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This paper proposes a new adaptive controller for a 2-Degree of Freedom (DOF) helicopter system in the presence of input quantization. The inputs are quantized by uniform quantizers. A nonlinear mathematical model is derived for the 2-DOF helicopter system based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. A new adaptive control algorithm is developed by using backstepping technique to track the pitch and yaw position references independently. Only quantized input signals are used in the system which reduces communication rate and cost. It is shown that not only the ultimate stability is guaranteed by the proposed controller, but also the designers can tune the design parameters in an explicit way to obtain the required closed loop behavior. Experiments are carried out on the Quanser helicopter system to validate the effectiveness, robustness and control capability of the proposed scheme.

This paper proposes an adaptive nonlinear controller for a 2-Degree of Freedom (DOF) helicopter. The proposed controller is designed using backstepping control technique and is used to track the pitch and yaw position references independently. A MIMO nonlinear mathematical model is derived for the 2DOF helicopter based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. Unlike some existing control schemes for the helicopter control, the developed controller does not require the knowledge on the system uncertain parameters. Updating laws are used to estimate the unknown parameters. It is shown that not only the global stability is guaranteed by the proposed controller, but also asymptotic tracking and transient performances are quantified as explicit functions of the design parameters. Simulations and experiments are carried out on the Quanser helicopter to validate the effectiveness, robustness and control capability of the proposed scheme.

In this paper, the attitude tracking control problem of a rigid body is investigated where the states are quantized. An adaptive backstepping based control scheme is developed and a new approach to stability analysis is developed by constructing a new compensation scheme for the effects of the vector state quantization. It is shown that all closed-loop signals are ensured uniformly bounded and the tracking errors converge to a compact set containing the origin. Experiments on a 2 degreesof-freedom helicopter system illustrate the proposed control scheme.

The anti-swing control of offshore cranes presents much more challenges. Most existing controllers for offshore cranes are designed based on linearized dynamics and require the accurate values of the plant parameters. In this paper, an adaptive sliding mode control scheme is investigated for a nonlinear underactuated crane system with unmodeled dynamics. The proposed control method can ensure asymptotic stability and does not need linearization of the complicated nonlinear dynamic equations during controller design and stability analysis. To reduce the communication burden in a network, a uniform quantizer is introduced in the input communication channel. A quantized adaptive sliding mode control scheme is further developed for the underactuated cranes to compensate for the effects of input quantization and uncertain parameters. The proposed controller together with the quantizer ensures the asymptotic stability of the closed-loop system in the sense of signal boundedness and zero stabilization error. Numerical simulations are conducted to illustrate the effectiveness of proposed schemes.