• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.508-513
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• 2003

This paper is concerned with a mixed control with aerodynamic fin and side thrusters applied to an agile missile using two-time scale dynamic inversion and linear time-varying control technique. The nonlinear dynamic inversion method with the weighting function allocates the desired control inputs (aerodynamic fin and side thrusters) to track a reference trajectory, and the time-varying control technique guarantees the robustness for the uncertainties. Closed-loop stability is achieved by the assignment of the extended-mean of these linear time-varying eigenvalues to the left half complex plane. The proposed schemes are validated by nonlinear simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.4
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• pp.276-283
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• 2017

This paper presents position control of multicopter using nonlinear dynamic model inversion in singular perturbation. Multicopter dynamics are developed and separated into the fast time-scale variables, related with the inner-loop design, and the slow time-scale variables, related with the outer-loop design. The final design is evaluated in 6-DOF simulation. The results show accurate position tracking performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.50-57
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• 2003

In the paper, the design and evaluation of a helicopter trajectory tracking controller are presented. The control algorithm is implemented using the feedback linearization technique and the two time-scale separation architecture. In addition, and on-line adaptive architecture that employs a neural network compensating the model inversion error caused by the deficiency of full knowledge of helicopter dynamic is applied to augment the attitude control system. Trajectory tracking performance of the control system in evaluated using modified TMAN simulation program representing as Apache helicopter. It is show that the on-line neural network in an adaptive control architecture is very effective in dealing with the performance depreciation problem of the trajectory tracking control caused by insufficient information of dynamics.