We examine sample based Bayesian inference from impedance imaging data. We report experiments employing low level pixel based priors with mixed discrete and continuous conductivities. Sampling is carried out using MetropolisHastings Markov chain Monte Carlo, employing both large scale, Langevin updates, and state-adaptive local updates. Computing likelihood ratios of conductivity distributions ...

In this work we focus on solving quadratically constrained pseudoboolean optimization problems with quadratic objective as mixed integer linear programs. The standard mixed integer linear formulation of such problems is strengthened using valid inequalities derived from solving Reformulation-Linearization relaxation called partial DRL* relaxation. The proposed PDRL* relaxation features block-de...

In this paper we develop an intelligent controller on the basis of Genetic Algorithms for the stabilization of a class of Underactuated Mechanical Systems. First we develop a static State Feedback Controller with inner noncollocated partial feedback linearization loop to stabilize the nominal system. Second, we develop a Genetic algorithm controller to maintain system stabilization and to adapt...

We describe a technique for the stabilization of a 2R robot moving in the horizontal plane with a single actuator at the base, an interesting example of underactuated mechanical system that is not smoothly stabilizable. The proposed method is based on a recently introduced iterative steering paradigm, which prescribes the repeated application of an error contracting open-loop control law. In or...

In this paper, we address -tracking and -stabilization for a class of SE(2) autonomous vehicles with firstorder nonholonomic constrains. We introduce a class of transformations called near-identity diffeomorphisms that allow dynamic partial feedback linearization of the translational dynamics of this planar vehicle. This allows us to achieve global exponential -stabilization and -tracking (in p...

Backstepping control technique is a Lyapunov based nonlinear robust technique which is applicable to only strict feedback system. Backstepping technique has been applied on linear inverted pendulum which is under actuated system. Inverted pendulum is swung from its pendant position and stabilized at its upright position. Swing up is achieved by nonlinear backstepping controller but the linear i...

This paper presents neural network controller design for complex damage to a blended wing UAV (Unmanned Aerial Vehicle): partial loss of main wing and vertical tail. Longitudinal/lateral axis instability and the change of flight dynamics is investigated via numerical simulation. Based on this, neural network based adaptive controller combined with feedback linearization is designed in order to ...

Underactuated systems are those processing fewer actuators than degrees of freedom. But generally they are difficult to control. In this paper we realize crawling motion by an underactuated robot. By changing the location of the fixed point of the robot to the environment, the constraint of the system is changed. Local accessibility of the system with changing the constraints as a nonhoronomic ...

This paper deals with a control approach dedicated to stable limit cycle generation for underactuated mechanical systems. The proposed approach is based on partial nonlinear feedback linearization and dynamic control for optimal periodic reference trajectories tracking. The computation of the reference trajectories is performed in order to optimize the behavior of the whole dynamics of the syst...

Abstract Because linear programming algorithms are so efficient and in widespread use, together with the limitations of non-linear optimization solvers applied to large models, modelers faced wanting solve very models often attempt linearize terms their models. This chapter introduces various approaches for accomplishing this, using binary (0, 1) variables.