• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.505-516
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• 2011

The concept of the IGC(Integrated Guidance and Control) has been introduced to overcome the performance limit of the SGC(Separated Guidance and Control) loop. A new type of IGC with impact angle constraint has been proposed in this paper. Angle of attack, pitch angle rate, pitch angle and line of sight angle are considered as state variables. A controllability analysis and equilibrium point analysis have been carried out to investigate the control characteristic of the prposed IGC. The LQR(Linear Quadratic Regulator) has been adopted for the control law and detailed explanations about the adoption has been provided. The performance comparison between the IGC and the SGC has been carried out. The result of numerical simulations shows that the IGC guarantees better guidance performance than the SGC when the agile maneuver is needed for a specific guidance geometry.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.90-98
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• 2012

In this paper, the Integrated Guidance and Control (IGC) law is proposed for the Rotary Unmanned Aerial Vehicle (RUAV). The objective of the IGC law is to consider the nonlinear dynamic characteristics of the RUAV and to design a guidance law which takes into consideration the nonlinear relationship between kinematics and dynamics. In order to control the RUAV system, sliding mode control scheme is adopted. As the RUAV is an under-actuated system, a slack variable approach is used to generate the available control inputs. Through the Lyapunov stability theorem, the stability of the proposed IGC law is proved. In order to verify the performance of the IGC law, numerical simulations are performed for waypoint tracking missions.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.15-22
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• 2009

The guidance controller of the conventional aircraft consists of inner-loop (autopilot) and outer-loop (guidance). If the guidance controller can be designed as an integrated guidance and control (IGC), the various advantages exist. The integrated guidance and control formulation can compensate for the effect of autopilot lag. An integrated approach also helps avoid the iterative procedure involved in tuning the guidance and autopilot subsystems, if designed separately. Integrated design is also less susceptible to saturation and stability problems. This paper presents an approach to IGC design for the unpowered air vehicle with the only flaperon using a combination of adaptive output feedback inversion and backstepping techniques. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process.