Adaptive Regelung von Robotersystemen in Kontaktaufgaben

Contact Tasks of Robotic Systems, Mobile Legged Robots, Industrial Manipulators, Service Operations, Robot's Locomotion, Adaptive Control, Impedance/Force Control

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Millora experimental de les lleis de control predictiu aplicades sobre la plataforma PRIM I, per el seguiment de trajectòries

Aquest projecte s’aplica sobre el robot PRIM (Plataforma Robotitzada d’Informació Multimèdia), un robot autònom no humanoide creat el 2004 per Ateneu Informàtic (AI) que permet realitzar trajectòries 2D gràcies a un sistema de tracció format per dues rodes motrius propulsades independentment. La plataforma PRIM és controlada a partir del control predictiu, aquest control es va implementar en un projecte anterior, creat per l’Alexandre Blasco Gutierrez i titulat “Implementació de tècniques MPC (Model Predictiu Control) sobre la plataforma PRIM I”. El que es pretén en aquest projecte és millorar els resultats obtinguts en el passat projecte reformulant la llei de control i analitzar les discrepàncies obtingudes en les metodologies que s’utilitzen per minimitzar la funció de costos a partir de simulacions de trajectòries

Structural and mean level analyses of the Five-Factor Model and Locus of Control: Further evidence from Africa

The present study examines the Five-Factor Model (FFM) of personality and locus of control in French-speaking samples in Burkina Faso (N = 470) and Switzerland (Ns = 1,090, 361), using the Revised NEO Personality Inventory (NEO-PI-R) and Levenson's Internality, Powerful others, and Chance (IPC) scales. Alpha reliabilities were consistently lower in Burkina Faso, but the factor structure of the NEO-PI-R was replicated in both cultures. The intended three-factor structure of the IPC could not be replicated, although a two-factor solution was replicable across the two samples. Although scalar equivalence has not been demonstrated, mean level comparisons showed the hypothesized effects for most of the five factors and locus of control; Burkinabè scored higher in Neuroticism than anticipated. Findings from this African sample generally replicate earlier results from Asian and Western cultures, and are consistent with a biologically-based theory of personality.

New delay-dependent stability criteria for uncertain neutral systems with mixed time-varying delays and nonlinear perturbations

The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method

Control de glicèmia en pacients crítics mitjançant CGMS

L’estudi que es realitza en aquest projecte/treball final de carrera queda englobat dins del grup de recerca MICE (Modal Intervals Control and Engeneering), el qual realitzainvestigacions entorn al control de glucèmia. Aquest grup de recerca vinculat a la Universitat de Girona col•labora amb l’Hospital Universitari Dr. Josep Trueta de Girona. La temàtica principal tractarà de realitzar el control de glucèmia en pacients crítics, que es troben ingressats en la unitat de cures intensives de qualsevol hospital. Com a conseqüència d’aquesta problemàtica, s’ha implementat en un entorn virtual, un pacient el qual simula la situació d’un pacient real en la unitat de cures intensives. El model emprat per a la obtenció del model de pacient virtual és el desenvolupat per Chase et al. (2005), el qual mitjançant variables com l’alimentació enteral i la sensibilitat insulínica, es podien realitzar assajos reals per a validar protocols de control ‘in silico’ per posteriorment realitzar assajos amb població real

Mobile Robot Local Predictive Control under Perception Constraints

This research extends a previously developed work concerning about the use of local model predictive control in mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The platformused is a differential driven robot with a free rotating wheel. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are also introduced. In this sense, monocular image data provide an occupancy grid where safety trajectories are computed by using goal attraction potential fields

Mobile robot experimental modeling and control strategies using sensor fusion

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test thecontroller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in mealestimation

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Characterization and Control Strategies of an Integrated Chemical-Biological System for the Remediation of Toxic Pollutants in Wastewater: A case of study

In a previous work, a hybrid system consisting of an advanced oxidation process (AOP) named Photo-Fenton (Ph-F) and a fixed bed biological treatment operating as a sequencing batch biofilm reactor (SBBR) was started-up and optimized to treat 200 mg·L-1 of 4-chlorophenol (4-CP) as a model compound. In this work, studies of reactor stability and control as well as microbial population determination by molecular biology techniques were carried out to further characterize and control the biological reactor. Results revealed that the integrated system was flexible and even able to overcome toxic shock loads. Oxygen uptake rate (OUR) in situ was shown to be a valid tool to control the SBBR operation, to detect toxic conditions to the biomass, and to assess the recovery of performance. A microbial characterization by 16S rDNA sequence analysis reveals that the biological population was varied, although about 30% of the bacteria belonged to the Wautersia genus.

Linear-quadratic optimal control of descriptor systems

In recent years the analysis and synthesis of (mechanical) control systems in descriptor form has been established. This general description of dynamical systems is important for many applications in mechanics and mechatronics, in electrical and electronic engineering, and in chemical engineering as well. This contribution deals with linear mechanical descriptor systems and its control design with respect to a quadratic performance criterion. Here, the notion of properness plays an important role whether the standard Riccati approach can be applied as usual or not. Properness and non-properness distinguish between the cases if the descriptor system is exclusively governed by the control input or by its higher-order time-derivatives additionally. In the unusual case of non-proper systems a quite different problem of optimal control design has to be considered. Both cases will be solved completely.

Prediction of transients and control reactions in a transonic wind tunnel

This work describes a lumped parameter mathematical model for the prediction of transients in an aerodynamic circuit of a transonic wind tunnel. Control actions to properly handle those perturbations are also assessed. The tunnel circuit technology is up to date and incorporates a novel feature: high-enthalpy air injection to extend the tunnel’s Reynolds number capability. The model solves the equations of continuity, energy and momentum and defines density, internal energy and mass flow as the basic parameters in the aerodynamic study as well as Mach number, stagnation pressure and stagnation temperature, all referred to test section conditions, as the main control variables. The tunnel circuit response to control actions and the stability of the flow are numerically investigated. Initially, for validation purposes, the code was applied to the AWT ("Altitude Wind Tunnel" of NASA-Lewis). In the sequel, the Brazilian transonic wind tunnel was investigated, with all the main control systems modeled, including injection.

Cardiovascular control in experimental diabetes

Several studies have reported impairment in cardiovascular function and control in diabetes. The studies cited in this review were carried out from a few days up to 3 months after streptozotocin administration and were concerned with the control of the circulation. We observed that early changes (5 days) in blood pressure control by different peripheral receptors were maintained for several months. Moreover, the impairment of reflex responses observed after baroreceptor and chemoreceptor stimulation was probably related to changes in the efferent limb of the reflex arc (sympathetic and parasympathetic), but changes also in the central nervous system could not be excluded. Changes in renal sympathetic nerve activity during volume expansion were blunted in streptozotocin-treated rats, indicating an adaptive natriuretic and diuretic response in the diabetic state. The improvement of diabetic cardiovascular dysfunction induced by exercise training seems to be related to changes in the autonomic nervous system. Complementary studies about the complex interaction between circulation control systems are clearly needed to adequately address the management of pathophysiological changes associated with diabetes.