This paper deals with stabilization and optimal control of interconnected discrete-time nonlinear systems under given information constraints on the controller structure. As a prominent example, the considered information constraints on the controller structure include decentralized and distributed control over a given communication network. Firstly, we briefly recall the recently introduced no...

Recently, the passivity results for linear time-invariant systems were successfully extended to nonlinear and nonstationary systems, thus guaranteeing stability of adaptive control of nonlinear square systems. Based on this theoretical development, this paper presents the development of a new class of direct adaptive controllers, which employ a new decentralized adaptation law mechanism that is...

In this paper, we apply a Control Lyapunov Function methodology to design two families of cruise controllers for the two-dimensional movement autonomous vehicles on lane-free roads using bicycle kinematic model. The control functions are based measures energy system with kinetic expressed in ways similar Newtonian or relativistic mechanics. derived feedback laws (cruise controllers) decentraliz...

This paper deal with planar motion control of multiple underactuated Remotely Operated Vehicles (ROVs) based on merging of Fuzzy/Lyapunov and kinetic controllers. A cooperative algorithm based on a decentralized planning algorithm which considers the underwater vehicles in an initial open chain configuration is developed. All the planned trajectories are intersections-free, and each trajectory ...

Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying as needed the horizon length of Model Predictive Control (MPC). Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requi...

The nominal linear subsystem state-space model having nonlinear couplings are used in this work. The quadratic dissipativity constraint approach, previously introduced and developed for the model predictive control of interconnected systems, is deployed herein with a static state-feedback strategy. We re-use the derivation for a quadratic bound on the nonlinear coupling in a newly derived stabi...

tthe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. this paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. as a novelty, the proposed controller employs a simple gaussian radial-basis-function network as an uncertainty estimator. the proposed netw...

this paper proposes a hybrid control scheme for the synchronization of two chaotic duffing oscillator system, subject to uncertainties and external disturbances. the novelty of this scheme is that the linear quadratic regulation (lqr) control, sliding mode (sm) control and gaussian radial basis function neural network (grbfnn) control are combined to chaos synchronization with respect to extern...