Caizhi Fan

System identification and attitude control of a small scale unmanned helicopter

This paper copes with the problem of identifying the attitude dynamics of a small scale helicopter using the frequency sweep technology based on the flight data collected near the hovering condition. The frequency domain responses of a helicopter in the lateral, longitudinal and yaw channels are analysed by the partial coherence method, and the transfer functions are obtained by the weighted fitting method. The proposed method can identify the attitude dynamics including the actuator dynamics using the flight data only without carrying out any additional ground experiments. The models identified are verified by comparing model outputs with the experimental data on a small scale helicopter in our lab. We also carried out experiments on the attitude control of the helicopter to further validate the identified models.

Nonlinear robust control of a small-scale helicopter on a test bench

A nonlinear robust controller design procedure is presented, which is designed to simultaneously satisfy multiple conflicting closed-loop performance specifications. Significantly, a robust performance specification for the experimental system, developed for studying the attitude control of a small-scale helicopter in our previous work, is discussed quantitatively. The robust performance specifications and nominal multiple closed-loop performance specifications are conflicting. Use of the Convex Integrated Design (CID) method can provide, where feasible, a single closed-loop controller which satisfies a set of multiple conflicting performance specifications. However, the resultant controller has a complex form. Here, the standard CID method is extended to a more general control system framework to solve the conflicting simultaneous performance design problem. When compared with the standard CID design, the extended CID design procedure generates a relatively simple closed-loop controller. Finally, the synthesised controller is tested in simulation and is validated with an experimental small-scale test helicopter, demonstrating the performance of the proposed controller.

Nonlinear system and control of the model-scale helicopter

A nonlinear model and control of a small-scale helicopter near hovering are investigated. Aiming at the characteristics of the model helicopter, the stabilizer bar dynamics is studied, and the tail rotor with the electronic gyro is discussed in detail. In addition, the main rotor inflow dynamics is modeled basing on the three-state nonlinear Pitt/Peters model. Then, a simplified nonlinear model is proposed for system identification and controller design. It is proved that the attitude-heave subsystem can be linearized by the dynamic feedback linearization technique. So, we conclude that the full nonlinear model can also be feedback linearized.

Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments

This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique but differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depth of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of the image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performance of the proposed method.

Adaptive Visual Servoing of a Small Scale Autonomous Helicopter: Adaptive Visual Servoing of a Small Scale Autonomous Helicopter

This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points.The controller is based on the backstepping technique,but its design differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depths of the feature points.The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates online.Two potential functions are introduced in the controller to guarantee convergence of image errors and to avoid trivial solutions of the estimated parameters.The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter.Simulations have been also conducted to demonstrate the performances of the proposed method.