Dynamic Modeling, Control System Design and MIL–HIL Tests of an Unmanned Rotorcraft Using Novel Low-Cost Flight Control System

Abstract

Unmanned helicopters have gained great importance during recent years due to their special abilities such as hover flight, vertical take-off and landing, maneuverability and superior agility. The advances in electronic devices technologies lead to more powerful and lighter processors to be used in avionic systems which have attracted more attention to these UAVs. The first steps of utilizing an unmanned helicopter are dynamic modeling, control system design and performing model-in-the-loop (MIL) and hardware-in-the-loop (HIL) tests which are presented in this paper. In this research, MIL and HIL tests of an unmanned helicopter are done using novel Linux-based flight control system built on Raspberry Pi board (different from normally used PC-104 and STM- or Arduino-based systems). Dynamic modeling, robust hierarchical control design, flight control system hardware and software architecture and MIL and HIL test results are reported here. By succeeding in these tests, it is shown that the proposed platform can be used in experimental flight tests in next steps.

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Abbreviations

\(P_{n} = \left[ {\begin{array}{*{20}c} {x_{n} } & {y_{n} } & {z_{n} } \\ \end{array} } \right]^{\text{T}}\) :

Helicopter CG position vector in earth frame

\(V_{\text{b}} = \left[ {\begin{array}{*{20}c} u & v & w \\ \end{array} } \right]^{\text{T}}\) :

Helicopter translational velocity in body frame

\(\omega_{{{\text{b}}/n}}^{\text{b}} = \left[ {\begin{array}{*{20}c} p & q & r \\ \end{array} } \right]^{\text{T}}\) :

Helicopter rotational velocity in body frame

\(\phi ,\theta ,\psi\) :

Helicopter body Euler angles (roll, pitch and yaw, respectively)

X, Y, Z :

Force components

T :

Thrust force

L, M, N :

Moment components

\(\delta_{ped,int }\) :

State defined for yaw rate feedback PI controller

\(\delta_{\text{lat}}\), \(D_{\text{lat}}\) :

Lateral cyclic control input (aileron servo)

\(\delta_{\text{lon}}\), \(D_{\text{lon}}\) :

Longitudinal cyclic control input (elevator servo)

\(\delta_{\text{col}}\), \(D_{\text{col}}\) :

Main rotor collective control input (collective servo)

\(\delta_{ped}\), \(D_{ped}\) :

Tail rotor collective control input (rudder servo)

\(\bar{\delta }_{ped}\) :

Applied tail rotor collective input

\(\beta_{1cH}\), \(a_{s}\) :

Main rotor longitudinal flapping angle

\(\beta_{1sH}\), \(b_{s}\) :

Main rotor lateral flapping angle

\(\bar{\beta }_{1cH}\), \(c_{s}\) :

Stabilizer bar longitudinal flapping angle

\(\bar{\beta }_{1sH}\), \(d_{s}\) :

Stabilizer bar lateral flapping angle

g :

Gravity acceleration

m :

Mass of helicopter

\(A_{\text{lon}}\), \(B_{\text{lat}}\) :

Main rotor longitudinal and lateral input coefficients

\(C_{\text{lon}}\), \(D_{\text{lat}}\) :

Stabilizer bar longitudinal and lateral input coefficients

\(K_{\text{sb}}\) :

Stabilizer bar flapping angles mixing coefficient

\(J_{xx}\), \(J_{yy}\), \(J_{zz}\) :

Helicopter principal moments of inertia about X, Y and Z axes

\(\tau_{\text{mr}} , \tau_{\text{sb}}\) :

Main rotor and stabilizer bar time constants

\(A_{{b_{s} }} , B_{{a_{s} }}\) :

Main rotor flapping coupling coefficients

\(K_{\beta }\) :

Main rotor blades equivalent spring constant

\(v_{\text{i}}\) :

Inflow velocity

\(P_{\text{mr}}\) :

Main rotor consumed power

\(K_{P} , K_{I}\) :

Internal PI feedback controller coefficients

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Correspondence to Hassan Salarieh.

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Khalesi, M.H., Salarieh, H. & Foumani, M.S. Dynamic Modeling, Control System Design and MIL–HIL Tests of an Unmanned Rotorcraft Using Novel Low-Cost Flight Control System. Iran J Sci Technol Trans Mech Eng 44, 707–726 (2020). https://doi.org/10.1007/s40997-019-00288-x

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Keywords

  • Unmanned rotorcraft
  • Dynamic modeling
  • Flapping dynamics
  • Robust hierarchical control
  • Flight control system
  • HIL test