Advanced Control Strategies for a 6 DoF Hydraulic Parallel Robot Based on the Dynamic Model

Nowadays robots have made their way into real applications that were prohibitive and unthinkable thirty years ago. This is mainly due to the increase in power computations and the evolution in the theoretical field of robotics and control. Even though there is plenty of information in the current literature on this topics, it is not easy to find clear concepts of how to proceed in order to design and implement a controller for a robot. In general, the design of a controller requires of a complete understanding and knowledge of the system to be controlled. Therefore, for advanced control techniques the systems must be first identified. Once again this particular objective is cumbersome and is never straight forward requiring of great expertise and some criteria must be adopted. On the other hand, the particular problem of designing a controller is even more complex when dealing with Parallel Manipulators (PM), since their closed-loop structures give rise to a highly nonlinear system. Under this basis the current work is developed, which intends to resume and gather all the concepts and experiences involve for the control of an Hydraulic Parallel Manipulator. The main objective of this thesis is to provide a guide remarking all the steps involve in the designing of advanced control technique for PMs. The analysis of the PM under study is minced up to the core of the mechanism: the hydraulic actuators. The actuators are modeled and experimental identified. Additionally, some consideration regarding traditional PID controllers are presented and an adaptive controller is finally implemented. From a macro perspective the kinematic and dynamic model of the PM are presented. Based on the model of the system and extending the adaptive controller of the actuator, a control strategy for the PM is developed and its performance is analyzed with simulation.

Controle de um pêndulo invertido com 6 graus de liberdade e rodas de reação.

Nesta dissertação, um tipo diferente de pêndulo invertido controlado por rodas de reação é apresentado. Sua principal diferença está em seu ponto de articulação, que é constituído por uma junta esférica que permite com que o pêndulo gire em torno de seus três eixos. Além disso, três rodas de reação são utilizadas para seu controle e estabilização. Primeiramente, um modelo do sistema é obtido a partir das equação de Euler-Lagrange, das leis de Newton e das leis de Kirchhoff. Em seguida, uma lei de controle que assegura a estabilização assintótica do sistema em um grande domínio é proposta. Por fim, simulações são realizadas para validar o controlador projetado. Esse sistema possui diversas características interessantes, tanto do ponto de vista teórico como do ponto de vista de pesquisa. Do ponto de vista teórico, o sistema é nãolinear e suas entradas são fortemente acopladas, o que torna particularmente adequado para o processo de projeto e implementação de diversas técnicas de estabilização. Do ponto de vista de pesquisa, são consideradas duas técnicas de controle não linear: linearização padrão e linearização exata. Para que o sistema seja robusto e não desperdice energia, essas duas leis de controle diferentes são comutadas para a obtencão de um número suficiente de domínio de estabilidade.

The lattice solid model to simulate the physics of rocks and earthquakes: Incorporation of friction

The particle-based lattice solid model developed to study the physics of rocks and the nonlinear dynamics of earthquakes is refined by incorporating intrinsic friction between particles. The model provides a means for studying the causes of seismic wave attenuation, as well as frictional heat generation, fault zone evolution, and localisation phenomena. A modified velocity-Verlat scheme that allows friction to be precisely modelled is developed. This is a difficult computational problem given that a discontinuity must be accurately simulated by the numerical approach (i.e., the transition from static to dynamical frictional behaviour). This is achieved using a half time step integration scheme. At each half time step, a nonlinear system is solved to compute the static frictional forces and states of touching particle-pairs. Improved efficiency is achieved by adaptively adjusting the time step increment, depending on the particle velocities in the system. The total energy is calculated and verified to remain constant to a high precision during simulations. Numerical experiments show that the model can be applied to the study of earthquake dynamics, the stick-slip instability, heat generation, and fault zone evolution. Such experiments may lead to a conclusive resolution of the heat flow paradox and improved understanding of earthquake precursory phenomena and dynamics. (C) 1999 Academic Press.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.

