This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2 U+00B3 factorial experimental design for a fractional order proportional integral and derivative controller U+0028 FOPID U+0029, integer order proportional integral and derivative controller U+0028 IOPID U+0029 and the Skogestad internal model control controller U+0028 SIMC U+0029. The factors assumed in experiment are the presence of random noise, external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.

In this paper a dynamic simulation methodology of systems is presented by using ADAMS/MATLAB co-simulation. This methodology allows simulation, development and validation of different control strategiesfor robotic manipulator models in a fast way. It provides a first stage into the design of robotic prototypes for researchers and professionals. Finally, the methodology was validated by constructing a simulation model of a double pendulum and by implementing a PD type control strategy.

This paper presents the identification, control and robustness analysis for a robotic system of 1 degree of freedom using fractional and integer PID controllers. Initially, an ADAMS-MATLAB co-simulation model is built to simulate the dynamic model of robotic system. The identification of the dynamic model parameters of the system employs the recursive least-squares method. The controller design uses a linearized model of the robotic system obtained by the method of input-output linearization, and then, the fractional PID and integer PID controllers are designed based on it. The robustness of the PID controllers is analyzed in the frequency and the time domain. The robustness analysis in the frequency domain uses The Gang of Four (sensibility, complementary sensibility, sensibility of the plant and sensibility of the controller effort). The time domain analysis uses the ADAMS-MATLAB co-simulation model, considering external disturbances, noise in the feedback loop, parametric uncertainty and set-point variation, using as performance criteria ISE, average value and standard deviation of the control action. The tests are performed for positioning and tracking tasks. The obtained results show that the fractional PID controller has a better behavior in presence of external disturbances and lower energy consumption.

In this paper a visual servoing architecture based on a parallel robot for the tracking of faster moving objects with unknown trajectories is proposed. The control strategy is based on the prediction of the future position and velocity of the moving object. The synthesis of the predictive control law is based on the compensation of the delay introduced by the vision system. Demonstrating by experiments, the high-speed parallel robot system has good performance in the implementation of visual control strategies with high temporary requirements.