On the Stability of a Self-Tuning Controller in the Presence of Bounded Disturbances

1988 ◽  
Author(s):  
Gu Xingyuan ◽  
Wang Wei
Keyword(s):  
Self Tuning ◽  
Bounded Disturbances ◽  
The Stability

Tracking Accuracy Analysis of a Planar Flexible Manipulator With Lubricated Joint and Interval Uncertainty

2016 ◽  
Vol 11 (5) ◽  
Author(s):  
Dongyang Sun
Keyword(s):  
Interval Uncertainty ◽  
Flexible Manipulator ◽  
Accuracy Analysis ◽  
Tracking Accuracy ◽  
Element Discretization ◽  
Revolute Joint ◽  
Interval Analysis Method ◽  
Self Tuning ◽  
The Stability ◽  
Control Accuracy

A method for trajectory tracking accuracy analysis of a two-link flexible manipulator with lubricated revolute joint involving interval uncertainty is presented. In this method, first, fuzzy self-tuning proportion integration differentiation (PID) control is applied to track the desired tip trajectory of the manipulator. The absolute nodal coordinate formulation (ANCF) is employed for the finite element discretization of the flexible manipulator. And lubricated revolute joint is modeled based on the infinitely short journal bearing with Gümbel conditions. Second, uncertainty of clearance size is considered, and interval analysis method is applied. Numerical simulation is posted to investigate the cushioning effect of lubricants on the clearance and influence of uncertainty on control accuracy of the manipulator. The results show that the lubricants can improve the stability of motion and operation precision of the manipulator; however, uncertainty of the manipulator may reduce the control accuracy of the manipulator.

On Self-Tuning Control of Nonminimum Phase Discrete-Time Systems Using Approximate Inverse Systems

1993 ◽  
Vol 115 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Takashi Yahagi ◽  
Jianming Lu
Keyword(s):  
Discrete Time ◽  
Stochastic Systems ◽  
Output Data ◽  
Approximate Inverse ◽  
Nonminimum Phase ◽  
Discrete Time Systems ◽  
Inverse Systems ◽  
Self Tuning ◽  
The Stability ◽  
Time Systems

This paper presents a new method for self-tuning control of nonminimum phase discrete-time stochastic systems using approximate inverse systems obtained from the least-squares approximation. We show how unstable pole-zero cancellations can be avoided, and that this method has the advantage of being able to determine an approximate inverse system independently of the plant zeros. The proposed scheme uses only the available input and output data and the stability using approximate inverse systems is analyzed. Finally, the results of computer simulation are presented to show the effectiveness of the proposed method.

Fuzzy PID Control and Simulation of Wind Power Generation Yaw System

2014 ◽  
Vol 953-954 ◽  
pp. 353-356 ◽  
Author(s):  
Fan Yang ◽  
Tong Yang ◽  
Xiao Hong Yang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Time Performance ◽  
System A ◽  
Self Tuning ◽  
Simulation Results ◽  
The Stability

Aimed at the high inertia and non-linear characteristics of yaw system, a parameter self –tuning fuzzy PID controller is designed. The controller can adjust the PID parameters based on the wind direction variation, and make the turbines track the coming wind timely to obtain maximum power output. Simulation results show that the controller has good real-time performance and robustness compared with the traditional PID control. It can lower the fluctuation and overshoot, and improve the stability of the yaw system significantly.

A Unified Approach for Independent Manipulator Joint Acceleration Control and Observation

2003 ◽  
Author(s):  
ElSayed M. ElBeheiry ◽  
Ahmed S. Zaki ◽  
Waguih H. ElMaraghy
Keyword(s):  
Variable Structure ◽  
Small Time ◽  
Observer Design ◽  
Unified Approach ◽  
Variable Structure Systems ◽  
Procedural Approach ◽  
Structure State ◽  
Bounded Disturbances ◽  
The Stability ◽  
Joint Acceleration

The ultimate goal of a manipulator control design is to combine the design of both the controller and the observer into one procedural approach. Hence, the stability of the global system, namely, the manipulator dynamics, controller, and observer is guaranteed. This paper presents a new, unified approach in combining the control and observation problem for robotic manipulators. It links the design of an independent joint acceleration controller to the design of a variable structure state observer that is used to estimate the joint acceleration. Since both the joint acceleration controller and the observer introduced in this paper are likely to implement high gains to improve tracking, the effects of the time delay between the measurement of the output and the control loop response has been investigated. The observer design also considers the observation robustness against unknown but bounded disturbances using the theory of variable structure systems. A simulation study to investigate the performance of the joint acceleration controller and observer is conducted on a PUMA 560 robot. Simulation results showed that the proposed combination of observer and controller are robust to the change in the payload and small time delays.

scholarly journals Disturbance Attenuation and Rejection for a Class of Switched Nonlinear Systems Subject to Input and Sensor Saturations

