This provides experimental evidence that the integral part considered in the proposed control strategy contributes to improving the performance of the vehicle under external disturbances. In fact, a comparative analysis of potential and kinetic energy consumption is developed between the Optimal Integral Controller (OIC) and a Proportional Integral Derivative Controller (PID), allowing us to determine the level of improvement of the closed-loop system when the discrete Integral Optimal Controller is applied.

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“…Many researchers have paid attention to the steady flight of aerial vehicles in strong winds. Different types of approaches and techniques including adaptive control, PID control, and backstepping have been studied [13] and [14]. In reference [15], the dynamics of the whole process are established through hybrid system theory.…”

Section: Introductionmentioning

confidence: 99%

Maneuvering Control of Hexrotor UAV Equipped With a Cable-Driven Gripper

Ali

Han

2021

IEEE Access

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This study proposes a control method for the maneuvering control of an aircraft system equipped with a cable-driven gripper. The UAV chosen for the study is a hex-rotor due to its durability and redundancy. The reason for opting for the cable-driven robotic arm is because of its extended range as compared to a fixed robotic arm. The aircraft system also contains an Ultra HD camera which helps to locate and identify the target object. Since the UAV grabs the object, the extra weight introduces some instability in the system. To help stabilize the dynamic behavior of the gripper and reduce external wind disturbance, we need an effective and robust control mechanism. To tackle these issues, this paper designs a control method based on the Model Reference Adaptive Control with an integrator (MRACI) with reference dynamics like an observer. On one hand, first, verify the performance of the proposed controller using computer-based simulations. On the other hand, it also applies the designed method to hardware-based results. The simulations and experimental results show that the designed controller works as intended and the errors are within an acceptable range.

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UAV Control Based on Dual LQR and Fuzzy-PID Controller

Cited by 3 publications

References 20 publications

The development status and analysis of motion control algorithms applied to UAVs

The development status and analysis of motion control algorithms applied to UAVs

Discrete Integral Optimal Controller for Quadrotor Attitude Stabilization: Experimental Results

Maneuvering Control of Hexrotor UAV Equipped With a Cable-Driven Gripper

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