National and ideological influence in the European Parliament
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...
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...
Nonlinear analysis of vehicle control actuations based on controlled invariant sets
In the paper, an analysis method is applied to the lateral stabilization problem of vehicle systems. The aim is to find the largest state-space region in which the lateral stability of the vehicle can be guaranteed by the peak-bounded control input. In the analysis, the nonlinear polynomial sum-of-squares programming method is applied. A practical computation technique is developed to calculate the maximum controlled invariant set of the system. The method calculates the maximum controlled invariant...
Nonlinear control for a diesel engine: A CLF-based approach
Nonlinear control of a planar multiaxis servohydraulic test facility using exact linearization techniques
Nonlinear model predictive control of a boiler unit: A fault tolerant control study
This paper deals with a nonlinear model predictive control designed for a boiler unit. The predictive controller is realized by means of a recurrent neural network which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law is derived solving an optimization problem. Fault tolerant properties of the proposed control system are also investigated. A set of eight faulty scenarios is prepared to verify the quality of the fault tolerant control. Based of different faulty...
Numerical stability analysis in respiratory control system models.