This paper discusses the maneuvering control algorithm based on all-wheel independent driving and steering control techniques for special purpose 6WD/WS vehicles. The maneuvering control algorithms considering superior dynamic characteristics of high power in-wheel motors and independent steering system are designed to perform driving and steering control, vehicle stability control, and fault t...

The MCA (Motion Cueing Algorithm) for driving simulator takes into account the simulator’s workspace limits and the driver’s motion perception thresholds to reproduce simulated vehicle’s accelerations. For the motion based driving simulators, the most applied MCAs are the classical and the optimal filters. This paper presents a new algorithm, called MPC (Model Predictive Control) explicit algor...

We study the problem of manipulation of the men-proposing Gale-Shapley algorithm by a single woman via permutation of her true preference list. Our contribution is threefold: First, we show that the matching induced by an optimal manipulation is stable with respect to the true preferences. Second, we identify a class of optimal manipulations called inconspicuous manipulations which, in addition...

RNA locally optimal secondary structures provide a concise and exhaustive description of all possible secondary structures of a given RNA sequence, and hence a very good representation of the RNA folding space. In this paper, we present an efficient algorithm that computes all locally optimal secondary structures for any folding model that takes into account the stability of helical regions. Th...

This paper presents a hybrid particle swarm optimization algorithm (HPSO) as a modern optimization tool to solve the optimal power flow (OPF) problem. The objective functions considered are the system real power losses, fuel cost, voltage deviation and voltage stability index. The proposed algorithm makes use of the PSO, known for its global searching capabilities, to allocate the optimal contr...

In this paper we first describe the stochastic optimal control algorithm called ((OPTCON)). The algorithm minimizes an intertemporal objective loss function subject to a nonlinear dynamic system in order to achieve optimal value of control (or instrument) variables. Second as an application, we implemented the algorithm by the statistical programming system ((GAUSS)) to determine the optimal fi...

This paper deals with the application of Iterative Learning Control (ILC) to further improve the performance of teleoperation systems based on Smith predictor. The goal is to achieve robust stability and optimal transparency for these systems. The proposed control structure make the slave manipulator follow the master in spite of uncertainties in time delay in communication channel and model pa...