Margarita Mediavilla

Isolation of Multiplicative Faults in the Industrial Actuator Benchmark

Abstract This paper presents an approach to the problem of fault isolation applied to the actuator benchmark test based on multiplicative fault isolation with parity equations. One of the problems of this benchmark is relative to the isolation of a multiplicative fault from additive disturbances. The fact that a fault can be modelled as multiplicative is used to isolate it from additive disturbances. An optimization procedure gets the most suitable residuals for multiplicative fault isolation.

Optimization of collision free trajectories in multi-robot systems

This work describes a path planning method applied to a three robot system. Trajectories are optimized to allow minimum time performance of the overall system. Mathematical programming methods with a global approach are used.

Decision-Making Approaches for a Model-Based FDI Method

Abstract This paper describes three ways of building a decision system for quantitative model-based fault diagnosis. Some clues are given to apply the method to qualitative model-based FDI. The aim is the management of uncertain and redundant information provided by a residual generator. Although any residual generation method may be considered, the input-output parity equation approach has been used. The key point is the fault sensitivity estimations of the residuals. which lead to define the decision rules. In the case of sensor and actuator faults, sensitivity estimates are easily obtainable from the parity equations. Three ways to solve the decision problem are described: fuzzy logic-based, direct weighting of symptoms and directional properties. The proposed methods have been tested, first on simulation and then on two laboratory control equipments: 3-tanks system and d.c motor system.

Online motion planning for robotic arms: new approach based on the reduction of the search space

This paper presents a new method for online path planning for robotic arms in dynamic environments. Most online path planning methods are based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). The method presented in this paper avoids local minima by using a two stage framework. The robots react to dynamic environments using a local and reactive planning method restricted to a subset of its configuration space. Since the subset has few degrees of freedom the computational cost of the online stage is very low. An off-line stage chooses the subset of the configuration space that minimizes the probability of blockades and inefficient motions.

Selection of Strategies for Collision-free Motion in Multi-manipulator Systems

Strategy-based path planning was introduced by the authors as a way to give robotic manipulators some sort of reactive behaviour in dynamic and unpredictable environments. This approach is based on making robots react to moving obstacles using a restricted subset of the configuration space, and on using an off-line pre-planning stage to choose the restricted subset. In this paper, strategy-based path planning is applied and explored, focusing our attention on the off-line stage. It is applied to the joint motion of two and three robots that perform pick and place tasks sharing common working areas.

Reactive approach to on-line path planning for robot manipulators in dynamic environments

Path planning for robot manipulators is a complex subject, which is why most research has been restricted to static environments, where off-line path planning is acceptable, and very little work has been done on dynamic environments. On-line path planning is normally based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). In this paper we present a new method for on-line path planning in dynamic environments. It solves the lack of global vision of local methods by using a hybrid two stage framework that combines global and local planning.

REACTIVE PATH PLANNING FOR ROBOTIC ARMS WITH MANY DEGREES OF FREEDOM IN DYNAMIC ENVIRONMENTS

Abstract It is well known that path planning for robots with many degrees of freedom is a complex task. That is the reason why the research on this area has been mostly restricted to static environments. This paper presents a new method for on-line path planning for robotic arms in dynamic environments. Most on-line path planning methods are based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). The method presented in this paper avoids local minima by using a two stage framework. The robots react to dynamic environments using a local and reactive planning method restricted to a subset of its configuration space. Since the subset has few degrees of freedom the computational cost of the on-line stage is very low. An off-line stage chooses the subset of the configuration space that minimizes the probability of blockades and inefficient motions.

Application of fuzzy tools to the automatic analysis of system dynamics models: an example of World3

Abstract Even the simple run of a medium size system dynamics model can be a cumbersome process, since the uncertainty of the parameters forces the modeler to consider many runs before being confident of how the model behaves. System dynamics simulation packages include some analysis tools, but there is a lack of a commonly used analysis tool such as fuzzy clustering. In this paper, we explore the possibilities of a programming language, Matlab, and its simulation tool, Simulink, for the above mentioned possibilities. These languages enable the development of customized analysis tools at a very low programming cost. World3 model is a widely known example of a large model whose analysis becomes a difficult task. We have programmed this model in Simulink and, afterwards, some tools, such as fuzzy clustering and pathway participation metric (PPM), have been applied to show their potential capacity to facilitate model simulation analyses.

Influences of robot maintenance and failures in the performance of a multirobot system

In a multirobot system (MRS) several robots can operate simultaneously on the same product, and allow the accomplishment of tasks that a single robot could not approach due to restrictions associated to the product and/or the robot. We propose a MRS consisting of three robots and four different working platforms, that allows the characteristics of joint operation to be maintained even if a robot is out of service. In order to make a detailed analysis of the operating characteristics of the MRS we propose to use timed Petri nets (GSPN and DSPN), than allow the efficiency of the system to be evaluated. This paper analyses the influence of the robot maintenance and failures on the throughput of an MRS, under different conditions of operative configuration, number of subtasks, degree of interference, operation mode on the product, etc.

Fault diagnosis system based on sensitivity analysis and fuzzy logic

This paper describes three ways of building a decision system for model-based fault diagnosis. The aim is the management of uncertain and redundant information provided by a parity equation fault diagnosis method. Although any residual generation method may be considered, the input-output parity equation approach has been used. Sensitivity analysis is the key point in the evaluation of fault symptoms in order to obtain a final diagnosis. With this method, sensitivity estimates are easily obtainable by direct observation of the parity equations. Three ways to solve the decision problem are described: fuzzy logic-based, direct weighting of symptoms and directional properties. A simple simulated case has been used to prove its performance. Moreover, the fuzzy approach, that has showed to be the most robust of them, has been tested on a real laboratory equipment with similar results.