Essam Badreddin

Real-time Implementation of Fault-tolerant Control Using Model Predictive Control

Abstract Fault-tolerant control using model predictive control with online accommodation to recover from faults is investigated. A framework for this purpose is presented and problems that one encounters by changing the control law online like error-free tracking, feasibility and computational effort are addressed. In a real-time implementation, the model predictive controller is tested under actuator faults like saturation, freezing and total loss as well as under a structural fault.

Modified particle petri nets for hybrid dynamical systems monitoring under environmental uncertainties

A real-time system in its environment constitutes a complex dynamic system (in general hybrid), which requires the development of new methods of modeling and monitoring. This paper presents the Modified Particle Petri nets (MPPN) approach, which combines Petri nets and particle filtering in order to model and monitor Hybrid Dynamical Systems (HDS) and their interaction with the environment. The approach considers the uncertainty of the process on both discrete and continuous variables as well as the environmental uncertainties. It presents relevant concepts of Petri nets within a probabilistic framework and how uncertainty is introduced (i) in the hybrid marking of the Petri net in order to represent an uncertain knowledge about all next possible hybrid states (ii) as well as in the process noise, which is incorporated into the filter. A marking updating of the Petri nets according to noisy measurements made by the system and a decision making algorithm are then used in order to estimate the hybrid system state, to detect inconsistencies and to attribute these to different kinds of faults. An example of mobile robot application modeled using MPPN is presented to show the usability of the approach.

Comparing different holonomic mobile robots

This paper presents a comparison between three different holonomic mobile robots. The first has three caster wheels with wheel angular velocities actuation and carries the name C3P. The second is omni-directional wheeled mobile robot and the third is a special holonomic robot configuration developed by ETH named Ramsis II. Inverse kinematic and forward dynamic models are presented for each robot for the simulation process. The simulation results illustrate the performance of each robot in comparison to the others. The comparison is done with respect to three main aspects; 1) the mobility, 2)the total energy consumed by each robot in a finite interval of time, and 3) the hardware complexity. A cost functional is obtained to demonstrate the comparison, and a criteria is developed to measure the hardware complexity of each robot. The weight sum method enables the cost functional to show the importance of each aspect and to distinguish between the lowest cost platform with respect to each aspect importance.

Hybrid, recursive, nested monitoring of control systems using Petri nets and particle filters

In this paper we propose a recursive and nested hybrid monitoring and diagnosis architecture for systems with Recursive Nested Behaviour-based Control structure. Such systems consist of behavioural levels, which use several models on different levels of abstractions. In this architecture scheme, the monitors of each subsystem use recursively the output of the monitors of the next lower level in order to get an estimate of the global status of the system at each time and having the advantage of low dimensionality for each level. The proposed monitoring structure is based on hybrid Petri Nets and particle filters. The advantages of the approach are illustrated by an example for a Heating Control System.

Dynamic Model of a Holonomic Mobile Robot with Actuated Caster Wheels

A dynamic model for the holonomic mobile robot C3P is proposed. The C3P has three caster wheels with angular velocities actuation. The model consists of two main dynamic equations which have been derived symbolically using a Lagrange approach. The first equation is the forward dynamics which is used to calculate the wheels angular velocities corresponding to the applied torques on the wheels. The second equation is the steering dynamic estimator for recursive calculation of the steering angles and their derivatives with respect to the wheel angular velocities and acceleration. The velocity control of the C3P using the dynamic model is simulated and compared to the kinematics based controller which have been proposed earlier. The simulation and experimental results clearly show the advantages of the dynamic model in relation to the kinematic one

Individual ability-based system configuration cognitive profiling with Bayesian Networks

In this paper, we present a new method to model individual cognitive abilities, which were originally described by structural equation models and which can be used to reduce the possibility of human error when interacting with complex technical system. Our proposed model is based on hierarchical Bayesian networks and deals therefore with uncertain and noisy data. The validity of the method is demonstrated on the basis of simulations of real-life data. The inference from the Bayesian network demonstrates that estimating the users cognitive abilities is possible in a reliable manner in real-time. Structural and data dependency analyses further show that less evidence data are necessary to provide cognitive profile classification. This especially highlights the advantage of our new method in comparison to the - in psychology - traditionally used structural equation models. Such cognitive profiling will allow adapting a systems demand character to the cognitive ability level of an individual user, which will make operating that system less error-prone, as many human errors result out of systems requesting more cognitive abilities than the operator has available.

Controlling a Holonomic Mobile Robot With Singularities

In this paper a method is presented to control a holonomic mobile robot with singularities. The robot has 3 castor wheels, each wheel actuated by its angular velocity only. Using the proposed approach, singular wheel configurations are escaped without adding steering actuation to any wheel. The wheel coupling equation (WCE) virtually actuates the steering angular velocity of one wheel through controlling the actuated angular velocities of the other two wheels. Basing on the WCE and a cascaded control structure a standard wheel velocity controller is used to control the velocity of the robot. Simulations and practical experiments are carried out to illustrate the performance of the proposed approach and controller

Practical evaluation for two different holonomic wheeled mobile robots

This work is a practical evaluation between two different holonomic wheeled mobile robot platforms. The evaluation criteria had been theoretically explained and used on the simulation level in previous publication. The main objective of this paper is evaluating each wheeled mobile robot practically using the proposed criteria. The first robot is the C3P, which has three caster wheels with wheel angular velocities actuation. The second robot is omni-directional wheeled platform with three omni-directional wheels. The inverse and forward kinematics required in the control structure is presented for the practical experiments, which illustrate the performance of each robot. The comparison is done with respect to three main aspects; 1) the mobility, 2) the total energy consumed by each robot in a finite interval of time, and 3) the hardware complexity. A cost functional is obtained to demonstrate the comparison, and a criteria is developed to measure the hardware complexity of each robot. The weight sum method enables the cost functional to show the importance of each aspect and to distinguish between the lowest cost platform with respect to each aspect importance.

Entropy-based features for robust place recognition

In this paper, an appearance-based modeling of the environment is presented for the sake of mobile robot localization. The model allows perception and recognition within a topological context. Highly descriptive SIFT is used to extract local features from visual data acquired from an indoor environment. A method is developed to select those features, which are best for localization using a probabilistic modeling and an entropy measure. The impact of feature selection on the localization performance is more than 60% reduction in the storage and recognition time overhead. The methodology insures the recognition of different places with 96% precision, in spite of perceptual aliasing and image variability.

Mission-based online generation of probabilistic monitoring models for mobile robot navigation using Petri nets

This paper presents a generic hybrid monitoring approach, which allows the detection of inconsistencies in the navigation of autonomous mobile robots using online-generated models. A mission on the context of the navigation corresponds to an autonomous navigation from a start to an end mission point. The operator defines this mission by selecting a final goal point. Based on this selection the monitoring models for the current mission must be generated online. The originalities of this work are (i) the association of classic state estimation based on a particle filter with a special class of Petri net in order to deliver an estimation of the next robot state (position) as well as the environment state (graph nodes) and to use both pieces of information to distinguish between external noise influences, internal component faults and global behaviour inconsistency (ii) the integration of the geometrical and the logical environment representation into the monitor model (iii) the online generation of the corresponding monitoring model for the present mission trajectory while the system is running. The model takes simultaneously into account the uncertainty of the robot and of the environment through a unified modelling of both. To show the feasibility of the approach we apply it to an intelligent wheelchair (IWC) as a special type of autonomous mobile robot.