Minimum energy oriented global stabilizing control of the PVTOL aircraft

Robust Stabilization of Nonlinear PVTOL Aircraft with Parameter Uncertainties

“…A state transformation [19, (1)], containing model parameters, is defined to obtain a simplified model without model parameters. Although this simplified model is actually easy to control and is widely exploited in [7][8][9][10][11][12][13][14][15][16][17][18][19], the resulting stabilization control schemes have to include the new defined states and hence include the model parameters, which are inapplicable to the case of unknown model parameters. Consequently, we turn to the original model (1) in order to develop a robust control scheme.…”

“…Considering unmeasurable velocities and bounded external disturbances, Cardenas [6] designed an output feedback control scheme by sliding-mode technique, which guaranteed local finite time stability of the closed-loop PVTOL aircraft system. Secondly, some researchers were aware that the coupling coefficient should be taken into account (hence viewed as nonzero) for gaining a better control performance [8][9][10][11][12][13][14][15][16][17][18][19]. In [9], the receding horizon control method was used to design a globally asymptotical stabilization controller with a low computational cost.…”

Control of complex robotic systems: Challenges, design and experiments

“…Basic examples of underactuated systems are the inverted pendula, including the cart-pole inverted pendulum [10], Furuta inverted pendulum [11], the wheeled inverted pendulum [12] and the inertia wheel inverted pendulum [13]. Other examples include, among others, underactuated manipulators [14], gymnast robots [15] [16], underwater vehicles [17], some mobile robots [18] and some aerial vehicles, like the PVTOL (Planar Vertical Takeoff and Landing) [19].…”

Constrained Model Predictive Control of a skid-steering mobile robot

“…Based on the approach proposed in [1,5,16] we will set to develop a model predictive receding horizon stabilizing control. Since finding the optimal solution of the global problem is quite complex; we will separate it into two subsystems: (θ) and (x, y) T , and then find an appropriate trajectory for each one.…”

“…Finally, the third approach is Model Predictive Control (MPC, or Receding Horizon Control) which uses piecewise constant controls. See for instance [1,5,6,16,17].…”