This Thesis presents an optimal framework with dynamic perceptibility and chaos compensation for the control of robot manipulators. The fundamental objective of this framework is to obtain a variety of control laws for implementing dynamic visual servoing systems. In addition, this Thesis presents different contributions like the concept of dynamic perceptibility that is used to avoid image and robot singularities, the framework itself, that implements a delayed feedback controller for chaos compensation, and the extension of the framework for space robotic systems. Most of the image-based visual servoing systems implemented to date are indirect visual controllers in which the control action is joint or end-effector velocities to be applied to the robot in order to achieve a given desired location with respect to an observed object. The direct control of the motors for each joint of the robot is performed by the internal controller of the robot, which translates these velocities into joint torques. This Thesis mainly addresses the direct image-based visual servoing systems for trajectory tracking. In this case, in order to follow a given trajectory previously specified in the image space, the control action is defined as a vector of joint torques. The framework detailed in the Thesis allows for obtaining different kind of control laws for direct image-based visual servoing systems. It also integrates the dynamic perceptibility concept into the framework for avoiding image and robot singularities. Furthermore, a delayed feedback controller is also integrated so the chaotic behavior of redundant systems is compensated and thus, obtaining a smoother and efficient movement of the system. As an extension of the framework, the dynamics of free-based space systems is considered when determining the control laws, being able to determine trajectories for systems that do not have the base attached to anything. All these different steps are described throughout the Thesis. This Thesis describes in detail all the calculations for developing the visual servoing framework and the integration of the described optimization techniques. Simulation and experimental results are shown for each step, developing the controllers in an FPGA for further optimization, since this architecture allows to reduce latency and can be easily adapted for controlling of any joint robot by simply modifying certain modules that are hardware dependents. This architecture is modular and can be adapted to possible changes that may occur as a consequence of the incorporation or modification of a control driver, or even changes in the configuration of the data acquisition system or its control. This implementation, however, is not a contribution of this Thesis, but is necessary to briefly describe the architecture to understand the framework’s potential. These are the main objectives of the Thesis, and two robots where used for experimental results. A commercial industrial seven-degrees-of-freedom robot: Mitsubishi PA10, and another three-degrees-of-freedom robot. This last one’s design and implementation has been developed in the research group where the Thesis is written.