No description available.

The main objective of this work is to design robust, fast, and practical controllers for gantry and tower cranes. The controllers are designed to transfer the load from point to point as fast as possible and, at the same time, the load swing is kept small during the transfer process and completely vanishes at the load destination. Moreover, variations of the system parameters, such as the cable length and the load weight, are also included. Practical considerations, such as the control action power, and the maximum acceleration and velocity, are taken into account. In addition, friction effects are included in the design using a friction-compensation technique. The designed controllers are based on two approaches. In the first approach, a gain-scheduling feedback controller is designed to move the load from point to point within one oscillation cycle without inducing large swings. The settling time of the system is taken to be equal to the period of oscillation of the load. This criterion enables calculation of the controller feedback gains for varying load weight and cable length. The position references for this controller are step functions. Moreover, the position and swing controllers are treated in a unified way. In the second approach, the transfer process and the swing control are separated in the controller design. This approach requires designing two controllers independently: an anti-swing controller and a tracking controller. The objective of the anti-swing controller is to reduce the load swing. The tracking controller is responsible for making the trolley follow a reference position trajectory. We use a PD-controller for tracking, while the anti-swing controller is designed using three different methods: (a) a classical PD controller, (b) two controllers based on a delayed-feedback technique, and (c) a fuzzy logic controller that maps the delayed-feedback controller performance. To validate the designed controllers, an experimental setup was built. Although the designed controllers work perfectly in the computer simulations, the experimental results are unacceptable due to the high friction in the system. This friction deteriorates the system response by introducing time delay, high steady-state error in the trolley and tower positions, and high residual load swings. To overcome friction in the tower-crane model, we estimate the friction, then we apply an opposite control action to cancel it. To estimate the friction force, we assume a mathematical model and estimate the model coefficients using an off-line identification technique using the method of least squares. With friction compensation, the experimental results are in good agreement with the computer simulations. The gain-scheduling controllers transfer the load smoothly without inducing an overshoot in the trolley position. Moreover, the load can be transferred in a time near to the optimal time with small swing angles during the transfer process. With full-state feedback, the crane can reach any position in the working environment without exceeding the system power capability by controlling the forward gain in the feedback loop. For large distances, we have to decrease this gain, which in turn slows the transfer process. Therefore, this approach is more suitable for short distances. The tracking-anti-swing control approach is usually associated with overshoots in the translational and rotational motions. These overshoots increase with an increase in the maximum acceleration of the trajectories . The transfer time is longer than that obtained with the first approach. However, the crane can follow any trajectory, which makes the controller cope with obstacles in the working environment. Also, we do not need to recalculate the feedback gains for each transfer distance as in the gain-scheduling feedback controller. / Ph. D.

O problema de transferir uma carga ao se movimentar num plano em tempo mínimo e sem oscilação no ponto de descarga, num guindaste portuário tipo pórtico é investigado neste trabalho. Assume-se que a carga esteja inicialmente em repouso na posição vertical no ponto de carga acima do navio e igualmente em repouso no ponto de descarga na moega de alimentação no porto. Assume-se também que o carro do guindaste esteja em repouso em ambos os pontos. Um modelo completo é apresentado para o sistema do guindaste onde as equações dinâmicas não-lineares são linearizadas para ângulos de oscilação pequenos o suficiente e reescritas para a forma adimensional. A solução de tempo mínimo é buscada considerando como variáveis de controle as funções do tempo que descrevem tanto a força aplicada no carro para produzir seu deslocamento horizontal, como a velocidade de içamento da carga. Um método iterativo preditor-corretor usando a Programação Linear (PL) é proposto, baseado no modelo do sistema de tempo discreto onde as variáveis de controle são tomadas constantes por trechos. Na etapa corretora, assume-se que o movimento de içamento é dado e uma solução de tempo mínimo é obtida resolvendo-se uma seqüência de problemas de PL de tempo fixo e máximo deslocamento. Na etapa preditora, um modelo linearizado é empregado para obter-se uma correção ótima do movimento de içamento usando a PL. O problema de controle de tempo mínimo é formulado levando-se em consideração restrições práticas na velocidade do carro do guindaste, velocidade máxima de içamento, assim como na máxima força que pode ser aplicada ao carro. Resultados numéricos são apresentados e mostram a efetividade do método. / The problem of minimum-time anti-swing transfer of a load in a ship-to-pier gantry crane is investigated in this work. The load is assumed to be initially at rest at the vertical position at the loading point above the ship and equally at rest at the unloading point above the hopper. The trolley is also assumed to be at rest at both points. A complete model is presented for the crane system where the nonlinear dynamic equations are linearized for sufficiently small swing angles and then rewritten in dimensionless form. The minimum-time solution is sought by considering as control variables both the force applied on the trolley that produces its horizontal motion and the hoisting speed of the load as functions of time. A predictor-corrector iterative method using Linear Programming (LP) is proposed based on a discretetime model of the system where the control variables are taken as stepwise constants. At the corrector step, the hoisting motion is assumed given and a minimum-time solution is obtained by solving a sequence of LP problems representing fixed-time maximum-range problems. At the predictor step, a linearized model is employed to obtain an optimal correction of the hoisting motion using LP. The minimum-time control problem is formulated by taking into account practical constraints on the maximum speeds of both the trolley and the load hoisting, as well as on the maximum force that can be applied to the trolley. Numerical results are presented and show the effectiveness of the method.