Wave chaotic behaviour generated by linear systems

It is shown that regimes with dynamical chaos are inherent not only to nonlinear system but they can be generated by initially linear systems and the requirements for chaotic dynamics and characteristics need further elaboration. Three simplest physical models are considered as examples. In the first, dynamic chaos in the interaction of three linear oscillators is investigated. Analogous process is shown in the second model of electromagnetic wave scattering in a double periodical inhomogeneous medium occupying half-space. The third model is a linear parametric problem for the electromagnetic field in homogeneous dielectric medium which permittivity is modulated in time. © 2008 Springer Science+Business Media, LLC.

A probabilistic indirect adaptive control for systems with input-dependent noise

A probabilistic indirect adaptive controller is proposed for the general nonlinear multivariate class of discrete time system. The proposed probabilistic framework incorporates input–dependent noise prediction parameters in the derivation of the optimal control law. Moreover, because noise can be nonstationary in practice, the proposed adaptive control algorithm provides an elegant method for estimating and tracking the noise. For illustration purposes, the developed method is applied to the affine class of nonlinear multivariate discrete time systems and the desired result is obtained: the optimal control law is determined by solving a cubic equation and the distribution of the tracking error is shown to be Gaussian with zero mean. The efficiency of the proposed scheme is demonstrated numerically through the simulation of an affine nonlinear system.

The B-Terminal Busy Probability Prediction

In the teletraffic engineering of all the telecommunication networks, parameters characterizing the terminal traffic are used. One of the most important of them is the probability of finding the called (B-terminal) busy. This parameter is studied in some of the first and last papers in Teletraffic Theory. We propose a solution in this topic in the case of (virtual) channel systems, such as PSTN and GSM. We propose a detailed conceptual traffic model and, based on it, an analytical macro-state model of the system in stationary state, with: Bernoulli– Poisson–Pascal input flow; repeated calls; limited number of homogeneous terminals; losses due to abandoned and interrupted dialling, blocked and interrupted switching, not available intent terminal, blocked and abandoned ringing and abandoned conversation. Proposed in this paper approach may help in determination of many network traffic characteristics at session level, in performance evaluation of the next generation mobile networks.

Activated escape from polarization pulling in fibre Raman amplifiers

Fluctuation-induced escape (FIE) from a metastable state with probability controlled by external force is a process inherent in many physical phenomena such as diffusion in crystals, protein folding, activated chemical reactions etc. [1-3]. In this work we present a novel example of FIE problem, considering a very practical nonlinear system recently emerged in the area of fibre telecommunications. Unlike the standard FIE problems where noise is time-dependent, in fibre Raman amplifier (FRA) the role of noise is played by frozen fluctuations of parameters (random birefringence) along the fibre span which result from the breaking of cylindrical symmetry during the fibre drawing [4-6]. The role of periodic forcing in this problem is played by the periodic fibre spinning, leading to key model that is formally similar to the time-domain equations for periodically forced escape [1-3]. © 2011 IEEE.

Investigation and modelling of tremor reducer with the technology of targeted energy transfer

This thesis presents the study of a two-degree-of-freedom (2 DOF) nonlinear system consisting of two grounded linear oscillators coupled to two separate light weight nonlinear energy sinks of an essentially nonlinear stiffness. In this thesis, Targeted Energy Transfer (TET) and NES concept are introduced. Previous studies and research of Energy pumping and NES are presented. The characters in nonlinear energy pumping have been introduced at the start of the thesis. For the aim to design the application of a tremor reduction assessment device, the knowledge of tremor reduction has also been mentioned. Two main parties have been presented in the research: dynamical theoretic method of nonlinear energy pumping study and experiments of nonlinear vibration reduction model. In this thesis, nonlinear energy sink (NES) has been studied and used as a core attachment for the research. A new theoretic method of nonlinear vibration reduction which with two NESs has been attached to a primary system has been designed and tested with the technology of targeted energy transfer. Series connection and parallel connection structure systems have been designed to run the tests. Genetic algorithm has been used and presented in the thesis for searching the fit components. One more experiment has been tested with the final components. The results have been compared to find out most efficiency structure and components for the theoretic model. A tremor reduction experiment has been designed and presented in the thesis. The experiment is for designing an application for reducing human body tremor. By using the theoretic method earlier, the experiment has been designed and tested with a tremor reduction model. The experiment includes several tests, one single NES attached system and two NESs attached systems with different structures. The results of theoretic models and experiment models have been compared. The discussion has been made in the end. At the end of the thesis, some further work has been considered to designing the device of the tremor reduction.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Effect of road quality in structural health monitoring under operational conditions

