Simulation and experimental study on PID control of a quadrotor MAV with perturbation

Noordin, Aminurrashid; Basri, Mohd Ariffanan Mohd; Mohamed, Zulkifli

doi:10.11591/eei.v9i5.2158

Cited by 26 publications

(13 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Lyapunov theorem states that the system in ( 10) is said to be asymptotically stable once a real symmetric matrix P satisfies the following LMIs [29]; (11) The LMIs in (11) provides the conditions for the stability of the system in (10). The LMI region is as presented in Figure 4.…”

Section: Lmi Controller Designmentioning

confidence: 99%

“…Where the input command filter was designed to suppress tip deflection and was incorporated with LQR for tracking control. Researchers [11] proposed proportional integral derivative (PID) as feedback control for rigid body motion control of single-link flexible manipulator. A hybrid output based input shaping control scheme for vibration and position control of a single-link flexible manipulator was proposed in [12], an output-based filter was designed to reduce tip deflection while the linear quadric regulator (LQR) controller and PID controller were incorporated for precise hub angle positioning of the single-link flexible manipulator.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimized output-based input shaping for control of single-link flexible manipulator using linear matrix inequality

Tahir¹,

Muhammad²,

Muhammad³

et al. 2020

IJEECS

View full text Add to dashboard Cite

<span>Precise hub angle positioning due to tip deflections, flexible motions and under various payloads is enormous tasks in the control of single-link flexible manipulators. In this paper, output-based command shaping (OBCS) was designed using the system output for tip deflections and residuals vibrations suppression, and this was incorporated with a linear matrix inequality (LMI) closed-loop control scheme for precise hub angle positioning. The robustness of the hybrid control scheme was tested by changing the payloads from 0g to 30g, and 50g. Simulation results showed that endpoint residuals vibrations and tip deflections due to flexible motions were suppressed and hence precise hub angle positioning under various payloads was achieved. Integral absolute error (IAE), Integral square error (ISE) and Time response analysis (TRA) were used as the performance indexes. Hence, the hybrid control scheme is simple and robust.</span>

show abstract

Section: Lmi Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized output-based input shaping for control of single-link flexible manipulator using linear matrix inequality

Tahir¹,

Muhammad²,

Muhammad³

et al. 2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…First, the PID controller parameters were selected to have the desired energy consumption [16]. Then, a PID flight controller for a small aerial vehicle was presented in [17], where the proposed algorithm was deployed using Bluetooth® low energy connection via a personal area network (PAN). Besides, a design and implementation solution that utilizes low-cost components with a PID control for a quadrotor system was proposed with acceptable experimental test results [4].…”

Section: Introductionmentioning

confidence: 99%

Adaptive proportional integral derivative deep feedforward network for quadrotor trajectory-tracking flight control

Chater

Housny

Fadil

2022

IJECE

View full text Add to dashboard Cite

<span>When the controlled system is subject to parameter variations and external disturbances, a fixed-parameter proportional integral derivative (PID) controller cannot ensure its stabilization. In this case, its control requires online parameter adjustment. Specifically, as the quadrotor is a multi-input multi-output, nonlinear, and underactuated system, robust control is necessary to ensure efficient trajectory tracking flights. In this paper, an adaptive proportional integral derivative (APID) controller is proposed to control the quadrotor systems. This APID-based control strategy uses a two hidden layer deep feedforward network (DFN), where the one-step secant algorithm is chosen for initializing the DFN parameters. All the design steps of the proposed adaptive controller are described. The multidimensional particle swarm optimization (PSO) algorithm is used for tuning the DFN parameters. Then, using two simulation efficiency tests, a comparison between the proposed PSO-based APID-DFN, the (non-optimized) APID-DFN, the feedforward network APID, and the fixed-parameter PID controllers proves much efficiency of the proposed adaptive controller. The results illustrate that the proposed PSO-based APID-DFN controller can ensure good quadrotor system stabilization and achieve minimum overshoot and faster convergence speed for all quadrotor motions. Thus, the proposed control strategy could be considered an additional intelligent method-based adaptive control for unmanned aerial vehicles.</span>

show abstract

“…al. [2] designed a quadrotor micro aerial vehicle(MAV) flight controller using a PID. Since MAV was small, it was affected by slight perturbation.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor Flight System Design using Collective and Differential Morphing with SPSA and ANN

Köse¹,

Oktay²

2021

ijisae

View full text Add to dashboard Cite

Quadrotor modeling has been done with collective and differential morphing. Quadrotor initial state and morphing states are drawn in the Solidworks program. Newton-Euler approximation was used for quadrotor modeling. The mass and moment of inertia values required for modeling and simulation were obtained from the Solidworks program. Matlab / Simulink environment and state-space model approaches are used for simulations. A simultaneous perturbation stochastic approximation (SPSA) algorithm was used to determine the quadrotor morphing rates. If the morphing state obtained by SPSA is not included in the values obtained from the drawings, here it is provided to find the moments of inertia with the method based on learning by using the data obtained with the Artificial Neural Network(ANN). Proportional Integral Derivative (PID) is used as the quadrotor control algorithm. PID coefficients are also determined by SPSA.

show abstract

Simulation and experimental study on PID control of a quadrotor MAV with perturbation

Cited by 26 publications

References 19 publications

Optimized output-based input shaping for control of single-link flexible manipulator using linear matrix inequality

Optimized output-based input shaping for control of single-link flexible manipulator using linear matrix inequality

Adaptive proportional integral derivative deep feedforward network for quadrotor trajectory-tracking flight control

Quadrotor Flight System Design using Collective and Differential Morphing with SPSA and ANN

Contact Info

Product

Resources

About