Adaptive Self-Regulation PID Control of Course-Keeping for Ships

2020 ◽  
Vol 27 (1) ◽  
pp. 39-45
Author(s):  
Qiang Zhang ◽  
Zhongyu Ding ◽  
Meijuan Zhang
Keyword(s):  
Pid Control ◽  
Direct Method ◽  
Self Regulation ◽  
Model Parameters ◽  
Control Problems ◽  
Time Varying ◽  
Lyapunov Direct Method ◽  
Environmental Disturbances ◽  
Nonlinear Control Problems ◽  
Control Scheme

AbstractTo solve the nonlinear control problems of the unknown time-varying environmental disturbances and parametric uncertainties for ship course-keeping control, this paper presents an adaptive self-regulation PID (APID) scheme which can ensure the boundedness of all signals in the ship course-keeping control system by using the Lyapunov direct method. Compared with the traditional PID control scheme, the APID control scheme not only is independent of the model parameters and the unknown input, but also can regulate the gain of PID adaptively and resist time-varying disturbances well. Simulation results illustrate the effectiveness and the robustness of the proposed control scheme.

PID PARAMETERS OPTIMIZATION USING PSO TECHNIQUE FOR NONLINEAR ELECTRO HYDRAULIC ACTUATOR

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Siti Marhainis Othman ◽  
Mohd Fua’ad Rahmat ◽  
Sahazati Md. Rozali ◽  
Sazilah Salleh
Keyword(s):  
Particle Swarm Optimization ◽  
Simulation Study ◽  
Pid Control ◽  
Parameters Optimization ◽  
Model Parameters ◽  
Time Varying ◽  
Proportional Integral Derivative ◽  
Hydraulic Actuator ◽  
Swarm Optimization ◽  
Control Scheme

Electro-hydraulic actuator (EHA) system inherently suffers from uncertainties, nonlinearities and time- varying in its model parameters which cause the modeling and controller designs are more complicated. Proportional Integral Derivative (PID) control scheme has been proposed and the main problem with its application is to tune the parameters to its optimum values. This study will look into an optimization of PID parameters using particle swarm optimization (PSO). Simulation study has been done in Matlab and Simulink. 

scholarly journals Stabilization of the FO-BLDCM Chaotic System in the Sense of Lyapunov

2015 ◽  
Vol 2015 ◽  
pp. 1-5
Author(s):  
Ping Zhou ◽  
Rongji Bai ◽  
Hao Cai
Keyword(s):  
Fractional Order ◽  
Chaotic System ◽  
Direct Method ◽  
Order System ◽  
Lyapunov Direct Method ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Dc Motors ◽  
System A ◽  
Control Scheme

Based on an integer-order Brushless DC motors (IO-BLDCM) system, we give a fractional-order Brushless DC motors (FO-BLDCM) system in this paper. There exists a chaotic attractor for fractional-order0.95<q≤1in the FO-BLDCM system. Furthermore, using the Lyapunov direct method for fractional-order system, a control scheme is proposed to stabilize the FO-BLDCM chaotic system in the sense of Lyapunov. Numerical simulation shows that the control scheme in this paper is valid for the FO-BLDCM chaotic system.

scholarly journals Neuro-PID Control for Electric Vehicle

2011 ◽  
Vol 15 (7) ◽  
pp. 846-853 ◽  
Author(s):  
Shigeru Omatu ◽  
◽  
Michifumi Yoshioka ◽  
Toru Fujinaka ◽  
◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Pid Control ◽  
Control Method ◽  
Torque Control ◽  
Learning Ability ◽  
Control Problems ◽  
Process Industries ◽  
The Neural Network ◽  
Control Scheme ◽  
Self Tuning

In this paper we consider the neuro-control method and its application to control problems of an electric vehicle. The neuro-control methods adopted here is based on Proportional-plus-Integral-plus-Derivative (PID) control, which has been adopted to solve process control or intelligent control problems. In Japan about eighty four percent of the process industries have used the PID control. After deriving the self-tuning PID control scheme (neuro-PID) using the learning ability of the neural network, we will show the control results by using the speed and torque control of an electric vehicle.

scholarly journals Asymptotic Stability of Distributed-Order Nonlinear Time-Varying Systems with the Prabhakar Fractional Derivatives

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
MohammadHossein Derakhshan ◽  
Azim Aminataei
Keyword(s):  
Asymptotic Stability ◽  
Fractional Derivatives ◽  
Direct Method ◽  
Time Varying ◽  
Lyapunov Direct Method ◽  
Fractional Differential Systems ◽  
Time Varying Systems ◽  
Fractional Differential ◽  
The Stability ◽  
Distributed Order

In this article, we survey the Lyapunov direct method for distributed-order nonlinear time-varying systems with the Prabhakar fractional derivatives. We provide various ways to determine the stability or asymptotic stability for these types of fractional differential systems. Some examples are applied to determine the stability of certain distributed-order systems.

