Position Control of a 2D Nonlinear Gantry Crane System Using Model Predictive Controller

2015 ◽  
Vol 735 ◽  
pp. 282-288
Author(s):  
Najib K. Dankadai ◽  
Ahmad Athif Mohd Faudzi ◽  
Amir Bature ◽  
Suleiman Babani ◽  
Muhammad I. Faruk
Keyword(s):  
Closed Loop ◽  
Position Control ◽  
Lagrange Equation ◽  
Input Voltage ◽  
Gantry Crane ◽  
Closed Loop System ◽  
Model Predictive Controller ◽  
Loop Control ◽  
Predictive Controller ◽  
Payload Mass

This paper presents the application of model predictive controller for controlling a nonlinear 2D gantry crane system with a DC motor as an actuator. The gantry crane system (GCS) dynamics is derived using Lagrange equation method. A model predictive controller is designed based on the linearised GCS and prediction cost function to ensure accurate positioning and oscillation reduction. Simulation via MATLAB and Simulink was performed to investigate the performance of the model predictive controller on the GCS. The controller test was done under several elements altering the behaviour of the system. The closed loop system was analysed considering different cable length, payload mass and trolley position. It was found that the closed loop control meets the main goal of this work, trolley positioning as fast as possible with minimum payload swinging all within a robust input voltage.

An Infinite Model Predictive Controller for Multi Input Nonlinear Processes

2017 ◽  
Author(s):  
Ma’moun Abu-Ayyad ◽  
Abdelkader Abdessameud ◽  
Issam Abu-Mahfouz
Keyword(s):  
Closed Loop ◽  
Nonlinear Functions ◽  
Model Predictive Controller ◽  
Nonlinear Characteristics ◽  
Loop Control ◽  
Dynamic Matrix ◽  
New Strategy ◽  
Predictive Controller ◽  
Process Gain ◽  
Infinite Model

This paper presents a novel algorithm of an infinite model predictive controller for controlling nonlinear multi-input multi-output (MIMO) processes. The new strategy uses a set of continuous nonlinear functions that captures the nonlinear characteristics of the MIMO plant over a wide operating range resulting in a more accurate prediction of the controlled variables. The method formulates a nonlinear dynamic matrix that is manipulated variable dependent during closed-loop control. The proposed algorithm was implemented on a nonlinear MIMO thermal system comprising of three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. The MIMO process has nonlinear parameters such as process gain and time constant that are dependent on the size of the control actions. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.

scholarly journals Modeling and energy-based sway reduction control for tower crane systems with double-pendulum and spherical-pendulum effects

2019 ◽  
Vol 53 (1-2) ◽  
pp. 141-150 ◽  
Author(s):  
Menghua Zhang ◽  
Yongfeng Zhang ◽  
Bing Ji ◽  
Changhui Ma ◽  
Xingong Cheng
Keyword(s):  
Closed Loop ◽  
Double Pendulum ◽  
Control Methods ◽  
Spherical Pendulum ◽  
Closed Loop System ◽  
Tower Crane ◽  
Lyapunov Techniques ◽  
Payload Mass ◽  
System States ◽  
Invariance Theorem

As typical underactuated systems, tower crane systems present complicated nonlinear dynamics. For simplicity, the payload swing is traditionally modeled as a single-pendulum in existing works. Actually, when the hook mass is close to the payload mass, or the size of the payload is large, a tower crane may exhibit double-pendulum effects. In addition, existing control methods assume that the hook and the payload only swing in a plane. To tackle the aforementioned practical problems, we establish the dynamical model of the tower cranes with double-pendulum and spherical-pendulum effects. Then, on this basis, an energy-based controller is designed and analyzed using the established dynamic model. To further obtain rapid hook and payload swing suppression and elimination, the swing part is introduced to the energy-based controller. Lyapunov techniques and LaSalle’s invariance theorem are provided to demonstrate the asymptotic stability of the closed-loop system and the convergence of the system states. Simulation results are illustrated to verify the correctness and effectiveness of the designed controller.

