Sliding Mode Control (SMC) is one of the robust and nonlinear methods which have several advantages such as robustness against matched external disturbances and parameter uncertainties.
Even if digital watermarks can be categorized based on several properties, such as robustness, security, complexity, and invertibility [1], a common taxonomy is to distinguish between robust and fragile watermarks.
It suits requirements such as robustness to the movement of a target or non-Gaussian noise.
Real life scenarios often present critical challenges for autonomous vision-based localization, such as robustness to viewpoint and appearance changes.
Aspects such as robustness, precision, usability of the measured data, acceptation criteria and ergonomic aspects have been assessed.
Concepts from engineering such as robustness and modularity are indeed becoming a regular way of describing biological systems.
Simulation results illustrate that the closed-loop system has desired properties such as robustness and chattering elimination.
Numerical results demonstrated some advantages of the proposed method over the C-V method, such as robustness to the locations of initial contour and the high computation efficiency.
In order to keep our exposition simple, other issues such as robustness to distortions or to desynchronization are not considered in this analysis.
For these applications, several performance criteria can be defined, such as robustness, responsiveness, consumption, size, scalability, compatibility with human beings, accuracy, or precision.
For the optimal watermarking application trade-offs among competing criteria such as robustness, non-perceptibility, capacity, non-detectability, and security have to be considered.