O problema de transferir uma carga ao se movimentar num plano em tempo mínimo e sem oscilação no ponto de descarga, num guindaste portuário tipo pórtico é investigado neste trabalho. Assume-se que a carga esteja inicialmente em repouso na posição vertical no ponto de carga acima do navio e igualmente em repouso no ponto de descarga na moega de alimentação no porto. Assume-se também que o carro do guindaste esteja em repouso em ambos os pontos. Um modelo completo é apresentado para o sistema do guindaste onde as equações dinâmicas não-lineares são linearizadas para ângulos de oscilação pequenos o suficiente e reescritas para a forma adimensional. A solução de tempo mínimo é buscada considerando como variáveis de controle as funções do tempo que descrevem tanto a força aplicada no carro para produzir seu deslocamento horizontal, como a velocidade de içamento da carga. Um método iterativo preditor-corretor usando a Programação Linear (PL) é proposto, baseado no modelo do sistema de tempo discreto onde as variáveis de controle são tomadas constantes por trechos. Na etapa corretora, assume-se que o movimento de içamento é dado e uma solução de tempo mínimo é obtida resolvendo-se uma seqüência de problemas de PL de tempo fixo e máximo deslocamento. Na etapa preditora, um modelo linearizado é empregado para obter-se uma correção ótima do movimento de içamento usando a PL. O problema de controle de tempo mínimo é formulado levando-se em consideração restrições práticas na velocidade do carro do guindaste, velocidade máxima de içamento, assim como na máxima força que pode ser aplicada ao carro. Resultados numéricos são apresentados e mostram a efetividade do método. / The problem of minimum-time anti-swing transfer of a load in a ship-to-pier gantry crane is investigated in this work. The load is assumed to be initially at rest at the vertical position at the loading point above the ship and equally at rest at the unloading point above the hopper. The trolley is also assumed to be at rest at both points. A complete model is presented for the crane system where the nonlinear dynamic equations are linearized for sufficiently small swing angles and then rewritten in dimensionless form. The minimum-time solution is sought by considering as control variables both the force applied on the trolley that produces its horizontal motion and the hoisting speed of the load as functions of time. A predictor-corrector iterative method using Linear Programming (LP) is proposed based on a discretetime model of the system where the control variables are taken as stepwise constants. At the corrector step, the hoisting motion is assumed given and a minimum-time solution is obtained by solving a sequence of LP problems representing fixed-time maximum-range problems. At the predictor step, a linearized model is employed to obtain an optimal correction of the hoisting motion using LP. The minimum-time control problem is formulated by taking into account practical constraints on the maximum speeds of both the trolley and the load hoisting, as well as on the maximum force that can be applied to the trolley. Numerical results are presented and show the effectiveness of the method.

Can we reduce disturbance, swing, and errors by delegating some of the tasks to a subsystem on the tool hanging from a drone to gain precision and dependability? This project covers developing and implementing a user-controlled prototype with an automatic control system and gripper for functionality and controlled movement in 5 DOF. AirForestry is developing a new way of working in the forestry business to provide a greener and healthier solution for the soil and the environment. The forestry industry emits approximately one million tons of CO2 per year from heavy diesel-fueled vehicles. With a renewable energy battery-powered drone of a diameter of 6.2 m and a hanging harvesting tool, they can significantly improve the environmental impact of forestry. The harvesting tool has an automatic control system and is user controlled to perform the thinning and cutting of trees. The main focus is to use IMU sensor data to produce accurate angle estimation to control the stability of a scaled prototype and to implement physical restrictions to make it able to be attached safely and tested on a drone but not limit the controlled mobility of the prototype with a system independent of the control system of the drone itself. The user can control the attitude and elevation and receive real-time sensor data wireless during operation. With the intended spacing of the attachment points on the drone, it can prevent unwanted swing from a push or displaced drop. It uses the accelerometer on the IMUsensor to calculate the angle of roll and pitch, although the accelerometer is sensitive to vibrations and rotations. The control system has a fast response and rise time, but it experiences noise and oscillations. Sensor fusion of the accelerometer and gyroscope in a complementary filter can be implemented to increase the accuracy of the angle estimations and decrease the noise, which will be reflected in the speed of the servos and thereby improve the stability and mobility of the system.