149 research outputs found
A Robust Offline Precomputed Optimal Feedforward Control Action for the Real Time Feedback/Feedforward Control of Double Pendulum Gantry Cranes
none1openvalentina orsiniOrsini, Valentin
Model predictive control for improving operational efficiency of overhead cranes
Model predictive control (MPC) has been
successfully applied to many transportation systems.
For the control of overhead cranes, existing MPC approaches
mainly focus on improving the regulation performance,
such as tracking error or steady-state error.
In this paper, energy efficiency as well as safety is newly
considered in our proposed MPC approach. Based on
the system model designed, the MPC approach is applied
to minimize an objective function that is formulated
as the integration of energy consumption and swing
angle. In our approach, promising results in terms of
low energy consumption and small swing angle can be
found, whilst the solutions obtained can satisfy all practical
constraints. Our test results indicate that the MPC
approach can ensure stability and robustness of improving
energy efficiency and safety.http://link.springer.com/journal/110712016-03-31hb201
Development of controller and observer for 2D Crane System via State-space approach
This report actually presents researches and studies and progress that are being achieved for the chosen topic which is Development of controller and observer for 2D Crane Systems via State-space approach. This report contains an introduction and background studies about cranes and how does this topic it related to my studies as a final year & control system student all being represented in scope of studies section, in fact the main objectives of this research are getting the dynamic equation for the 2D crane systems and applies state-space approach to develop a controller and an observer for them. The dynamic equations for the systems are being obtained by using Euler-Langrange formulation for obtaining the state-space representation of the systems. Furthermore, control & observer canonical forms have been designed and then simulated using Matlab Simulink for testing the stability of the system before designing the controller and the observer for the syste
Second-Order Sliding Mode Control of a Perturbed-Crane
A five degrees-of-freedom overhead crane system affected by external perturbations is the topic of study. Existing methods just handle the unperturbed case or, in addition, the analysis is limited to three or two degrees-of-freedom. A wide range of processes cannot be restricted to these scenarios and this paper goes a step forward proposing a control solution for a five degrees-of-freedom system under the presence of matched and unmatched disturbances. The contribution includes a model description and a secondorder sliding mode (SOSM) control design ensuring the precise trajectory tracking for the actuated variables and at the same time the regulation of the unactuated variables. Furthermore, the proposed approach is supported by the design of strong Lyapunov functions providing an estimation of the convergence time. Simulations and experiments, including a comparison with a proportional-integral-derivative (PID) controller, verified the advantages of the methodology
Vision-based control of a knuckle boom crane with online cable length estimation
A vision-based controller for a knuckle boom crane is presented. The
controller is used to control the motion of the crane tip and at the same time
compensate for payload oscillations. The oscillations of the payload are
measured with three cameras that are fixed to the crane king and are used to
track two spherical markers fixed to the payload cable. Based on color and size
information, each camera identifies the image points corresponding to the
markers. The payload angles are then determined using linear triangulation of
the image points. An extended Kalman filter is used for estimation of payload
angles and angular velocity. The length of the payload cable is also estimated
using a least squares technique with projection. The crane is controlled by a
linear cascade controller where the inner control loop is designed to damp out
the pendulum oscillation, and the crane tip is controlled by the outer loop.
The control variable of the controller is the commanded crane tip acceleration,
which is converted to a velocity command using a velocity loop. The performance
of the control system is studied experimentally using a scaled laboratory
version of a knuckle boom crane
HIGH ORDER SLIDING MODE CONTROL WITH ANTI-SWAY BASED COMPENSATION ON ARTIFICIAL NEURAL NETWORK BY PSO ALGORITHM FOR OVERHEAD CRANE
This paper proposes a second order sliding mode controller combined with signal set calibrator for overhead crane tracking desired position and resisting disturbance. High order sliding mode controller ensures that the overhead crane tracks desired trajectory and resists disturbance. Neural network is trained by particle swarm optimization algorithm (PSO) to compensate anti-sway for load. The results on the computer simulation show that high order sliding mode controller with anti-sway compensation for overhead crane tracks desired trajectory and the swing of load that is smaller than high order sliding mode controller without anti-sway compensation
Nonlinear optimal control for the 4-DOF underactuated robotic tower crane
Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controllerâs feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robotâs number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robotâs actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the articleâs nonlinear optimal control scheme is of proven global stability and convergence to the optimum.This research work has been partially supported by Grant Ref. âCSP contract 040322âââNonlinear control, estimation and fault diagnosis for electric power generation and electric traction/propulsion systemsâ of the Unit of Industrial Automation of the Industrial Systems Institute
Integrated sensing, dynamics and control of a moble gantry crane
This thesis investigates the dynamics and control of a Rubber Tyred Gantry (RTG)
crane which is commonly used in container handling operations. Both theoretical and
experimental work has been undertaken to ensure the balance of this research.
The concept of a Global Sensing System (GSS) is outlined, this being a closed loop
automatic sensing system capable of guiding the lifting gear (spreader) to the location
of the target container by using feedback signals from the crane's degrees of freedom.
To acquire the crucial data for the coordinates and orientation of the swinging
spreader a novel visual sensing system (VSS) is proposed. In addition algorithms used
in the VSS for seeking the central coordinates of the clustered pixels from the digitised
images are also developed.
In order to investigate the feasibility of different control strategies in practice, a scaleddown, 1/8 full size, experimental crane rig has been constructed with a new level of
functionality in that the spreader in this rig is equipped with multiple cables to emulate
the characteristics of a full-size RTG crane. A Crane Application Programming
Interface (CAPI) is proposed to reduce the complexity and difficulty in integrating the
control software and hardware. It provides a relatively user-friendly environment in
which the end-user can focus on implementing the more fundamental issues of control
strategies, rather than spending significant amounts of time in low-level devicedependent programming.
A control strategy using Feedback Linearization Control (FLC) is investigated. This
can handle significant non-linearity in the dynamics of the RTG crane. Simulation
results are provided, and so by means of the CAPI this controller is available for direct
control of the experimental crane rig. The final part of the thesis is an integration of the
analyses of the different subjects, and shows the feasibility of real-time implementation
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