scholarly journals Consistency of Control Performance in 3D Overhead Cranes under Payload Mass Uncertainty

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 657 ◽  
Author(s):  
Uyen Tu Thi Hoang ◽  
Hai Xuan Le ◽  
Nguyen Huu Thai ◽  
Hung Van Pham ◽  
Linh Nguyen
Keyword(s):  
Closed Loop ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Control Technique ◽  
Control Performance ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Mass Uncertainty ◽  
Payload Mass

The paper addresses the problem of effectively and robustly controlling a 3D overhead crane under the payload mass uncertainty, where the control performance is shown to be consistent. It is proposed to employ the sliding mode control technique to design the closed-loop controller due to its robustness, regardless of the uncertainties and nonlinearities of the under-actuated crane system. The radial basis function neural network has been exploited to construct an adaptive mechanism for estimating the unknown dynamics. More importantly, the adaptation methods have been derived from the Lyapunov theory to not only guarantee stability of the closed-loop control system, but also approximate the unknown and uncertain payload mass and weight matrix, which maintains the consistency of the control performance, although the cargo mass can be varied. Furthermore, the results obtained by implementing the proposed algorithm in the simulations show the effectiveness of the proposed approach and the consistency of the control performance, although the payload mass is uncertain.

Closed-loop system disturbance recovery

2003 ◽  
Vol 217 (6) ◽  
pp. 631-649 ◽  
Author(s):  
R Whalley ◽  
M Ebrahimi
Keyword(s):  
Closed Loop ◽  
Low Frequency ◽  
Closed Loop Control ◽  
Multivariable System ◽  
Closed Loop System ◽  
Outer Loop ◽  
Loop Control ◽  
Passive Network ◽  
Loop Tuning ◽  
Reference Input

The regulation of linearized multivariable system models, following input set point and load disturbance changes, is considered. An inner and outer closed-loop control strategy is outlined, enabling targeted recovery rates, offset attenuation and low steady state interaction to be achieved. Proportional control and passive network compensation alone are employed. Gain ratio selection and outer loop tuning are exercised, ensuring thereby the confinement of output perturbations to low-frequency load disturbances and reference input changes. Application studies are presented for purposes of comparison.

The Study of Closed-Loop Position Control System Based on CNC Processing

2014 ◽  
Vol 941-944 ◽  
pp. 2243-2246
Author(s):  
Xin Zhou
Keyword(s):  
Control System ◽  
Machine Tools ◽  
Closed Loop ◽  
Position Control ◽  
Machining Accuracy ◽  
Closed Loop Control ◽  
Loop Control ◽  
Nc Machine ◽  
Nc Machine Tools ◽  
Position Control System

In view of the existing problems of indirect position closed-loop control, a digitized closed-loop control method is presented and a new kind of position control system with fully digitized closed-loop based on that method is developed. In this way, the fully digitized control of cutter trajectory is implemented with the features of digitized driving, digitized measuring and digitized position control, so that the machining accuracy of the NC machine tools is effectively assured. This system has been used on varieties of NC machine tools and very good results have been obtained in the machining of complex precision parts.

scholarly journals Conventional and Fuzzy Force Control in Robotised Machining

2013 ◽  
Vol 210 ◽  
pp. 178-185 ◽  
Author(s):  
Zenon Hendzel ◽  
Andrzej Burghardt ◽  
Piotr Gierlak ◽  
Marcin Szuster
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Force Control ◽  
Closed Loop ◽  
Position Control ◽  
Control Strategies ◽  
Closed Loop System ◽  
Fuzzy Logic Systems ◽  
Complex Control System ◽  
Artificial Neural

This article presents an application of the hybrid position-force control of the robotic manipulator with use of artificial neural networks and fuzzy logic systems in complex control system. The mathematical description of the manipulator and a closed-loop system are presented. In the position control were used the PD controller and artificial neural networks, which compensate nonlinearities of the manipulator. The paper presents mainly the application of various strategies of the force control. The force control strategies using conventional controllers P, PI, PD, PID and fuzzy controllers are presented and discussed. All of the control methods were verified on the real object in order to make a comparison of a control quality.

