This paper develops a novel probabilistic framework for stochastic nonlinear and uncertain control problems. The proposed exploits the Kullback–Leibler divergence to measure between distribution of closed-loop behavior dynamical system predefined ideal distribution. To facilitate derivation analytic solution randomized controllers systems, transformation methods are applied such that dynamics c...

in recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...

This paper treats the question of output trajectory tracking in nonlinear systems in the presence of uncertainty. It is assumed that the nominal system is decouplable using state variable feedback. An adaptive control law is derived such that in the closed-loop system, output vector asymptotically converges to the given reference trajectory. The controller includes a dynamic system in the feedb...

introduction this paper proposes the concept of autonomous drug-encapsulated nanoparticle (adenp) as a novel non-invasive approach to prevent atherosclerosis. adenp consists of three simple units of sensor, controller (computing), and actuator. the hardware complexity of adenp is much lower than most of the nanorobots, while the performance is maintained by the synergism in the swarm architectu...