Output-based command shaping technique for an effective payload sway control of a 3D crane with hoisting

2016 ◽  
Vol 39 (10) ◽  
pp. 1443-1453 ◽  
Author(s):  
Auwalu M Abdullahi ◽  
Z Mohamed ◽  
MS Zainal Abidin ◽  
S Buyamin ◽  
Amir A Bature
Keyword(s):  
Closed Loop ◽  
Reference Model ◽  
Damping Ratio ◽  
Time Varying ◽  
Actual System ◽  
Command Shaping ◽  
Shaping Technique ◽  
Non Linear ◽  
Length Changes ◽  
Travel Length

This paper presents an output-based command shaping (OCS) technique for an effective payload sway control of a 3D crane with hoisting. A crane is a challenging and time-varying system, as the cable length changes during the operation. The OCS technique is designed based on output signals of an actual system and reference model, does not require the natural frequency and damping ratio of the system, and thus can be utilized to minimize the hoisting effects on the payload sway. The shaper was designed by using the derived non-linear model of a 3D crane. To test the effectiveness of the controller, simulations using a non-linear 3D crane model and experiments on a lab-scale 3D crane were performed and compared with a zero vibration derivative (ZVD) shaper and a ZVD shaper designed using an average travel length (ATL) technique. In both the simulations and the experiments, the OCS technique was shown to be superior in reducing the payload sway with reductions of more than 56% and 33% in both of the transient and residual sways that were achieved when compared with both the ZVD and the ATL shapers, respectively. In addition, the OCS technique provided the fastest time response during the hoisting. It is envisaged that the method can be very useful in reducing the complexity of closed-loop controllers for both tracking and sway control.

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.

Adaptive robust stabilization of a class of uncertain non-linear systems with mismatched time-varying parameters

2011 ◽  
Vol 226 (2) ◽  
pp. 204-214 ◽  
Author(s):  
M M Arefi ◽  
M R Jahed-Motlagh
Keyword(s):  
Linear Systems ◽  
Closed Loop ◽  
Robust Stabilization ◽  
Lyapunov Theory ◽  
Loop System ◽  
Time Varying ◽  
Closed Loop System ◽  
Mismatched Uncertainties ◽  
Non Linear ◽  
Non Linear Systems

In this paper, an adaptive robust stabilization algorithm is presented for a class of non-linear systems with mismatched uncertainties. In this regard, a new controller based on the Lyapunov theory is proposed in order to overcome the problem of stabilizing non-linear time-varying systems with mismatched uncertainties. This method is such that the stability of the closed-loop system is guaranteed in the absence of the triangularity assumption. The proposed approach leads to asymptotic convergence of the states of the closed-loop system to zero for unknown but bounded uncertainties. Subsequently, this method is modified so that all the signals in the closed-loop system are uniformly ultimately bounded. Eventually, numerical simulations support the effectiveness of the given algorithm.

scholarly journals A Single Differential Equation for First-Excursion Time in a Class of Linear Systems

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Matthew B. Greytak ◽  
Franz S. Hover
Keyword(s):  
Structural Dynamics ◽  
Closed Loop ◽  
Damping Ratio ◽  
Robotic Systems ◽  
Time Varying ◽  
Stochastic Environments ◽  
Closed Loop Systems ◽  
Time Varying Systems ◽  
Major Application ◽  
Excursion Time

First-excursion times have been developed extensively in the literature for oscillators; one major application is structural dynamics of buildings. Using the fact that most closed-loop systems operate with a moderate to high damping ratio, we have derived a new procedure for calculating first-excursion times for a class of linear continuous, time-varying systems. In several examples, we show that the algorithm is both accurate and time-efficient. These are important attributes for real-time path planning in stochastic environments, and hence the work should be useful for autonomous robotic systems involving marine and air vehicles.