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Yunliang Wei ◽  
Liping Sun ◽  
Shengsen Jia ◽  
Kunming Liu ◽  
Fanwei Meng
Keyword(s):  
Nonlinear Systems ◽  
Disturbance Attenuation ◽  
Switched Nonlinear Systems ◽  
Reduced Order ◽  
Closed Loop Systems ◽  
Augmented Systems ◽  
Bounded Disturbances ◽  
Effective Synthesis ◽  
System States ◽  
The Stability

This paper investigates the problem of disturbance attenuation and rejection for a class of switched nonlinear systems subject to input and sensor saturations, in which exosystem generated disturbances and H2-norm bounded disturbances are considered. The full-order and reduced-order observers are designed according to whether the system states are available or not. Based on the estimating values of the system states and exosystem generated disturbances, the design schemes for the composite controllers are put forward based on the full-order and reduced-order observers, respectively. For a switched system, the input and sensor saturations would influence the effective synthesis of observer and controller. By sector nonlinearity technology, the stability of the augmented closed-loop systems under the proposed composite controllers are analyzed, and the conditions of synthesis of the observers and controllers are further presented to ensure the augmented systems to be robustly asymptotically stable with a weighted H∞ performance level. An example is given to guarantee the effectiveness of the proposed control schemes.

Machine Learning Enabled Adaptive Optimization of a Transonic Compressor Rotor With Precompression

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Michael Joly ◽  
Soumalya Sarkar ◽  
Dhagash Mehta
Keyword(s):  
Machine Learning ◽  
Design Space Exploration ◽  
Surrogate Models ◽  
Processing Unit ◽  
Adaptive Optimization ◽  
Transonic Compressor ◽  
Central Processing ◽  
Compressor Rotor ◽  
Self Tuning ◽  
The Stability

In aerodynamic design, accurate and robust surrogate models are important to accelerate computationally expensive computational fluid dynamics (CFD)-based optimization. In this paper, a machine learning framework is presented to speed-up the design optimization of a highly loaded transonic compressor rotor. The approach is threefold: (1) dynamic selection and self-tuning among several surrogate models; (2) classification to anticipate failure of the performance evaluation; and (3) adaptive selection of new candidates to perform CFD evaluation for updating the surrogate, which facilitates design space exploration and reduces surrogate uncertainty. The framework is demonstrated with a multipoint optimization of the transonic NASA rotor 37, yielding increased compressor efficiency in less than 48 h on 100 central processing unit cores. The optimized rotor geometry features precompression that relocates and attenuates the shock, without the stability penalty or undesired reacceleration usually observed in the literature.

Self-Tuning Fuzzy Sliding Controller for the Ship Heading Problem

2010 ◽  
Author(s):  
Nassim Khaled ◽  
Nabil G. Chalhoub
Keyword(s):  
Fuzzy Logic Controller ◽  
Sliding Mode ◽  
Variable Structure ◽  
Guidance System ◽  
Tuning Parameter ◽  
Variable Structure Systems ◽  
Modeling Uncertainties ◽  
Self Tuning ◽  
The Stability ◽  
Yaw Angle

A self-tuning fuzzy-sliding mode controller is presented in the current work. It aims at combining the advantages of the variable structure systems (VSS) theory with the self-tuning fuzzy logic controller. Neither the development of an accurate dynamic model of the plant nor the construction of a rule-based expert system is required for designing the controller. The only requirement is that the upper bound of the modeling uncertainties has to be known. The stability of the controlled system is ensured by forcing the tuning parameter to satisfy the sliding condition. The controller is implemented to control the heading of an under-actuated ship. The simulation results demonstrate the robust performance of the controller in accurately tracking the desired yaw angle specified by the guidance system in the presence of considerable modeling imprecision and environmental disturbances.

Research on Single Neuron Adaptive PID Controller

2014 ◽  
Vol 651-653 ◽  
pp. 826-830 ◽  
Author(s):  
Xiu Jia Chen ◽  
Hong Di Qiu
Keyword(s):  
Pid Controller ◽  
Single Neuron ◽  
Control Effect ◽  
External Disturbances ◽  
Simulation Research ◽  
Process System ◽  
Self Tuning ◽  
The Stability ◽  
Actual Control ◽  
Controlled Object

The paper focuses on single neuron adaptive PID controller based on unsupervised Hebb algorithm, and simulation research on the controller is carried out for a second-order pure lag process system. Simulation results show that through learning and adjusting weights of single neuron adaptive PID controller, its online self-tuning ability can make timely adjustment of PID controller parameters according to controlled object changes and external disturbances in order to ensure that the stability and robustness of the system and, ultimately, more satisfactory actual control effect is obtained. At last, the control characteristics and parameter design rules are concluded.

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