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A fuzzy adaptive controller design for integrated guidance and control of a nonlinear model helicopter

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Abstract

A fuzzy adaptive sliding mode controller is presented in this research and implemented on a nonlinear helicopter model. An integrated guidance and control for a model helicopter which is flying behind a floating platform is considered in order to stabilise dynamics and track path, simultaneously. A fuzzy logic is designed to adaptively choose the best control parameters for the sliding mode controller and relieve the designer’s concern in choosing the parameter. A matrix consisted of fuzzy sliding mode parameters is used instead of a single parameter with the goal of enhancing controller tracking capability. The problem is simulated under different conditions and intense disturbances of an empirical model, while the performance is acceptable. Controller performance is compared, and a performance analysis is done on the selection of fuzzy membership functions using an optimisation method. Simulation results show the robustness, agility, stability and overall outperformance of the proposed controller.

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Data Availability

Not applicable.

Code Availability

Not applicable.

Abbreviations

a :

Perturbed longitudinal flap** angle

A :

Longitudinal flap** angle

A :

Flap** stability derivatives

A :

System dynamics matrix

B :

Input matrix

DoF:

Degrees of freedom

e :

Error

g :

Gravity

I :

Identity matrix

ICA:

Imperialist competitive algorithm

IGC:

Integrated guidance and control

K :

Feedback gains matrix

LQR:

Linear–quadratic regulator

m :

Number of fuzzy rules

M :

Stability derivatives of pitch moment

MF:

Membership function

MIMO:

Multi-input multi-output

n :

Number of variables

NB:

Negative big

NS:

Negative small

PB:

Positive big

PID:

Proportional, integral and derivative

PS:

Positive small

q :

Perturbed pitch rate

Q :

Pitch rate

R m :

Radius of the main rotor

RMS:

Root mean square

s :

Transfer function variable

T :

Transformation matrix

u :

Perturbed forward speed

u :

Vector of inputs

U :

Forward speed

U∞ :

Wind mean speed

UAV:

Unmanned flying vehicle

w :

Perturbed vertical speed

W :

Vertical speed

x :

Horizontal displacement, position variable

x :

Vector of state variables

X:

Stability derivatives of force in x-direction

Z :

Vertical displacement

Z :

Stability derivatives of force in z-direction

ZO:

Zero

γ:

Sliding mode parameter

δ :

Deflection angle

θ :

Perturbed pitch angle

Θ :

Pitch angle

µ F :

Membership function

π:

Pi number

σ ω :

Turbulence intensity

τ f :

Rotor time constant

ω n :

White noise

~:

Difference between the desired and current value

col:

Collective

d :

Desired

i :

Input

j :

Loop counter

lon:

Longitudinal cyclic

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Authors and Affiliations

  1. Aerospace Engineering Department, K. N. Toosi University of Technology, Tehran, Iran

    Farhad Pakro & Amir Ali Nikkhah

Authors
  1. Farhad Pakro
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  2. Amir Ali Nikkhah
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Farhad Pakro and Amir Ali Nikkhah. The first draft of the manuscript was written by Farhad Pakro, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Farhad Pakro or Amir Ali Nikkhah.

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Pakro, F., Nikkhah, A.A. A fuzzy adaptive controller design for integrated guidance and control of a nonlinear model helicopter. Int. J. Dynam. Control 11, 701–716 (2023). https://doi.org/10.1007/s40435-022-00993-7

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  • DOI: https://doi.org/10.1007/s40435-022-00993-7

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