Acceleration feedback control for direct-drive motor system

Han, Jianda; Wang, Y.C.; Tan, Dongmei; Wang, Xu

doi:10.1109/iros.2000.893161

Cited by 22 publications

(17 citation statements)

References 12 publications

(5 reference statements)

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“…Recently, the acceleration feedback control (AFC) has been successful in suppressing uncertainties and external disturbances of mechatronic systems [11][12][13][14]. There disturbances and uncertainties are presented as force or torque, which is directly reflected in acceleration signal.…”

Section: Doi: 102514/145659mentioning

confidence: 99%

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Acceleration-Feedback-Enhanced Robust Control of an Unmanned Helicopter

2010

Journal of Guidance, Control, and Dynamics

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While a few proposed control strategies have shown their acceptable effectiveness, performance improvement on stability and robustness of unmanned helicopters are still imperative and a great challenge due to strong nonlinearities, extensive parameter uncertainties and external disturbances when the flight condition is terrible, such as flight on a windy day. Because acceleration feedback control is advantageous in terms of simple controller structure and easy implementation, we attempt to incorporate it into the tracking control of an unmanned helicopter that is highly nonlinear and underactuated. In this paper, we use a prefilter to formulate a new acceleration feedback control and then use it as a robust enhancement for the H 1 algorithm to attenuate uncertainties and external disturbances involved in the tracking control of an unmanned helicopter. We conduct simulations with an unmanned model helicopter and compare the tracking performance of the helicopter with and without acceleration feedback control. The results show that the use of acceleration feedback control does enhance tracking performance greatly compared to the standard H 1 control.

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Section: Doi: 102514/145659mentioning

confidence: 99%

“…While AFC has been successful [11][12][13][14], it cannot be used directly in the control of an unmanned helicopter for the following reasons:…”

Section: Doi: 102514/145659mentioning

confidence: 99%

Acceleration-Feedback-Enhanced Robust Control of an Unmanned Helicopter

2010

Journal of Guidance, Control, and Dynamics

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“…If m = n, i.e., for a fullactuated system, the idea of high-gain AFC is to design the following controller as in [17] …”

Section: High Gain Afcmentioning

confidence: 99%

Acceleration Feedback Enhanced <I>H</I><SUB>∞</SUB> Disturbance Attenuation Control for a Class of Nonlinear Underactuated Vehicle Systems

He¹

2008

Acta Automatica Sinica

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In this paper, a generalized acceleration feedback control (AFC) design method, named AFC enhanced H∞ controller, is proposed for both fullactuated and underactuated nonlinear autonomous vehicle systems. The AFC is designed as a robust enhancement to the normal control based on known dynamics. First, in order to reject the uncertainties and external disturbances, a linear prefilter is used in the new AFC design method to replace the high gain in the normal AFC. Then, backstepping algorithm is applied to the AFC design of underactuated systems. The analysis of both the disturbance attenuation in frequency domain and input-output finite gain L2 stability shows the new controller design method is applicable. In the end, simulations are conducted with respect to the tracking control of unmanned model helicopter. The results are compared with those obtained by the tracking control without AFC to verify the feasibility of the new method. Key words Disturbance attenuation, acceleration feedback control, underactuated systems, backstepping, nonlinear H∞ control Unmanned vehicles are being anticipated to handle some high-risk tasks that are dangerous or even impossible for humans. The general goal of the autonomous control for unmanned vehicles is to enable these systems to complete tasks with minimal human interventions. Precise tracking control is a key technology for unmanned systems which are widely used in the areas such as satellite clusters, air traffic control, and the U×Vs in battlefield (unmanned ground/surface/air vehicles) [1] . However, there are at least three difficulties or challenges in the tracking control of unmanned vehicles.1) The dynamics of most unmanned systems are highly nonlinear, time-varying, and coupled, which might be too complicated to be used for controller design. The controller based on a linearized or simplified model might only guarantee a local performance or result in unexpected tracking error because of the model differences.2) The working environments of unmanned vehicles are usually dynamic, complex, and unstructured, which bring unpredictable disturbances to the control system, for example, the aerodynamics of UAV and the wave/wind for USV.3) Many unmanned vehicles, such as UAV [2] , USV [3−4] , and UUV [5] are underactuated, i.e., a system possessing more degrees of freedom than independent control inputs, which might bring more difficulties for its controller design.Thus, how to overcome the above difficulties and achieve high tracking performance has been one of the main tasks of the autonomous control of unmanned vehicles.Traditional robust and adaptive control methods for uncertainty and external disturbances suffer from several problems, including conservativeness because of the inaccuracy in the preassumption of uncertainties, online divergence because of unknown external disturbances, and the complication for real-time implementation.Many researches on the trajectory tracking of underactuated vehicles have been proposed [6] , among which backstepping technique so...

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“…Meanwhile new technologies have been designed for measuring angular velocities and accelerations, e.g. brushless AC motors with digital servo-drivers, microcontroller based measurements (Laopoulos and Papageorgiou 1996), digital processing (Kadhim et al 1992), (Lygouras et al 1998), linear accelerometers (Ovaska and Vliviita 1998), (Han et al 2000). However, such technologies are not very common in applications yet.…”

Section: Velocity and Acceleration Measurementsmentioning

confidence: 99%