Multi-objective Anti-swing Trajectory Planning of Double-pendulum Tower Crane Operations using Opposition-based Evolutionary Algorithm

Underactuated tower crane lifting requires time-energy optimal trajectories for the trolley/slew operations and reduction of the unactuated swings resulting from the trolley/jib motion. In scenarios involving non-negligible hook mass or long rig-cable, the hook-payload unit exhibits double-pendulum behaviour, making the problem highly challenging. This article introduces an offline multi-objective anti-swing trajectory planning module for a Computer-Aided Lift Planning (CALP) system of autonomous double-pendulum tower cranes, addressing all the transient state constraints. A set of auxiliary outputs are selected by methodically analyzing the payload swing dynamics and are used to prove the differential flatness property of the crane operations. The flat outputs are parameterized via suitable B\'{e}zier curves to formulate the multi-objective trajectory optimization problems in the flat output space. A novel multi-objective evolutionary algorithm called Collective Oppositional Generalized Differential Evolution 3 (CO-GDE3) is employed as the optimizer. To obtain faster convergence and better consistency in getting a wide range of good solutions, a new population initialization strategy is integrated into the conventional GDE3. The computationally efficient initialization method incorporates various concepts of computational opposition. Statistical comparisons based on trolley and slew operations verify the superiority of convergence and reliability of CO-GDE3 over the standard GDE3. Trolley and slew operations of a collision-free lifting path computed via the path planner of the CALP system are selected for a simulation study. The simulated trajectories demonstrate that the proposed planner can produce time-energy optimal solutions, keeping all the state variables within their respective limits and restricting the hook and payload swings.Comment: 14 pages, 14 figures, 6 table

Dynamic weighted idle time heuristic for flowshop scheduling

The constructive heuristic of Nawaz, Enscore and Ham (NEH) has been introduced in 1983 to solve flowshop scheduling. Many researchers have continued to improve the NEH by adding new steps and procedures to the existing algorithm. Thus, this study has developed a new heuristic known as Dynamic Weighted Idle Time (DWIT) method by adding dynamic weight factors for solving the partial solution with purpose to obtain optimal makespan and improve the NEH heuristic. The objective of this study are to develop a DWIT heuristic to solve flowshop scheduling problem and to assess the performance of the new DWIT heuristic against the current best scheduling heuristic, ie the NEH. This research developed a computer programming in Microsoft Excel to measure the flowshop scheduling performance for every change of weight factors. The performance measure is done by using n jobs (n=6,10 and 20) and 4 machines. The weight factors were applied with numerical method within the range of zero to one. Different weight factors and machines idle time were used at different problem sizes. For 6 jobs and 4 machines, only idle time before and in between two jobs were used while for 10 jobs and 20 jobs the consideration of idle time was idle time before, in between two jobs and after completion of the last job. In 6 jobs problem, the result was compared between DWIT against Optimum and NEH against Optimum. While in 10 jobs and 20 jobs problem the result was compared between DWIT against the NEH. Overall result shows that the result on 6 and 10 jobs problem the DWIT heuristic obtained better results than NEH heuristic. However, in 20 jobs problem, the result shows that the NEH was better than DWIT. The result of this study can be used for further research in modifying the weight factors and idle time selections in order to improve the NEH heuristic

Modelling And Fuzzy Logic Control Of An Underactuated Tower Crane System

Tower crane is one of the flexible maneuvering systems that has been applied pervasively as a powerful big-scale construction machine. The under-actuated tower crane system has nonlinearity behavior with a coupling between translational and slew motions which increases the crane control challenge. In practical applications, most of the tower cranes are operated by a human operator which lead to unsatisfactory control tasks. Motivated to overcome the issues, this paper proposes a fuzzy logic controller based on single input rule modules dynamically connected fuzzy inference system for slew/translational positioning and swing suppressions of a 3 degree-of-freedom tower crane system. The proposed method can reduce the number of rules significantly, resulting in a simpler controller design. The proposed method achieves higher suppressions of at least 56% and 81% in the overall in-plane and out-plane swing responses, respectively as compared to PSO based PID+PD control

