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Efficient nonlinear predictive control based on structured neural models

Maciej Ławryńczuk (2009)

International Journal of Applied Mathematics and Computer Science

This paper describes structured neural models and a computationally efficient (suboptimal) nonlinear Model Predictive Control (MPC) algorithm based on such models. The structured neural model has the ability to make future predictions of the process without being used recursively. Thanks to the nature of the model, the prediction error is not propagated. This is particularly important in the case of noise and underparameterisation. Structured models have much better long-range prediction accuracy...

Energy dissipation and hysteresis cycles in pre-sliding transients of kinetic friction

Michael Ruderman (2023)

Applications of Mathematics

The problem of transient hysteresis cycles induced by the pre-sliding kinetic friction is relevant for analyzing the system dynamics, e.g., of micro- and nano-positioning instruments and devices and their controlled operation. The associated energy dissipation and consequent convergence of the state trajectories occur due to the structural hysteresis damping of contact surface asperities during reversals, and it is neither exponential (i.e., viscous type) nor finite-time (i.e., Coulomb type). In...

Estimation of the output deviation norm for uncertain, discrete-time nonlinear systems in a state dependent form

Przemysław Orłowski (2007)

International Journal of Applied Mathematics and Computer Science

Numerical evaluation of the optimal nonlinear robust control requires estimating the impact of parameter uncertainties on the system output. The main goal of the paper is to propose a method for estimating the norm of an output trajectory deviation from the nominal trajectory for nonlinear uncertain, discrete-time systems. The measure of the deviation allows us to evaluate the robustness of any designed controller. The first part of the paper concerns uncertainty modelling for nonlinear systems...

Event-triggered optimal control of completely unknown nonlinear systems via identifier-critic learning

Zhinan Peng, Zhiquan Zhang, Rui Luo, Yiqun Kuang, Jiangping Hu, Hong Cheng, Bijoy Kumar Ghosh (2023)

Kybernetika

This paper proposes an online identifier-critic learning framework for event-triggered optimal control of completely unknown nonlinear systems. Unlike classical adaptive dynamic programming (ADP) methods with actor-critic neural networks (NNs), a filter-regression-based approach is developed to reconstruct the unknown system dynamics, and thus avoid the dependence on an accurate system model in the control design loop. Meanwhile, NN adaptive laws are designed for the parameter estimation by using...

Existence of different kind of solutions for discrete time equations

Denis Pennequin (2014)

Nonautonomous Dynamical Systems

The aim of this paper is to extend the classical linear condition concerning diagonal dominant bloc matrix to fully nonlinear equations. Even if assumptions are strong, we obtain an explicit condition which exactly extend the one known in linear case, and the setting allows also to consider bicontinuous operator instead of the schift and as particular case, we receive periodic or almost periodic solutions for discrete time equations.

Exponential stabilization of nonlinear driftless systems with robustness to unmodeled dynamics

Pascal Morin, Claude Samson (2010)

ESAIM: Control, Optimisation and Calculus of Variations

Exponential stabilization of nonlinear driftless affine control systems is addressed with the concern of achieving robustness with respect to imperfect knowledge of the system's control vector fields. In order to satisfy this robustness requirement, and inspired by Bennani and Rouchon [1] where the same issue was first addressed, we consider a control strategy which consists in applying periodically updated open-loop controls that are continuous with respect to state initial conditions. These...

Fault estimation for time-varying systems with Round-Robin protocol

Haijing Fu, Hongli Dong, Jinbo Song, Nan Hou, Gongfa Li (2020)

Kybernetika

This paper is concerned with the design problem of finite-horizon H fault estimator for a class of nonlinear time-varying systems with Round-Robin protocol scheduling. The faults are assumed to occur in a random way governed by a Bernoulli distributed white sequence. The communication between the sensor nodes and fault estimators is implemented via a shared network. In order to prevent the data from collisions, a Round-Robin protocol is utilized to orchestrate the transmission of sensor nodes. By...

Fault tolerant control of switched nonlinear systems with time delay under asynchronous switching

Zhengrong Xiang, Ronghao Wang, Qingwei Chen (2010)

International Journal of Applied Mathematics and Computer Science

This paper investigates the problem of fault tolerant control of a class of uncertain switched nonlinear systems with time delay under asynchronous switching. The systems under consideration suffer from delayed switchings of the controller. First, a fault tolerant controller is proposed to guarantee exponentially stability of the switched systems with time delay. The dwell time approach is utilized for stability analysis and controller design. Then the proposed approach is extended to take into...

Feedback linearization idle-speed control: design and experiments

Rolf Pfiffner, Lino Guzzella (1999)

Kybernetika

This paper proposes a novel nonlinear control algorithm for idle-speed control of a gasoline engine. This controller is based on the feedback linearization approach and extends this technique to the special structure and specifications of the idle-speed problem. Special static precompensations and cascaded loops are used to achieve the desired bandwidth separation between the fast spark and slow air-bypass action. A key element is the inclusion of the (engine-speed dependent) induction to power...

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