Discrete-Time Adaptive Controller Based on Estimated Pseudopartial Derivative and Reaching Sliding Condition

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Chidentree Treesatayapun
Keyword(s):  
Discrete Time ◽  
Sliding Mode ◽  
Direct Method ◽  
Experimental System ◽  
Adaptive Controller ◽  
Current Control ◽  
Lyapunov Direct Method ◽  
Model Free ◽  
Control Scheme ◽  
Time Systems

An adaptive controller based on sliding mode condition is developed with estimated pseudopartial derivative (PPD) of data-driven scheme. The controlled plant is considered as a class of unknown discrete-time systems with only output feedback, which allows the proposed controller to be applicable for practical plants operated by computerization systems. The convergence of estimated PPD is analyzed by Lyapunov direct method under reasonable assumptions. The control law is derived by the estimated PPD and reaching condition of sliding surface as a model-free of controlled plant. The performance of the proposed control scheme is validated by theoretical analysis and experimental system with direct current (DC) motor current control.

scholarly journals Global dynamics of alcoholism epidemic model with distributed delays

2021 ◽  
Vol 18 (6) ◽  
pp. 8245-8256
Author(s):  
Salih Djillali ◽  
◽  
Soufiane Bentout ◽  
Tarik Mohammed Touaoula ◽  
Abdessamad Tridane ◽  
...  
Keyword(s):  
Epidemic Model ◽  
Direct Method ◽  
Distributed Delays ◽  
Positive Equilibrium ◽  
Model Parameters ◽  
Threshold Condition ◽  
Global Dynamics ◽  
Lyapunov Direct Method ◽  
Globally Asymptotically Stable ◽  
The Social

<abstract><p>This paper aims to investigate the global dynamics of an alcoholism epidemic model with distributed delays. The main feature of this model is that it includes the effect of the social pressure as a factor of drinking. As a result, our global stability is obtained without a "basic reproduction number" nor threshold condition. Hence, we prove that the alcohol addiction will be always uniformly persistent in the population. This means that the investigated model has only one positive equilibrium, and it is globally asymptotically stable independent on the model parameters. This result is shown by proving that the unique equilibrium is locally stable, and the global attraction is shown using Lyapunov direct method.</p></abstract>

Adaptive control of time-varying non-linear plants by speed-gradient algorithms

2019 ◽  
pp. 37-44 ◽  
Author(s):  
O. P. Tomchina ◽  
D. N. Polyakhov ◽  
O. I. Tokareva ◽  
A. L. Fradkov
Keyword(s):  
Adaptive Control ◽  
Adaptive Systems ◽  
Reference Model ◽  
Maximum Deviation ◽  
Model Parameters ◽  
Time Varying ◽  
System Solution ◽  
Non Linear ◽  
Initial Uncertainty ◽  
Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

scholarly journals Lie-Algebraic Approach for Pricing Zero-Coupon Bonds in Single-Factor Interest Rate Models

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
C. F. Lo
Keyword(s):  
Interest Rate ◽  
Algebraic Approach ◽  
Dynamical Symmetry ◽  
Bond Pricing ◽  
Model Parameters ◽  
Time Varying ◽  
Single Factor ◽  
Bond Price ◽  
Interest Rate Models ◽  
Root Model

The Lie-algebraic approach has been applied to solve the bond pricing problem in single-factor interest rate models. Four of the popular single-factor models, namely, the Vasicek model, Cox-Ingersoll-Ross model, double square-root model, and Ahn-Gao model, are investigated. By exploiting the dynamical symmetry of their bond pricing equations, analytical closed-form pricing formulae can be derived in a straightfoward manner. Time-varying model parameters could also be incorporated into the derivation of the bond price formulae, and this has the added advantage of allowing yield curves to be fitted. Furthermore, the Lie-algebraic approach can be easily extended to formulate new analytically tractable single-factor interest rate models.

scholarly journals Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4374
Author(s):  
Jose Bernardo Martinez ◽  
Hector M. Becerra ◽  
David Gomez-Gutierrez
Keyword(s):  
Obstacle Avoidance ◽  
Tracking Control ◽  
Global Coordinate System ◽  
Avoidance Task ◽  
Time Varying ◽  
Control Laws ◽  
Formation Tracking ◽  
Control Scheme ◽  
First Time ◽  
Hierarchical Scheme

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.

Models of a hybrid wheeled hopping self-balanced robot

2021 ◽  
pp. 095440622098419
Author(s):  
Qimin Li ◽  
Haibing Zeng ◽  
Long Bai ◽  
Zijian An
Keyword(s):  
Pid Control ◽  
Motion Pattern ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Swarm Optimization ◽  
Hopping Robot ◽  
Control Scheme ◽  
Hopping Robots ◽  
Hybrid Motion ◽  
Classical Control

Combining wheeled structure with hopping mechanism, this paper purposes a self-balanced hopping robot with hybrid motion pattern. The main actuator which is the cylindrical cam, optimized by particle swarm optimization (PSO), is equipped with the motor to control the hopping motion. Robotic system dynamics model is established and solved by Lagrangian method. After linearization, control characteristics of the system is obtained by classical control theory based on dynamics equations. By applying Adams and Matlab to simulate the system, hopping locomotion and self-balanced capability are validated respectively, and result shows that jump height can reach 750 mm theoretically. Then PID control scheme is developed and specific models of hardware and software are settled down accordingly. Finally, prototype is implemented and series of hopping experiments are conducted, showing that with different projectile angle, prototype can jump 550 mm in height and 460 mm in length, transcending majority of other existing hopping robots.

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