This brief presents the design of a controller that allows an underactuated vessel to track a reference trajectory in the x-y plane. A trajectory tracking controller designed originally for robotic systems is applied for underactuated surface ships. Such a model is represented by numerical methods and, from this approach, the control actions for an optimal operation of the system are obtained. Its main advantage is that the condition for the tracking error tends to zero, and the calculation of control actions are obtained solving a system of linear equations. The proofs of convergence to zero of the tracking error are presented here and complete the previous work of the authors. Simulation results show the good performance of the proposed control system.

Nowadays, the energetic cost of flying in electric-powered UAVs is one of the key challenges. The continuous evolution of electrical energy storage sources is overcome by the great amount of energy required by the propulsion system. Therefore, the on-board energy is a crucial factor that needs to be further analyzed. In this work, different control strategies applied to a generic UAV propulsion system are considered and a lithium polymer battery dynamic model is included as the propulsion system energy source. Several simulations are carried out for each control strategy, and a quantitative evaluation of the influence of each control law over the actual energy consumed by the propulsion system is reported. This energy, which is delivery by the battery, is next compared against a well-known control-effort-based index. The results and analysis suggest that conclusions regarding energy savings based on control effort signals should be drawn carefully, because they do not directly represent the actual consumed energy.

In this work, a novel algorithm for trajectory tracking in mobile robots is presented. For the purpose of tracking trajectory, a methodology based on the interpolation of trigonometric functions of the wheeled mobile robot kinematics is proposed. In addition, the convergence of the interpolation-based control systems is analysed. Furthermore, the optimal controller parameters are selected through Monte Carlo Experiments (MCE) in order to minimize a cost index. The MCE is able to find, the best set of gains that minimizes the tracking error. Experimental results over a mobile robot Pionner 3AT are conclusive and satisfactory. In addition, a comparative study of control performance is carried out against another controllers.