The hierarchical control decomposition provided by inverse kinematics is seldom used in the field of Computer Animation. In this chapter we first review the properties and limitations of inverse kinematics compared to other techniques dedicated to the motion control of complex articulated figures. Then, beyond the sole pseudo-inverse solution, we examine the homogeneous solution allowing the pa...

Nonlinear inverse dynamic models can be utilized in various parts of advanced model-based control system design: reference trajectory optimization, feedforward control and feedback linearization [35]. In this paper, a new synthesis approach for nonlinear inverse dynamic models of satellites with flexible structures is presented. For satellite configurations with unstable zero dynamics, a stable...

We present a new framework for prioritized multi-task motion/force control of fully-actuated robots. This work is established on a careful review and comparison of the state of the art. Some control frameworks are not optimal, that is they do not find the optimal solution for the secondary tasks. Other frameworks are optimal, but they tackle the control problem at kinematic level, hence they ne...

Inverse optimization is the problem of determining the values of missing input parameters that are closest to given estimates and that will make a given target solution optimal. This study is concerned with inverse mixed integer linear optimization problems (MILPs) in which the missing parameters are objective function coefficients. This class generalizes the class studied by Ahuja and Orlin [2...

In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large ...

An adjoint based functional optimization technique in conjunction with the spectral stochastic finite element method is proposed for the solution of an inverse heat conduction problem in the presence of uncertainties in material data, process conditions and measurement noise. The ill-posed stochastic inverse problem is restated as a conditionally well-posed L2 optimization problem. The gradient...

We present neural inverse space mapping (NISM) optimization for electromagnetics-based design of microwave structures. The inverse of the mapping from the fine to the coarse model parameter spaces is exploited for the first time in a space mapping algorithm. NISM optimization does not require up-front EM simulations, multipoint parameter extraction, or frequency mapping. It employs a simple sta...