Event-Triggered Adaptive Control

2015 ◽  
Author(s):  
Ali Albattat ◽  
Benjamin C. Gruenwald ◽  
Tansel Yucelen
Keyword(s):  
Adaptive Control ◽  
Lyapunov Stability ◽  
Data Exchange ◽  
Closed Loop ◽  
Closed Loop System ◽  
Control Approach ◽  
Event Triggering ◽  
Control Methodology ◽  
Tools And Methods ◽  
Event Triggered

In this paper, we present a new adaptive control methodology that allows a desirable command performance while the proposed controller exchanges data with the physical system through a real-time network. Specifically, we utilize tools and methods from event-triggering control theory to schedule data exchange dependent upon errors exceeding user-defined thresholds and show the boundedness of the overall closed-loop system using Lyapunov stability. An illustrative numerical example is provided to demonstrate the efficacy of the proposed adaptive control approach.

scholarly journals Distributed Fuzzy Adaptive Control for Heterogeneous Nonlinear Multiagent Systems with Similar Composite Structure

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yongqing Fan ◽  
Tiantian Xiao ◽  
Zhen Li
Keyword(s):  
Adaptive Control ◽  
Graph Theory ◽  
Multiagent Systems ◽  
Lyapunov Stability ◽  
Closed Loop ◽  
Zero Set ◽  
Closed Loop System ◽  
Fuzzy Adaptive Control ◽  
Different Dimensions ◽  
Fuzzy Adaptive

A distributed fuzzy adaptive control with similar parameters is constructed for a class of heterogeneous multiagent systems. Unlike many existing works, the dimensions of each multiagent dynamic system are considered to be nonidentical in this paper. Firstly, similar properties for different dimensions of multiagent systems are introduced, and some similar parameters among multiagent systems are also proposed. Secondly, a distributed fuzzy adaptive control on the basis of similar parameters is designed for the consensus of leader-follower multiagent systems. Following the graph theory and Lyapunov stability approach, it is concluded that UUB (uniformly ultimately bounded) of all signals in the closed-loop system can be guaranteed, and the consensus tacking error converges to a small compact zero set. Finally, a simulation example with different dimensions is provided to illustrate the effectiveness of the proposed method.

Logic-Based Switching Adaptive Control of DC-DC Buck Converter

2012 ◽  
Vol 229-231 ◽  
pp. 2209-2212
Author(s):  
Bao Bin Liu ◽  
Wei Zhou
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Buck Converter ◽  
Uncertain Parameters ◽  
Small Signal ◽  
Closed Loop System ◽  
Unknown Parameters ◽  
Signal Model ◽  
Small Signal Model ◽  
Control Scheme

Logic-based switching adaptive control scheme is proposed for the model of DC-DC buck converter in presence of uncertain parameters and power supply disturbance. All uncertain parameters and the disturbance are estimated together through constructing Lyapunov function. And a switching mechanism is used to ensure global asymptotic stability of the closed-loop system. The results of simulation show that even if there are multiple unknown parameters in the small-signal model, the control system of DC-DC buck converter can estimate unknown parameters quickly and accurately.

ADAPTIVE CONTROL OF UNCERTAIN LORENZ SYSTEM USING DECOUPLED BACKSTEPPING

2004 ◽  
Vol 14 (04) ◽  
pp. 1439-1445 ◽  
Author(s):  
S. S. GE
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Lorenz System ◽  
Physical Property ◽  
Asymptotic Convergence ◽  
Closed Loop System ◽  
Feedback Form ◽  
Controlling Chaos ◽  
Simulation Results ◽  
The Lorenz System

In this letter, we reconsider the problem of controlling chaos in the well-known Lorenz system. Firstly, the difficulty in controlling the Lorenz system is discussed in the general strict-feedback form. Then, singularity-free adaptive control is presented for the Lorenz system with three key parameters unknown by exploiting the physical property of the system using decoupled backstepping design. The proposed controller guarantees the asymptotic convergence of the output and the boundedness of all the signals in the closed-loop system. Simulation results are conducted to show the effectiveness of the approach.

scholarly journals Adaptive Stabilization Control for a Class of Complex Nonlinear Systems Based on T-S Fuzzy Bilinear Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jinsheng Xing ◽  
Naizheng Shi
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Complex Systems ◽  
Closed Loop ◽  
Loop System ◽  
Asymptotically Stable ◽  
Bilinear Model ◽  
Closed Loop System ◽  
Fuzzy Modelling ◽  
Control Scheme

This paper proposes a stable adaptive fuzzy control scheme for a class of nonlinear systems with multiple inputs. The multiple inputs T-S fuzzy bilinear model is established to represent the unknown complex systems. A parallel distributed compensation (PDC) method is utilized to design the fuzzy controller without considering the error due to fuzzy modelling and the sufficient conditions of the closed-loop system stability with respect to decay rateαare derived by linear matrix inequalities (LMIs). Then the errors caused by fuzzy modelling are considered and the method of adaptive control is used to reduce the effect of the modelling errors, and dynamic performance of the closed-loop system is improved. By Lyapunov stability criterion, the resulting closed-loop system is proved to be asymptotically stable. The main contribution is to deal with the differences between the T-S fuzzy bilinear model and the real system; a global asymptotically stable adaptive control scheme is presented for real complex systems. Finally, illustrative examples are provided to demonstrate the effectiveness of the results proposed in this paper.

