Design and implementation of a robust and nonlinear flight control system for an unmanned helicopter

Cai, Guowei; Chen, Ben M.; Dong, Xiangxu; Lee, Tong H.

doi:10.1016/j.mechatronics.2011.02.002

Cited by 131 publications

(69 citation statements)

References 14 publications

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“…The nose, right side and downward directions of the helicopter are defined as the x, y and z axes of the body frame, respectively, with the origin located at the center of gravity. The 6-DOF dynamic model of the helicopter can be expressed by the following Newton-Euler equations with respect to the body frame (Cai, Chen, Dong and Lee, 2011a):…”

Section: Dynamic Model Of the Uhmentioning

confidence: 99%

Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

Song

et al. 2015

International Journal of Applied Mathematics and Computer Science

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Simultaneous state and parameter estimation based actuator fault detection and diagnosis (FDD) for single-rotor unmanned helicopters (UHs) is investigated in this paper. A literature review of actuator FDD for UHs is given firstly. Based on actuator healthy coefficients (AHCs), which are introduced to represent actuator faults, a combined dynamic model is established with the augmented state containing both the flight state and AHCs. Then the actuator fault detection and diagnosis problem is transformed into a general nonlinear estimation one: given control inputs and the measured flight state contaminated by measurement noises, estimate both the flight state and AHCs recursively in each time-step, which is also known as the simultaneous state and parameter estimation problem. The estimated AHCs can further be used for fault tolerant control (FTC). Based on the existing widely used nonlinear estimation methods such as the unscented Kalman filter (UKF) and the extended set-membership filter (ESMF), three kinds of adaptive schemes (KF-UKF, MIT-UKF and MIT-ESMF) are proposed by our team to improve the actuator FDD performance. A comprehensive comparative study on these different estimation methods is given in detail to illustrate their advantages and disadvantages when applied to unmanned helicopter actuator FDD.

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Section: Dynamic Model Of the Uhmentioning

confidence: 99%

Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

Song

et al. 2015

International Journal of Applied Mathematics and Computer Science

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“…However these linear controllers are uncomplicated and reliable, lack of robustness is a major defect of them. Most of linear controllers that have been applied to unmanned helicopters are based on the ∞ approach [7][8][9]. The main advantage of the ∞ approach is its robustness in the presence of model uncertainties and disturbances.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Sliding Mode Control for a Model-Scaled Unmanned Helicopter

Razzaghian¹,

Moghaddam²

2016

Journal of Fuzzy Set Valued Analysis

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This paper presents a novel Adaptive Fuzzy Sliding Mode Controller (AFSMC) for a model-scaled unmanned helicopter as real nonlinear plant. First, in order to efficient control law design, the nonlinear model of the helicopter is reformulated as an affine nonlinear system. To do this aim, a Dynamic Inverter (DI) is introduced as a bijective function. The proposed DI is used to interconnect the helicopter actuators' main inputs to the helicopter dynamic inputs. Then, AFSMC is designed to control it, and the asymptotic stability of the closed loop system is proved using Lyapunov stability theorem. To verify the merits of the proposed controller, it is compared with traditional sliding mode control system. Simulation results confirmed that the controller as a robust and stable control method has desired controlling performance and well cope with the undesirable chattering phenomenon.

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“…A fuzzy gain-scheduling algorithm based on linearization of the nonlinear model [10] was proposed. Some literature also proposed nonlinear predictive controllers [11] [12], neural network controllers based on the nonlinear model [13,14], H  controllers [15,16] and nonlinear robust controllers [17,18] for UAHs. A feedback linearization technique with a Convex Integrated Design (CID) method was proposed [19] for a model helicopter.…”

Section: Introductionmentioning

confidence: 99%

A New Hybrid Control Architecture to Attenuate Large Horizontal Wind Disturbance for a Small-Scale Unmanned Helicopter

Zhu

Zeng

et al. 2012

International Journal of Advanced Robotic Systems

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This paper presents a novel method to attenuate large horizontal wind disturbance for a small-scale unmanned autonomous helicopter combining wind tunnel-based experimental data and a backstepping algorithm. Large horizontal wind disturbance is harmful to autonomous helicopters, especially to small ones because of their low inertia and the high cross-coupling effects among the multiple inputs. In order to achieve more accurate and faster attenuation of large wind disturbance, a new hybrid control architecture is proposed to take advantage of the direct force/moment compensation based on the wind tunnel experimental data. In this architecture, large horizontal wind disturbance is treated as an additional input to the control system instead of a small perturbation around the equilibrium state. A backstepping algorithm is then designed to guarantee the stable convergence of the helicopter to the desired position. The proposed technique is finally evaluated in simulation on the platform, HIROBO Eagle, compared with a traditional wind velocity compensation method.

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Design and implementation of a robust and nonlinear flight control system for an unmanned helicopter

Cited by 131 publications

References 14 publications

Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

Adaptive Fuzzy Sliding Mode Control for a Model-Scaled Unmanned Helicopter

A New Hybrid Control Architecture to Attenuate Large Horizontal Wind Disturbance for a Small-Scale Unmanned Helicopter

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