Adaptive Augmenting Control Design for Time-Varying Polytopic Systems

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Hessam Mahdianfar ◽  
Emmanuel Prempain
Keyword(s):  
Convex Optimization ◽  
State Feedback ◽  
Closed Loop ◽  
Reference Model ◽  
Tracking Error ◽  
Control Design ◽  
Adaptive Controller ◽  
Time Varying ◽  
Robust Convex Optimization ◽  
And Performance

To increase the performance of closed-loop controlled systems in off-nominal conditions and in the presence of inevitable faults and uncertainties, a systematic approach based on robust convex optimization for adaptive augmenting control design is discussed in this paper. More specifically, this paper addresses the problem of adaptive augmenting controller (AAC) design for systems with time-varying polytopic uncertainty. First, a robust state-feedback controller is designed via robust convex optimization as a baseline controller. The closed-loop polytopic system with the baseline controller is considered as the desired time-varying reference model for the design of a direct state-feedback adaptive controller. Next using Lyapunov arguments, global stability of combined robust baseline and adaptive augmenting controllers is established. Furthermore, it is proved that tracking error converges to zero asymptotically. A case study for a generic nonminimum phase nonlinear pitch-axis missile autopilot is conducted. Simulation tests are performed to evaluate stability and performance of nonlinear time-varying closed-loop system in the presence of uncertainties in pitching moment and normal force coefficients, and unmodeled time delays. In addition, results of the simulations indicate satisfactory robustness in case of severe loss of control effectiveness event.

scholarly journals Learning Input Shaping Technique for Non-LTI Systems

1998 ◽  
Vol 123 (2) ◽  
pp. 288-293 ◽  
Author(s):  
Juyi Park ◽  
Pyung-Hun Chang
Keyword(s):  
Natural Frequency ◽  
Closed Loop ◽  
Industrial Robot ◽  
Loop System ◽  
Input Shaping ◽  
Time Varying ◽  
Closed Loop System ◽  
Shaping Technique ◽  
Time Varying Systems

It is well known that conventional Input Shaping Technique (IST) is not very effective in suppressing residual vibrations for non-LTI systems, such as substantially nonlinear or time-varying systems. In an effort to increase the effectiveness such systems, this paper presents Learning Input Shaping Technique (LIST) which iteratively updates the parameters of IST from previous trials. Simulations are presented for four different cases: (1) when the natural frequency or damping of a system is not estimated well; (2) when a system has time varying vibration; (3) when a system has nonlinear flexibility; and (4) when a closed-loop system includes a saturation element in the loop. LIST is experimented on a six D.O.F industrial robot to evaluate its effectiveness. The results of the simulations and the experiment show that the residual vibrations become considerably smaller as iteration goes on, thereby demonstrating the effectiveness of LIST.

Simulation and Design of Double Close-Loop DC Motor Control System Based on Matlab

2012 ◽  
Vol 546-547 ◽  
pp. 248-253
Author(s):  
Jing Jing Xiong ◽  
Zhen Feng ◽  
Jiao Yu Liu
Keyword(s):  
Motor Control ◽  
Control System ◽  
System Design ◽  
Closed Loop ◽  
Dynamic Performance ◽  
Model System ◽  
Optimal Parameters ◽  
Actual System ◽  
Dc Motor Control ◽  
Motor Control System

In this paper, based on the principle of the speed and current double closed loop DC regulating system and the requirement of the static and dynamic performance, we calculate time constant of the regulator, select the structure of the regulator to calculate related parameter and then correct its parameters, and model system and simulation by using Simulink, analysis waveform and debug to find out the optimal parameters of the system regulator to guide the actual system design.

The Swing Control of Cranes with Variable Rope Length Based on Linear Time Varying System Theory

2012 ◽  
Vol 461 ◽  
pp. 763-767
Author(s):  
Li Fu Wang ◽  
Zhi Kong ◽  
Xin Gang Wang ◽  
Zhao Xia Wu
Keyword(s):  
State Feedback ◽  
Closed Loop ◽  
Linear Time ◽  
Feedback Stabilization ◽  
Time Varying ◽  
Closed Loop System ◽  
Overhead Cranes ◽  
Time Varying Systems ◽  
Time Invariant ◽  
Time Invariant System

In this paper, following the state-feedback stabilization for time-varying systems proposed by Wolovich, a controller is designed for the overhead cranes with a linearized parameter-varying model. The resulting closed-loop system is equivalent, via a Lyapunov transformation, to a stable time-invariant system of assigned eigenvalues. The simulation results show the validity of this method.

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