Reduction of Oscillations in Hydraulically Actuated Knuckle Boom Cranes

Doktorgradsavhandling ved Universitetet i Agder, Institutt for ingeniørvitenskap, 2016A knuckle boom crane is characterized by being a versatile machine that during operation experiences large load variations caused by the changes in position and payload. Common uses are as a mobile loader crane mounted on trucks and in offshore applications. Since their introduction the use of counterbalance valves (CBV) have been the de facto standard on load-carrying hydraulically actuated applications like the knuckle boom crane. It offers a simple and practical solution to one of the issues of mobile cranes: Controlling the load safely when lowering. By law (e.g. European Standard) the hydraulic circuit of load-carrying applications is required to contain a load holding protection device. The classical way of actuating such a crane is to use a circuit containing a pressure compensator valve and a directional control valve (DCV) in series with a CBV. This circuit is referred to as the base circuit. It is well known that this combination of valve components tends to introduce instability in the base circuit. This is mainly a problem when the controlled actuator is subjected to a negative load, because this will require the CBV to throttle the return flow. The instability presents itself as pressure oscillations in the hydraulic circuit which cause the mechanical structure to oscillate. The consequence of the oscillations is a decreased accuracy of the boom motion which create a safety risk, reduces productivity and introduces an undesirable extra fatigue load. The objective of this project was to investigate the oscillations created in the hydraulic circuit of knuckle boom cranes and reduce their severity. The effort has mainly been split in two: First, was looked into existing solutions with the focus on the ones not requiring control systems to function. This was done with reliability and robustness in mind. The investigation identified the pressure control valve (PCV) as the best commercially available solution. The use of a PCV to control the inlet flow in crane applications was rather uncharted territory. The valve, a DCV with a pressure control spool manufactured by Danfoss, has been investigated both theoretically and experimentally. A linear stability analysis has been performed with the Routh-Hurwitz stability criterion. This analysis of the valve used together with a hydraulically actuated experimental setup indicates that the combination is stable in all situations. The use of the pressure control spool in the DCV is a simple and robust solution to the stability problem of the base circuit. Not related to the PCV’s ability to reduce the oscillations the use of it in knuckle boom cranes, however, comes with certain drawbacks. The drawbacks include a load dependent dead band and a load dependent inlet flow. In order to achieve similar behavior as the normal pressure compensated DCV a closed loop control system is required. These issues are addressed in this project, where control schemes are proposed to handle them. In the second part the perspective of the search was broadened to include solutions using control systems. This has lead to the development of a novel, patent pending, concept that significantly reduces the oscillations of the base circuit. It introduces a secondary circuit where a low-pass filtered value of the load pressure is generated and fed back to the compensator of the flow supply valve. The work has demonstrated a significant improvement of stability obtained for a system with the novel concept implemented both theoretically and experimentally. The stability has been investigated both using a linear and a nonlinear model of a hydraulically actuated experimental setup. The presented novel concept circuit has the same steady state characteristics as the base circuit but without the corresponding oscillatory nature. Because the main spool of the DCV is not used for stabilising the system, the novel concept can be combined with any feedback control strategy. In this project, the novel concept is presented with linear actuators only. However,its use covers circuits with rotational actuators and CBV’s as well. The base circuit is used as a reference for comparison. Therefore, the stability of the base circuit is also investigated with a linear model

Intelligent control of a class of nonlinear systems

The objective of this study is to improve and propose new fuzzy control algorithms for a class of nonlinear systems. In order to achieve the objectives, novel stability theorems as well as modeling techniques are also investigated. Fuzzy controllers in this work are designed based on the fuzzy basis function neural networks and the type-2 Takagi-Sugeno fuzzy models. For a class of single-input single-output nonlinear systems, a new stability condition is derived to facilitate the design process of proportional-integral Mamdani fuzzy controllers. The stability conditions require a new technique to calculate the dynamic gains of nonlinear systems represented by fuzzy basis function network models. The dynamic gain of a fuzzy basis function network can be approximated by finding the maximum of norm values of the locally linearized systems or by solving a non-smooth optimal control problem. Based on the new stability theorem, a multilevel fuzzy controller with self-tuning algorithm is proposed and simulated in a tower crane control system. For a class of multi-input multi-output nonlinear systems with measurable state variables, a new method for modeling unstructured uncertainties and robust control of unknown nonlinear dynamic systems is proposed by using a novel robust Takagi-Sugeno fuzzy controller. First, a new training algorithm for an interval type-2 fuzzy basis function network is presented. Next, a novel technique is derived to convert the interval type-2 fuzzy basis function network to an interval type-2 Takagi-Sugeno fuzzy model. Based on the interval type-2 Takagi-Sugeno and type-2 fuzzy basis function network models, a robust controller is presented with an adjustable convergence rate. Simulation results on an electrohydraulic actuator show that the robust Takagi-Sugeno fuzzy controller can reduce steady-state error under different conditions while maintaining better responses than the other robust sliding mode controllers can. Next, the study presents an implementation of type-2 fuzzy basis function networks and robust Takagi-Sugeno fuzzy controllers to data-driven modeling and robust control of a laser keyhole welding process. In this work, the variation of the keyhole diameter during the welding process is approximated by a type-2 fuzzy-basis-function network, while the keyhole penetration depth is modelled by a type-1 fuzzy basis function network. During the laser welding process, a CMOS camera integrated with the welding system was used to provide a feedback signal of the keyhole diameter. An observer was implemented to estimate the penetration depth in real time based on the adaptive divided difference filter and the feedback signal from the camera. A robust Takagi-Sugeno fuzzy controller was designed based on the fuzzy basis function networks representing the welding process with uncertainties to adjust the laser power to ensure that the penetration depth of the keyhole is maintained at a desired value. Experimental results demonstrated that the fuzzy models provided an accurate estimation of both the welding geometry and its variations due to uncertainties, and the robust Takagi-Sugeno fuzzy controller successfully reduced the penetration depth variation and improved the quality of the welding process

Modelado de sensores piezoresistivos y uso de una interfaz basada en guantes de datos para el control de impedancia de manipuladores robóticos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Arquitectura de Computadores y Automática, leída el 21-02-2014Sección Deptal. de Arquitectura de Computadores y Automática (Físicas)Fac. de Ciencias FísicasTRUEunpu

Modelling and control of subsea installation

Ph.DDOCTOR OF PHILOSOPH