SDRE and LQR Controls Comparison Applied in High-Performance Aircraft in a Longitudinal Flight

Santos, Guilherme Pacheco dos; Kossoski, Adriano; Balthazar, José Manoel; Tusset, Ângelo Marcelo

doi:10.31763/ijrcs.v1i2.329

Cited by 4 publications

(3 citation statements)

References 40 publications

(56 reference statements)

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“…The UX-7V VTOL UAV operator can easily control the aircraft in a position-assisted flight mode [84] [85]. The altitude and position are locked in this mode by the computed trajectory of the flight controller [86][87] [88]. Therefore, the input to the empirical model of this research is not the remote-control input from the operator but the command given to the actuator from the flight controller.…”

Section: A Empirical Modelmentioning

confidence: 99%

Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Priyambodo

Majid²,

Shouran³

2023

Journal of Robotics and Control

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Vertical take-off and landing (VTOL) is a type of unmanned aerial vehicle (UAV) that is growing rapidly because its ability to take off and land anywhere in tight spaces. One type of VTOL UAV, the tail-sitter, has the best efficiency. However, besides the efficiency offered, some challenges must still be overcome, including the complexity of combining the ability to hover like a helicopter and fly horizontally like a fixed-wing aircraft. This research has two contributions: in the form of how the analytical model is generated and the tools used (specifically for the small VTOL quad tail-sitter UAV) and how to utilize off-the-shelf components for UAV empirical modeling. This research focuses on increasing the speed and accuracy of the UAV VTOL control design in fixed-wing mode. The first step is to carry out analysis and simulation. The model is analytically obtained using OpenVSP in longitudinal and lateral modes. The next step is to realize this analytical model for both the aircraft and the controls. The third step is to measure the flight characteristics of the aircraft. Based on the data recorded during flights, an empirical model is made using system identification technique. The final step is to vali-date the analytical model with the empirical model. The results show that the characteristics of the analytical mode fulfill the specified requirements and are close to the empirical model. Thus, it can be concluded that the analytical model can be implemented directly, and consequently, the VTOL UAV design and development process has been shortened.

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Section: A Empirical Modelmentioning

confidence: 99%

Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Priyambodo

Majid²,

Shouran³

2023

Journal of Robotics and Control

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“…The LQR is the state feedback control that minimizes a cost function, as presented in Eq. (2) [37,38]. The matrices 𝑄 and 𝑅 determine the relative importance of the error and energy expenditure [39].…”

Section: Alqg Designmentioning

confidence: 99%

Adaptive Linear Quadratic Gaussian Speed Control of Induction Motor Using Fuzzy Logic

Maghfiroh,

Ma’arif,

Adriyanto

et al. 2023

JESA

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An induction motor's speed can be managed in a variety of ways using a Variable Frequency Drive (VFD). In this study, the speed control of an induction motor will be controlled by applying Indirect Field Oriented Control (IFOC) combined with Linear Quadratic Gaussian (LQG). Conventional LQG control is a linear controller; therefore, if the system's dynamic is high and over the linear boundary, the LQG performance will not be optimal. Therefore, Adaptive LQG (ALQG) is proposed. Fuzzy logic is used as an adaptive algorithm with low complexity and ease of implementation. The significance of this study lies in its endeavor to tackle the challenges associated with nonlinearities and high dynamics in induction motor control. The average performance of speed variation and load variation tests proves that ALQG is superior in terms of settling time and undershooting than PID and LQG. PID has the highest overshoot with the smallest Integral Absolute Error (IAE). In comparison, ALQG is superior to conventional LQG in terms of IAE with 3.59% lower.

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“…The proportional Integral Derivative (PID) controller has been known for its wide use in many control systems; hence, it also has been applied to control altitude in quadrotor [9] [10]. The other controller is Sliding Mode Control (SMC) [11], Linear Quadratic Regulator (LQR) [12][13], Predictive Control [14], Fuzzy Control [15] [16], Neural Network [17] [18], Fractional Order PID [19], Feedback Linearization [20], and other control techniques [21]. This research presented an application of the Integral State Feedback (ISF) controller for altitude control in quadrotor as a practical solution that enables a precise and robust control system performance.…”

Section: Introductionmentioning

confidence: 99%

Altitude Control of UAV Quadrotor Using PID and Integral State Feedback

Ma’arif,

Suwarno,

Nur’aini

et al. 2023

BIO Web Conf.

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Applications of control techniques for stabilizing altitude in a UAV Quadrotor, along with a comprehensive performance comparison, are presented in this paper. The two compared control techniques are: a Proportional Integral Derivative (PID) and Integral State Feedback (ISF) controller. While PID control consists of a Proportional, an Integral and a Derivative Controller, the Integral State Feedback consists of an Integral and a State Feedback Controller. Each part of the control technique provides advantages and drawbacks in the controlled system performance. Numerical simulations in the research were performed on Simulink MATLAB to provide quantitative results in control performance comparison; thus, a quadrotor model was designed prior to the application of control techniques. Based on the numerical results, ISF control resulted in a better settling time with zero overshoot than PID. Meanwhile, the PID control had a better rise time with a big overshoot than ISF in its system response. Therefore, it can be concluded that the ISF Controller was better than PID regarding the settling time and the overshoot response.

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SDRE and LQR Controls Comparison Applied in High-Performance Aircraft in a Longitudinal Flight

Cited by 4 publications

References 40 publications

Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Adaptive Linear Quadratic Gaussian Speed Control of Induction Motor Using Fuzzy Logic

Altitude Control of UAV Quadrotor Using PID and Integral State Feedback

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