Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a gradient descent algorithm. The proposed discrete control is robust against all uncertainties as verified by stability analysis. The proposed robust control law is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results show the effectiveness of the control approach

Rigidity of a Column-Foundation Connection for Guadua angustifolia Kunth Structures

Una de las limitantes que encuentran los ingenieros estructurales para el diseño de una edificación y, en general, de cualquier estructura en Guadua angustifolia Kunth es la falta de información técnica relacionada con los parámetros necesarios para realizar un adecuado modelo numérico de esta. El grado de empotramiento que puede brindar un apoyo al elemento estructural que soporta es una variable importante durante la modelación estructural, debido a que el criterio del ingeniero en la selección de este parámetro para la modelación puede incidir en la rigidez de la estructura y, por tanto, en su periodo de vibración. En este artículo se presentan los resultados experimentales de la constante de rigidez de una conexión entre una columna de Guadua angustifolia Kunth y un elemento de concreto que forma parte de la fundación, cuando la columna está solicitada a cargas laterales monotónicas. Adicionalmente, se ha evaluado la incidencia de cada uno de los componentes de la conexión en la rigidez de la estructura.One of the limitations structural engineers face when designing a building and, in general, any structure in Guadua angustifolia Kunth is the lack of technical information related to the parameters needed for a proper numerical model of the same. The degree of embedding that can provide support to its structural element is an important variable during structural modeling, because the judgment of the engineer in the selection of this parameter for modeling can influence the rigidity of the structure and, therefore, its period of vibration. This paper presents the experimental results of the constant of rigidity of a connection between a Guadua angustifolia Kunth column and a concrete element that is part of the foundation, when the column is under monotonic lateral loads. Additionally, the impact of each component of the connection on the rigidity of the structure has been evaluatedUma das limitações que os engenheiros estruturais encontram para o desenho de uma edificação e, em geral, de qualquer estrutura em Guadua angustifolia Kunth é a falta de informação técnica relacionada com os parâmetros necessários para realizar um adequado modelo numérico desta. O grau de incorporação que pode oferecer um apoio ao elemento estrutural que sustenta é uma variante importante durante a modelação estrutural, devido a que o critério do engenheiro na seleção deste parâmetro para a modelação pode incidir na rigidez da estrutura e, portanto, em seu período de vibração. Neste artigo se apresentam os resultados experimentais da constante de rigidez de uma conexão entre uma coluna de Guadua angustifolia Kunth e um elemento de concreto que faz parte da fundação, quando a coluna está solicitada a cargas laterais monotônicas. Adicionalmente, avaliou-se a incidência de cada um dos componentes da conexão na rigidez da estrutura

Bipedal Robotic Walking on Flat-Ground, Up-Slope and Rough Terrain with Human-Inspired Hybrid Zero Dynamics

The thesis shows how to achieve bipedal robotic walking on flat-ground, up-slope and rough terrain by using Human-Inspired control. We begin by considering human walking data and find outputs (or virtual constraints) that, when calculated from the human data, are described by simple functions of time (termed canonical walking functions). Formally, we construct a torque controller, through model inversion, that drives the outputs of the robot to the outputs of the human as represented by the canonical walking function; while these functions fit the human data well, they do not apriori guarantee robotic walking (due to do the physical differences between humans and robots). An optimization problem is presented that determines the best fit of the canonical walking function to the human data, while guaranteeing walking for a specific bipedal robot; in addition, constraints can be added that guarantee physically realizable walking. We consider a physical bipedal robot, AMBER, and considering the special property of the motors used in the robot, i.e., low leakage inductance, we approximate the motor model and use the formal controllers that satisfy the constraints and translate into an efficient voltage-based controller that can be directly implemented on AMBER. The end result is walking on flat-ground and up-slope which is not just human-like, but also amazingly robust. Having obtained walking on specific well defined terrains separately, rough terrain walking is achieved by dynamically changing the extended canonical walking functions (ECWF) that the robot outputs should track at every step. The state of the robot, after every non-stance foot strike, is actively sensed and the new CWF is constructed to ensure Hybrid Zero Dynamics is respected in the next step. Finally, the technique developed is tried on different terrains in simulation and in AMBER showing how the walking gait morphs depending on the terrain

Design and Implementation of Voltage Based Human Inspired Feedback Control of a Planar Bipedal Robot AMBER

This thesis presents an approach towards experimental realization of underactuated bipedal robotic walking using human data. Human-inspired control theory serves as the foundation for this work. As the name, "human-inspired control," suggests, by using human walking data, certain outputs (termed human outputs) are found which can be represented by simple functions of time (termed canonical walking functions). Then, an optimization problem is used to determine the best fit of the canonical walking function to the human data, which guarantees a physically realizable walking for a specific bipedal robot. The main focus of this work is to construct a control scheme which takes the optimization results as input and delivers human-like walking on the real-world robotic platform - AMBER. To implement the human-inspired control techniques experimentally on a physical bipedal robot AMBER, a simple voltage based control law is presented which utilizes only the human outputs and canonical walking function with parameters obtained from the optimization. Since this controller does not require model inversion, it can be implemented efficiently in software. Moreover, applying this methodology to AMBER, experimentally results in robust and efficient "human-like" robotic walking

Path Following for Robot Manipulators Using Gyroscopic Forces

This thesis deals with the path following problem the objective of which is to make the end effector of a robot manipulator trace a desired path while maintaining a desired orientation. The fact that the pose of the end effector is described in the task space while the control inputs are in the joint space presents difficulties to the movement coordination. Typically, one needs to perform inverse kinematics in path planning and inverse dynamics in movement execution. However, the former can be ill-posed in the presence of redundancy and singularities, and the latter relies on accurate models of the manipulator system which are often difficult to obtain. This thesis presents an alternative control scheme that is directly formulated in the task space and is free of inverse transformations. As a result, it is especially suitable for operations in a dynamic environment that may require online adjustment of the task objective. The proposed strategy uses the transpose Jacobian control (or potential energy shaping) as the base controller to ensure the convergence of the end effector pose, and adds a gyroscopic force to steer the motion. Gyroscopic forces are a special type of force that does not change the mechanical energy of the system, so its addition to the base controller does not affect the stability of the controlled mechanical system. In this thesis, we emphasize the fact that the gyroscopic force can be effectively used to control the pose of the end effector during motion. We start with the case where only the position of the end effector is of interest, and extend the technique to the control over both position and orientation. Simulation and experimental results using planar manipulators as well as anthropomorphic arms are presented to verify the effectiveness of the proposed controller