Payload Oscillations Minimization via Open Loop Control.

The results of tests of payload oscillations, forced by linear control function which allows to minimize payload sway after acceleration phase and after overhead crane stopping are presented in this paper. The analysis of solution of this problem has been carried out. The algorithm of operation for real drive system which takes into account the possibilities of driving of an overhead crane is also presented. The impact of inaccuracies of measurement of the ropes length on minimizing a displacements of payload during the duty cycle is shown as well. The correctness of the method is confirmed by results both simulation and experimental tests

Development of Motion Control Systems for Hydraulically Actuated Cranes with Hanging Loads

Automation has been used in industrial processes for several decades to increase efficiency and safety. Tasks that are either dull, dangerous, or dirty can often be performed by machines in a reliable manner. This may provide a reduced risk to human life, and will typically give a lower economic cost. Industrial robots are a prime example of this, and have seen extensive use in the automotive industry and manufacturing plants. While these machines have been employed in a wide variety of industries, heavy duty lifting and handling equipment such as hydraulic cranes have typically been manually operated. This provides an opportunity to investigate and develop control systems to push lifting equipment towards the same level of automation found in the aforementioned industries. The use of winches and hanging loads on cranes give a set of challenges not typically found on robots, which requires careful consideration of both the safety aspect and precision of the pendulum-like motion. Another difference from industrial robots is the type of actuation systems used. While robots use electric motors, the cranes discussed in this thesis use hydraulic cylinders. As such, the dynamics of the machines and the control system designmay differ significantly. In addition, hydraulic cranes may experience significant deflection when lifting heavy loads, arising from both structural flexibility and the compressibility of the hydraulic fluid. The work presented in this thesis focuses on motion control of hydraulically actuated cranes. Motion control is an important topic when developing automation systems, as moving from one position to another is a common requirement for automated lifting operations. A novel path controller operating in actuator space is developed, which takes advantage of the load-independent flow control valves typically found on hydraulically actuated cranes. By operating in actuator space the motion of each cylinder is inherently minimized. To counteract the pendulum-like motion of the hanging payload, a novel anti-swing controller is developed and experimentally verified. The anti-swing controller is able to suppress the motion from the hanging load to increase safety and precision. To tackle the challenges associated with the flexibility of the crane, a deflection compensator is developed and experimentally verified. The deflection compensator is able to counteract both the static deflection due to gravity and dynamic de ection due to motion. Further, the topic of adaptive feedforward control of pressure compensated cylinders has been investigated. A novel adaptive differential controller has been developed and experimentally verified, which adapts to system uncertainties in both directions of motion. Finally, the use of electro-hydrostatic actuators for motion control of cranes has been investigated using numerical time domain simulations. A novel concept is proposed and investigated using simulations.publishedVersio

Adaptive fuzzy observer based hierarchical sliding mode control for uncertain 2D overhead cranes

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. This paper proposes a new approach to robustly control a 2D under-actuated overhead crane system, where a payload is effectively transported to a destination in real time with small sway angles, given its inherent uncertainties such as actuator nonlinearities and external disturbances. The control law is proposed to be developed by the use of the robust hierarchical sliding mode control (HSMC) structure in which a second-level sliding surface is formulated by two first-level sliding surfaces drawn on both actuated and under-actuated outputs of the crane. The unknown and uncertain parameters of the proposed control scheme are then adaptively estimated by the fuzzy observer (FO), where the adaptation mechanism is derived from the Lyapunov theory. More importantly, stability of the proposed strategy is theoretically proved. Effectiveness of the proposed adaptive FO-based HSMC approach was extensively validated by implementing the algorithm in both synthetic simulations and real-life experiments, where the results obtained by our method are highly promising

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 controller’s 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 robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum.This research work has been partially supported by Grant Ref. “CSP contract 040322”—“Nonlinear control, estimation and fault diagnosis for electric power generation and electric traction/propulsion systems” of the Unit of Industrial Automation of the Industrial Systems Institute

Payload motion control for a varying length flexible gantry crane

Cranes play a very important role in transporting heavy loads in various industries. However, because of its natural swinging characteristics, the control of crane needs to be considered carefully. This paper presents a control approach to a flexible cable crane system in consideration of both rope length varying and system constraints. At first, from Hamilton\u27s extended principle the equations of motion that characterized coupled transverse-transverse motions with varying rope length of the gantry are obtained. The equations of motion consist of a system of partial differential equations. Then, a barrier Lyapunov function is used to derive the control located at the trolley end that can precisely position the gantry payload and minimize vibrations. The designed control is verified through extensive experimental studies

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

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