The effect of unevenness in a bridge deck for the purpose of Structural Health Monitoring (SHM) under operational conditions is studied in this paper. The moving vehicle is modelled as a single degree of freedom system traversing the damaged beam at a constant speed. The bridge is modelled as an Euler-Bernoulli beam with a breathing crack, simply supported at both ends. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. The unevenness in the bridge deck considered is modelled using road classification according to ISO 8606:1995(E). Numerical simulations are conducted considering the effects of changing road surface classes from class A - very good to class E - very poor. Cumulant based statistical parameters, based on a new algorithm are computed on stochastic responses of the damaged beam due to passages of the load in order to calibrate the damage. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are considered. The findings of this paper are important for establishing the expectations from different types of road roughness on a bridge for damage detection purposes using bridge-vehicle interaction where the bridge does not need to be closed for monitoring.

Effects of vehicle speed in structural health monitoring from operational conditions of bridges

The effects of vehicle speed for Structural Health Monitoring (SHM) of bridges under operational conditions are studied in this paper. The moving vehicle is modelled as a single degree oscillator traversing a damaged beam at a constant speed. The bridge is modelled as simply supported Euler-Bernoulli beam with a breathing crack. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. The unevenness of the bridge deck is modelled using road classification according to ISO 8606:1995(E). The stochastic description of the unevenness of the road surface is used as an aid to monitor the health of the structure in its operational condition. Numerical simulations are conducted considering the effects of changing vehicle speed with regards to cumulant based statistical damage detection parameters. The detection and calibration of damage at different levels is based on an algorithm dependent on responses of the damaged beam due to passages of the load. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are considered. Sensitivity of calibration values is studied. The findings of this paper are important for establishing the expectations from different vehicle speeds on a bridge for damage detection purposes using bridge-vehicle interaction where the bridge does not need to be closed for monitoring. The identification of bunching of these speed ranges provides guidelines for using the methodology developed in the paper.

Unknown input observer design for one-sided Lipschitz discrete-time systems subject to time-delay

In this paper, we address the problem of unknown input observer design, which simultaneously estimates state and unknown input, of a class of nonlinear discrete-time systems with time-delay. A novel approach to the state estimation problem of nonlinear systems where the nonlinearities satisfy the one-sided Lipschitz and quadratically inner-bounded conditions is proposed. This approach also allows us to reconstruct the unknown inputs of the systems. The nonlinear system is first transformed to a new system which can be decomposed into unknown-input-free and unknown-input-dependent subsystems. The estimation problem is then reduced to designing observer for the unknown-input-free subsystem. Rather than full-order observer design, in this paper, we propose observer design of reduced-order which is more practical and cost effective. By utilizing several mathematical techniques, the time-delay issue as well as the bilinear terms, which often emerge when designing observers for nonlinear discrete-time systems, are handled and less conservative observer synthesis conditions are derived in the linear matrix inequalities form. Two numerical examples are given to show the efficiency and high performance of our results.

Onset And Characterisation Of Chaos In A Two Dimensional Nonlinear Deterministic Model

Nature is full of phenomena which we call "chaotic", the weather being a prime example. What we mean by this is that we cannot predict it to any significant accuracy, either because the system is inherently complex, or because some of the governing factors are not deterministic. However, during recent years it has become clear that random behaviour can occur even in very simple systems with very few number of degrees of freedom, without any need for complexity or indeterminacy. The discovery that chaos can be generated even with the help of systems having completely deterministic rules - often models of natural phenomena - has stimulated a lo; of research interest recently. Not that this chaos has no underlying order, but it is of a subtle kind, that has taken a great deal of ingenuity to unravel. In the present thesis, the author introduce a new nonlinear model, a ‘modulated’ logistic map, and analyse it from the view point of ‘deterministic chaos‘.