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.

This paper aims to solve the problem of tracking optimal profiles for a nonlinear multivariable fed-batch bioprocess by a simple but efficient closed-loop control technique based on a linear algebra approach. In the proposed methodology, the control actions are obtained by solving a system of linear equations without the need for state transformations. The optimal profiles to follow are directly those corresponding to output desired variables, therefore, estimation of states for nonmeasurable variables is considered by employing a neural networks method. The efficiency of the proposed controller is tested through several simulations, including process disturbances and operation under parametric uncertainty. The optimal controller parameters are selected through the Montecarlo Randomized Algorithm. In addition, proof of convergence to zero of tracking errors is analyzed and included in this article.

SUMMARYThis paper is a continuation of a previous work of authors, Scaglia et al. [G. J. E. Scaglia, L. M. Quintero, V. Mut and F. Di Sciascio, “Numerical methods based controller design for mobile robots,” Robotica27(2), 269–279 (2009)]. A method is presented to choose the controller parameters such that, the values of the control actions do not exceed the maximum allowable and the tracking errors tend to zero. In addition, the analysis of the controller design parameters is included. The experimental results (laboratory experiments and a real world application) demonstrate the efficiency of the controller.

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