Nash and Stackelberg solutions to general linear-quadratic two player difference games. I. Open-loop and feedback strategies
National and ideological influence in the European Parliament
Nearly time optimal stabilizing patchy feedbacks
Necessary and sufficient conditions for stabilization of expanding systems servomechanism problems
The problem of designing realistic decentralized controller to solve a servomechanism problem in the framework of “large scale systems” is considered in this paper. As any large scale system is built by expanding construction of one subsystem being connected to the existing system. In particular, it is desired to find a local stabilizing controller in terms of a free parameter (belonging to the ring of proper stable transfer functions) so that desirable properties of the controlled system, such...
Necessary and sufficient Lyapunov-like conditions for robust nonlinear stabilization
In this work, we propose a methodology for the expression of necessary and sufficient Lyapunov-like conditions for the existence of stabilizing feedback laws. The methodology is an extension of the well-known Control Lyapunov Function (CLF) method and can be applied to very general nonlinear time-varying systems with disturbance and control inputs, including both finite and infinite-dimensional systems. The generality of the proposed methodology is also reflected upon by the fact that partial...
Necessary conditions for discrete dynamical systems with delays and general constraints
Necessary conditions for Lipschitz continuous discrete control problems
Necessary conditions of optimality for infinite dimensional uncertain systems.
Necessary Optimality Conditions for a Lotka-Volterra Three Species System
An optimal control problem is studied for a Lotka-Volterra system of three differential equations. It models an ecosystem of three species which coexist. The species are supposed to be separated from each others. Mathematically, this is modeled with the aid of two control variables. Some necessary conditions of optimality are found in order to maximize the total number of individuals at the end of a given time interval.
Necessary optimality conditions for a model of optimal control processes
Necessary optimality conditions for discrete systems with state-dependent control region
Některé funkční vlastnosti trajektorií geometrického místa kořenů
Některé otázky syntézy diskrétních regulačních obvodů s proměnnou strukturou
Neural network adaptive control for discrete-time nonlinear nonnegative dynamical systems.
Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system
This paper presents the design of a neural network based feedback linearization (NNFBL) controller for a two degree-offreedom (DOF), quarter-car, servo-hydraulic vehicle suspension system. The main objective of the direct adaptive NNFBL controller is to improve the system's ride comfort and handling quality. A feedforward, multi-layer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is developed using input-output data sets...
Neural network optimal control for nonlinear system based on zero-sum differential game
In this paper, for a class of the complex nonlinear system control problems, based on the two-person zero-sum game theory, combined with the idea of approximate dynamic programming(ADP), the constrained optimization control problem is solved for the nonlinear systems with unknown system functions and unknown time-varying disturbances. In order to obtain the approximate optimal solution of the zero-sum game, the multilayer neural network is used to fit the evaluation network, the execution network...
Neural network-based MRAC control of dynamic nonlinear systems
This paper presents direct model reference adaptive control for a class of nonlinear systems with unknown nonlinearities. The model following conditions are assured by using adaptive neural networks as the nonlinear state feedback controller. Both full state information and observer-based schemes are investigated. All the signals in the closed loop are guaranteed to be bounded and the system state is proven to converge to a small neighborhood of the reference model state. It is also shown that stability...
Neural network-based NARX models in non-linear adaptive control
The applicability of approximate NARX models of non-linear dynamic systems is discussed. The models are obtained by a new version of Fourier analysis-based neural network also described in the paper. This constitutes a reformulation of a known method in a recursive manner, i.e. adapted to account for incoming data on-line. The method allows us to obtain an approximate model of the non-linear system. The estimation of the influence of the modelling error on the discrepancy between the model and real...
Neurodynamic adaptive control systems
Neuro-Fuzzy Modeling in Bankruptcy Prediction