This paper presents a theoretical model of stability and coordination of posture and locomotion, together with algorithms for continuous-time quadratic optimization of motion control. Explicit solutions to the Hamilton-Jacobi equation for optimal control of rigid-body motion are obtained by solving an algebraic matrix equation. The stability is investigated with Lyapunov function theory and it ...

In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...

A recently developed PLUS factorization holds great promise in image coding due to its simplicity and integer reversibility. However, existing PLUS factorizations did not consider stability and optimality. To address these problems, we propose methodologies to design stable and optimal PLUS factorization algorithms. Firstly, we propose three stable PLUS factorization algorithms, prove the stabi...

In this paper a linearly parameterized approximators based algorithm for identifying uncertain systems is proposed. The proposed algorithm ensures stability without previous knowledge of bounds for the “optimal” parameter, approximation error, and disturbances. This algorithm guarantees that the state error converges asymptotically to zero, even in the presence of uncertainties, as long as some...

one of methods of improvement of the material flow is cross docking that in is considered as a good method to reduce inventory and improve customer satisfaction. too, the vehicle routing problem is one of the important problems in distribution management and its goal is to find paths for delivering various cargos. therefore, this study was conducted in order to vehicle routing problem with cros...

It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated 0.d.e. This in turn implies convergence of the algorithm. Several specific classes of algorithms are considered as applications. It is found that the results provide (i) a simpler derivation of known results for reinforcement learning algorithms; (ii) ...