The variable, fractional-order discrete-time PD controller in the IISv1.3 robot arm control

Open Physics ◽  
2013 ◽  
Vol 11 (6) ◽  
Author(s):  
Piotr Ostalczyk ◽  
Dariusz Brzezinski ◽  
Piotr Duch ◽  
Maciej Łaski ◽  
Dominik Sankowski
Keyword(s):  
Fractional Order ◽  
Discrete Time ◽  
Output Signal ◽  
Closed Loop ◽  
Loop System ◽  
Robot Arm ◽  
Pd Controller ◽  
Closed Loop System ◽  
Loop Control ◽  
Robot Arm Control

AbstractIn this paper, the discrete differentiation order functions of the variable, fractional-order PD controller (VFOPD) are considered. In the proposed VFOPD controller, a variable, fractional-order backward difference is applied to perform closed-loop, system error, discrete-time differentiation. The controller orders functions which may be related to the controller input or output signal or an input and output signal. An example of the VFOPD controller is applied to the robot arm closed-loop control due to system changes in moment of inertia. The close-loop system step responses are presented.

Qualitative Robustness and Its Role in the Robust Control of Uncertain Engineering Systems

2011 ◽  
Author(s):  
Nagini Devarakonda ◽  
Rama K. Yedavalli
Keyword(s):  
Control Systems ◽  
Uncertain Systems ◽  
Closed Loop ◽  
Quantitative Information ◽  
Engineering Systems ◽  
Closed Loop System ◽  
Qualitative Information ◽  
Loop Control ◽  
Qualitative Robustness ◽  
Ecological Principles

This paper addresses the issue of robustness of linear uncertain systems. In addition to the conventional notion of robustness based on quantitative information, in this paper, a new and novel perspective of qualitative robustness is introduced. The qualitative robustness measure is inspired by ecological principles and is based on the nature of interactions and interconnections of the system. Thus, using the proposed framework, the robustness of engineering systems can be assessed both from quantitative as well as qualitative information. This type of analysis from both viewpoints sheds considerable insight on the desirable nominal system in engineering applications. Using these concepts it is shown that a specific quantitative set of matrices labeled ‘Target Sign Stable Matrices’ are the best nominal matrices. These concepts are then extended to closed loop control systems and problem of control design and for ease in design a new set of matrices ‘Target Pseudosymmetric Matrices’ are introduced which enhance the class of desirable closed loop system matrices. Examples are included to illustrate these concepts.

EXPERIMENTAL RESULTS FOR THE SMALL-SIGNAL STUDY OF THE PWM BOOST DC–DC CONVERTER WITH AN INTEGRAL-LEAD CONTROLLER

1995 ◽  
Vol 05 (04) ◽  
pp. 747-755 ◽  
Author(s):  
MARIAN K. KAZIMIERCZUK ◽  
ROBERT C. CRAVENS, II
Keyword(s):  
Closed Loop ◽  
Transfer Functions ◽  
Low Frequency ◽  
Input Voltage ◽  
Open Loop ◽  
Small Signal ◽  
Loop Control ◽  
Pulse Width Modulated ◽  
Bode Plots ◽  
Step Responses

An experimental verification of previously derived small-signal low-frequency open- and closed-loop characteristics and step responses of a voltage-mode-controlled pulse-width-modulated (PWM) boost DC–DC converter is presented. The Bode plots of the voltage transfer function of the control circuit, the converter and the PWM modulator, the open-loop control-to-output and input-to-output transfer functions, the loop gain, and the closed-loop control-to-output and input-to-output transfer functions are measured. The step responses to the changes in the input voltage, the duty cycle, and the reference voltage are measured. The theoretical results were in good agreement with the measured results. The small-signal model of the converter is experimentally verified.

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