scholarly journals Disturbance-Improved Model-Free Adaptive Prediction Control for Discrete-Time Nonlinear Systems with Time Delay

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2128
Author(s):  
Honghai Ji ◽  
Yuzhou Wei ◽  
Lingling Fan ◽  
Shida Liu ◽  
Yulin Wang ◽  
...  
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Attenuation Factor ◽  
Smith Predictor ◽  
Controlled System ◽  
Model Free ◽  
Adaptive Prediction ◽  
The One ◽  
Improved Model ◽  
Prediction Control

This study proposes a Disturbance-improved Model-free Adaptive Prediction Control (DMFAPC) algorithm for a discrete-time nonlinear system with time delay and disturbance. The algorithm is shown to have good robustness. On the one hand, the Smith predictor is used to predict the output at a future time to eliminate the time delay in the system; on the other hand, an attenuation factor is introduced at the input to effectively eliminate the measurement disturbance. The proposed algorithm is a data-driven control algorithm that does not require the model information of the controlled system; it only requires the input and output data. The convergence of the DMFAPC is analyzed. Simulation results confirm the effectiveness of this algorithm.

Data-driven model-free sliding mode learning control for a class of discrete-time nonlinear systems

2020 ◽  
Vol 42 (13) ◽  
pp. 2533-2547
Author(s):  
Lei Cao ◽  
Shouli Gao ◽  
Dongya Zhao
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Sliding Mode ◽  
Learning Control ◽  
Linearization Method ◽  
Data Driven ◽  
Controlled System ◽  
Model Free ◽  
The Mathematical Model

This paper proposes a data-driven model-free sliding mode learning control (MFSMLC) for a class of discrete-time nonlinear systems. In this scheme, the control design does not depend on the mathematical model of the controlled system. The nonlinear system can be transformed into a dynamic linear data system by a novel dynamic linearization method. A recursive learning control algorithm is designed for the nonlinear system that can drive the sliding variable reach and remain on the sliding surface only by using output and input data. Moreover, the chattering is reduced because there is no non-smooth term in MFSMLC. After the strict stability analysis, the effectiveness of MFSMLC is validated by MATLAB simulations.

Method of first integrals and interface, surface waves

2010 ◽  
Vol 32 (2) ◽  
pp. 107-120
Author(s):  
Pham Chi Vinh ◽  
Trinh Thi Thanh Hue ◽  
Dinh Van Quang ◽  
Nguyen Thi Khanh Linh ◽  
Nguyen Thi Nam
Keyword(s):  
Rayleigh Waves ◽  
Displacement Vector ◽  
Attenuation Factor ◽  
Electrical Potential ◽  
Polarization Vector ◽  
First Integrals ◽  
Dispersion Equations ◽  
Interface Surface ◽  
Electric Induction ◽  
The One

The method of first integrals (MFI) based on the equation of motion for the displacement vector, or  based on the one for the traction vector was introduced  recently in order to find explicit secular equations of Rayleigh waves whose characteristic equations (i.e the equations determining the attenuation factor) are fully quartic or are of higher order (then the classical approach is not applicable). In this paper it is shown that, not only to Rayleigh waves,  the MFI can be applicable also to other waves by running it on the equations for mixed vectors. In particular: (i) By applying the MFI  to the equations for the displacement-traction vector we get the explicit dispersion equations of Stoneley waves in twinned crystals (ii)  Running the MFI on the equations for the traction-electric induction vector and the traction-electrical potential vector provides the explicit dispersion equations of SH-waves in piezoelastic materials. The obtained dispersion equations are identical with the ones previously derived using the method of polarization vector, but the procedure of driving them is more simple.

scholarly journals Construction of continuous abstractions for discrete-time time-delay systems

2020 ◽  
Author(s):  
Mobin Shahamat ◽  
Javad Askari ◽  
Abdalla Swikir ◽  
Navid Noroozi ◽  
Majid Zamani
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Delay Systems ◽  
Time Delay Systems

scholarly journals Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm

2021 ◽  
Author(s):  
Hossein Nejatbakhsh Esfahani ◽  
Rafal Szlapczynski
Keyword(s):  
Dynamic Programming ◽  
Time Delay ◽  
Control Algorithm ◽  
Approximate Dynamic Programming ◽  
Robust Adaptive Control ◽  
Stochastic Disturbances ◽  
Time Delay Control ◽  
Model Free ◽  
Delay Control ◽  
Robust Adaptive

AbstractThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control algorithm. Based on this integration, Actor-Critic Time-Delay Control (AC-TDC) is proposed. It offers a high-performance robust-adaptive control approach for path following of autonomous ships under deterministic and stochastic disturbances induced by the winds, waves, and ocean currents. Computer simulations have been conducted under two different conditions in terms of the deterministic and stochastic disturbances and all simulation results indicate an acceptable performance in tracking of paths for the proposed control algorithm in comparison with the conventional TDC approach.

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