229 research outputs found
An Efficient Adaptive Hierarchical Sliding Mode Control Strategy Using Neural Networks for 3D Overhead Cranes
© 2019, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Gmbh Germany, part of Springer Nature. In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and real-life systems, where the results obtained by our method are highly promising
Robust Adaptive Control of 3D Overhead Crane System
In this chapter an adaptive anti-sway controller for uncertain overhead cranes is proposed. The system model including the system uncertainties and disturbances is introduced firstly. Next, the adaptive controller which can guarantee tracking the desired position of the trolley as well as the anti-sway of the load cable is established. In this chapter, the system is proven to be input-to-state stable (ISS) which is supported by Lyapunov technique. The proposed algorithm is verified by using Matlab/Simulink simulation tool. The simulation results shown that the presented controller gives the good performances (i.e., fast transient response, position tracking, and low swing angle) when there exist system parameters variation as well as input disturbances
New developments in mathematical control and information for fuzzy systems
Hamid Reza Karimi, Mohammed Chadli and Peng Sh
Input shaping-based control schemes for a three dimensional gantry crane
The motion induced sway of oscillatory systems such as gantry cranes may decrease the efficiency of production lines. In this thesis, modelling and development of input shaping-based control schemes for a three dimensional (3D) lab-scaled gantry crane are proposed. Several input shaping schemes are investigated in open and closed-loop systems. The controller performances are investigated in terms of trolley position and sway responses of the 3D crane. Firstly, a new distributed Delay Zero Vibration (DZV) shaper is implemented and compared with Zero Vibration (ZV) shaper and Zero Vibration Derivative (ZVD) shaper. Simulation and experimental results show that all the shapers are able to reduce payload sway significantly while maintaining desired position response specifications. Robustness tests with ±20% error in natural frequency show that DZV shaper exhibits asymmetric robustness behaviour as compared to ZV and ZVD shapers. Secondly, as analytical technique could only provide good performance for linear systems, meta-heuristic based input shaper is proposed to reduce sway of a gantry crane which is a nonlinear system. The results show that designing meta-heuristic-based input shapers provides 30% to 50% improvement as compared to the analytical-based shapers. Subsequently, a particle swarm optimization based optimal performance control scheme is developed in closed-loop system. Simulation and experimental results demonstrate that the controller gives zero overshoot with 60% and 20% improvements in settling time and integrated absolute error value of position response respectively, as compared to a specific designed PID-PID anti swing controller for the lab-scaled gantry crane. It is found that crane control with changing cable length is still a problem to be solved. An adaptive input shaping control scheme that can adapt to variation of cable’s length is developed. Simulation with real crane dimensions and experimental results verify that the controller provides 50% reduction in payload sway for different operational commands with hoisting as compared to the average travel length approach
Adaptive Control
Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems
Advanced Discrete-Time Control Methods for Industrial Applications
This thesis focuses on developing advanced control methods for two industrial
systems in discrete-time aiming to enhance their performance in delivering the
control objectives as well as considering the practical aspects. The first part
addresses wind power dispatch into the electricity network using a battery
energy storage system (BESS). To manage the amount of energy sold to the
electricity market, a novel control scheme is developed based on discrete-time
model predictive control (MPC) to ensure the optimal operation of the BESS in
the presence of practical constraints. The control scheme follows a decision
policy to sell more energy at peak demand times and store it at off-peaks in
compliance with the Australian National Electricity Market rules. The
performance of the control system is assessed under different scenarios using
actual wind farm and electricity price data in simulation environment. The
second part considers the control of overhead crane systems for automatic
operation. To achieve high-speed load transportation with high-precision and
minimum load swings, a new modeling approach is developed based on independent
joint control strategy which considers actuators as the main plant. The
nonlinearities of overhead crane dynamics are treated as disturbances acting on
each actuator. The resulting model enables us to estimate the unknown
parameters of the system including coulomb friction constants. A novel load
swing control is also designed based on passivity-based control to suppress
load swings. Two discrete-time controllers are then developed based on MPC and
state feedback control to track reference trajectories along with a feedforward
control to compensate for disturbances using computed torque control and a
novel disturbance observer. The practical results on an experimental overhead
crane setup demonstrate the high performance of the designed control systems.Comment: PhD Thesis, 230 page
Robust Control of Crane with Perturbations
In the presence of persistent perturbations in both unactuated and actuated dynamics of crane systems, an observer-based robust control method is proposed, which achieves the objective of trolley positioning and cargo swing suppression. By dealing with the unactuated and unknown perturbation as an augmented state variable, the system dynamics are transformed into a quasi-chain-of-integrators form based on which a reduced-order augmented-state observer is established to recover the perturbations appearing in the unactuated dynamics. A novel sliding manifold is constructed to improve the robust performance of the control system, and a linear control law is presented to make the state variables stay on the manifold in the presence of perturbations in unactuated dynamics. A Lyapunov function candidate is constructed, and the entire closed-loop system is proved rigorously to be exponentially stable at the equilibrium point. The effectiveness and robustness of the proposed observer-based robust controller are verified by numerical simulation results
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