scholarly journals Adaptive Robust Quadratic Stabilization Tracking Control for Robotic System with Uncertainties and External Disturbances

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jinzhu Peng ◽  
Yan Liu
Keyword(s):  
Closed Loop ◽  
Robot Manipulator ◽  
Variable Structure ◽  
Robotic System ◽  
Loop System ◽  
Closed Loop System ◽  
Hybrid Scheme ◽  
External Disturbances ◽  
Control Approach ◽  
Quadratic Stabilization

An adaptive robust quadratic stabilization tracking controller with hybrid scheme is proposed for robotic system with uncertainties and external disturbances. The hybrid scheme combines computed torque controller (CTC) with an adaptive robust compensator, in which variable structure control (VSC) andH∞optimal control approaches are adopted. The uncertain robot manipulator is mainly controlled by CTC, the VSC is used to eliminate the effect of the uncertainties and ensure global stability, andH∞approach is designed to achieve a certain tracking performance of closed-loop system. A quadratic stability approach, which allows separate treatment of parametric uncertainties, is used to reduce the conservatism of the conventional robust control approach. It can be also guaranteed that all signals in closed-loop system are bounded. The validity of the proposed control scheme is shown by computer simulation of a two-link robotic manipulator.

scholarly journals Fractional-Order Sliding Mode Control of Overhead Cranes   

2020 ◽  
Vol 31 (1) ◽  
pp. 68-76
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Control Structure ◽  
Adaptive System ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Closed Loop System ◽  
Control Approach ◽  
Mode Control

We constitute a control system for overhead crane with simultaneous motion of trolley and payload hoist to destinations and suppression of payload swing. Controller core made by sliding mode control (SMC) assures the robustness. This control structure is inflexible since using fixed gains. For overcoming this weakness, we integrate variable fractional-order derivative into SMC that leads to an adaptive system with adjustable parameters. We use Mittag–Leffler stability, an enhanced version of Lyapunov theory, to analyze the convergence of closed-loop system. Applying the controller to a practical crane shows the efficiency of proposed control approach. The controller works well and keeps the output responses consistent despite the large variation of crane parameters.

Event-triggered Hꝏ control for NCS with time-delay and packet losses

2019 ◽  
Vol 37 (3) ◽  
pp. 918-934
Author(s):  
Jing Bai ◽  
Ying Wang ◽  
Li-Ying Zhao
Keyword(s):  
Time Delay ◽  
Closed Loop ◽  
Discrete Event ◽  
Sufficient Conditions ◽  
Loop System ◽  
Linear Matrix ◽  
Time Varying ◽  
Closed Loop System ◽  
Packet Losses ◽  
Event Triggered

Abstract This paper is concerned with the discrete event-triggered dynamic output-feedback ${H}_{\infty }$ control problem for the uncertain networked control system, where the time-varying sampling, network-induced delay and packet losses are taken into account simultaneously. The random packet losses are described via the Bernoulli distribution. And then, the closed-loop system is modelled as an augmented time-delay system with interval time-varying delay. By using the Lyapunov stability theory and the augmented state space method, the sufficient conditions for the asymptotic stability of the closed-loop system are proposed in the form of linear matrix inequalities. At the same time, the design method of the ${H}_{\infty }$ controller is created. Finally, a numerical example is employed to illustrate the effectiveness of the proposed method.

Robust Integral of NN and Error Sign Control for Nanomanipulation Using AFM

2012 ◽  
Vol 2 (2) ◽  
pp. 78-90
Author(s):  
Qinmin Yang ◽  
Jiangang Lu
Keyword(s):  
Closed Loop ◽  
Nano Particles ◽  
Feedback Signal ◽  
Error Feedback ◽  
Simulation Environment ◽  
Closed Loop System ◽  
Roughness Effect ◽  
Atomic Force ◽  
Applied Forces ◽  
Control Methodology

This paper presents a novel control methodology for automatically manipulating nano particles on the substrate by using Atomic Force Microscope (AFM). The interactive forces and dynamics between the tip, particle and substrate are modeled and analyzed including the roughness effect of the substrate. Further, the control signal is designed to consist of the robust integral of a neural network (NN) output plus the sign of the error feedback signal multiplied with an adaptive gain. Using the NN-based adaptive force controller, the task of pushing nano particles is demonstrated in simulation environment. Finally, the asymptotical tracking performance of the closed-loop system, boundedness of the NN weight estimates and applied forces are shown by using the Lyapunov-based stability analysis.

Sign in / Sign up

Export Citation Format

Share Document