We review crane models available in the literature, classify them, and discuss their applications and limitations. A generalized formulation of the most widely used crane model is analyzed using th...

Dynamics and Control of Cranes: A Review:

Dynamical systems: stability, symbolic dynamics and chaos

Learning new motor tasks from physical interactions is an important goal for both robotics and machine learning. However, when moving beyond basic skills, most monolithic machine learning approaches fail to scale. For more complex skills, methods that are tailored for the domain of skill learning are needed. In this paper, we take the task of learning table tennis as an example and present a new framework that allows a robot to learn cooperative table tennis from physical interaction with a human. The robot first learns a set of elementary table tennis hitting movements from a human table tennis teacher by kinesthetic teach-in, which is compiled into a set of motor primitives represented by dynamical systems. The robot subsequently generalizes these movements to a wider range of situations using our mixture of motor primitives approach. The resulting policy enables the robot to select appropriate motor primitives as well as to generalize between them. Finally, the robot plays with a human table tennis partner and learns online to improve its behavior. We show that the resulting setup is capable of playing table tennis using an anthropomorphic robot arm.

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Learning to select and generalize striking movements in robot table tennis

This paper applies a probabilistic power flow (PPF) algorithm to evaluate the influence of photovoltaic (PV) generation uncertainty on transmission system performance. PV generation has the potential to cause a significant impact on power system reliability in the near future. A cumulant-based PPF algorithm suitable for large systems is used to avoid convolution calculations. Correlation among input random variables is considered. Specifically correlation between adjacent PV resources are considered. Three types of approximation expansions based on cumulants, namely the Gram-Charlier expansion, the Edgeworth expansion, and the Cornish-Fisher expansion, are compared, and their properties, advantages, and deficiencies are discussed. Additionally, a novel probabilistic model of PV generation is developed to obtain the probability density function (PDF) of the PV generation production based on the environmental conditions. The proposed approaches with the three expansions are compared with Monte Carlo simulations (MCS) with results for a 2497-bus representation of the Arizona area of the Western Electricity Coordinating Council (WECC) system.

Probabilistic Power Flow Studies for Transmission Systems With Photovoltaic Generation Using Cumulants

Effects of hoisting on the input shaping control of gantry cranes

In the following work the hybrid systems with base in the renewable energy (RE) are modeled to compare many different design options based on their technical and economic merits. The power requirements will be guaranteed to reverse osmosis Autonomous Desalination Systems (ADS), with a capacity of up to 50 m3 of daily production. The HOMER Hybrid Optimization Model Tool has been used to create optimal designs for these renewable energy systems. The input assumptions in the model were: the electric demand of the desalination plant, the technical specifications of the equipments, as well as the potentials of solar radiation and the wind speeds. Although this study could be applied to different scenarios where an isolated system is found, in this work it has been applied to two islands. In particular these islands have got a relative high wind profile, along with a high a solar radiation profile. Several configurations have been considered by this simulation software and different optimal results attending to the use of renewable energy have been obtained for this particular case. In fact, real data from two particular islands (Lanzarote and Fuerteventura) have been used, although the results could be extent to other similar scenarios.

Assessment of hybrid renewable energy systems to supplied energy to autonomous desalination systems in two islands of the canary archipelago.

In this paper, a low-cost robot capable of playing ping-pong against human opponent using a vision system to detect the ball is presented. In the subsequent sections, the three main subsystems of the robot, i.e., the vision system, mechanical structure, and the control systems, are described. A prototype has been designed with lightweight and resistant materials to increase the response time and accurateness of the shot. One of the important features of this system is that it uses only one camera to detect the ball, thus reducing the computational time and hardware requirements. To detect the location of the ball, the robot combines the information about the ball and about the shadow it casts on the table. The expert module control defines the game strategy. Orienting the bat in order to return the ball to the desired position on the table does this. In these experiments, the success rate in returning balls was greater than 80%.

Ping-pong player prototype

Obstacle avoidance for a mobile robot: A neuro-fuzzy approach

A neural network-based self-tuning controller is presented. The scheme of the controller is based on using a multilayer perceptron, or a set of them, as a self-tuner for a controller. The method proposed has the advantage that it is not necessary to use a combined structure of identification and decision, common in a standard self-tuning controller. The paper explains the algorithm for a general case, and then a specific application on a nonlinear plant is presented. The plant is an overhead crane which involves an interesting control problem related to the oscillations of the load mass. The method proposed is tested by simulation in different conditions. A comparison was made with a conventional controller to evaluate the efficiency of the algorithm.

G.N. Marichal

Papers

Assessment of hybrid renewable energy systems to supplied energy to autonomous desalination systems in two islands of the canary archipelago.

Ping-pong player prototype

Obstacle avoidance for a mobile robot: A neuro-fuzzy approach

An Application of a Neural Self-Tuning Controller to an Overhead Crane

A self-tuning neuromorphic controller: application to the crane problem