The longitudinal controller at DaimlerChrysler AG consists of two cascade controllers. The outer control loop contains the driver assistance functions such as speed limiter, cruise control, etc. The inner control loop consists of a PID-controller and an observer. The task of the observer is to estimate the part of the vehicle's acceleration caused by large disturbances, for example by a changed vehicle mass or the slope of the road. As observer the Kalman filter is selected. It is the optimal filter when the process model is linear and the process noise and measurement noise can be modeled as Gaussian noise. In this Master's thesis the theory for the Kalman filter is presented and it is shown how to choose the filter parameters. Simulated annealing is a global optimization technique which can be used when autotuning, i.e., automatically find the optimal parameter settings. To be able to perform autotuning for the longitudinal controller one has to model the environment and driving situations. In this Master's thesis it is verified that the parameter choice is a compromise between a fast but jerky, or a slow but smooth estimate. As the output from the Kalman filter is directly added to the control value for the engine and brakes, it is important that the output is smooth. It is shown that the Kalman filter implemented in the test vehicles today can be exchanged with a first-order lag function, without loss in performance. This makes the filter tuning easier, as there is only one parameter to choose. Change detection is a method that can be used to detect large changes in the signal, and react accordingly - for example by making the filter faster. A filter using change detection is implemented and simulations show that it is possible to improve the estimate using this method. It is suggested to implement the change detection algorithm in a test vehicle and evaluate it further.

We compare the use of stochastic dynamic programming (SDP), Neural Networks and a simple approximation rule for calculating the real option value of a flexible production system. While SDP yields the best solution to the problem, it is computationally prohibitive for larger settings. We test two approximations of the value function and show that the results are comparable to those obtained via SDP. These methods have the advantage of a high computational performance and of no restrictions on the type of process used. Our approach is not only useful for supporting large investment decisions, but it can also be applied in the case of routine decisions like the determination of the production program when stochastic profit margins occur. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Microstructural evolution in a naturally-aged and cold-rolled AA6451 aluminum alloy during a non-isothermal annealing process, which leads to significant grain refinement, is investigated through: (a) conducting a comprehensive experimental analysis and (b) developing a computational modeling technique. The underlying mechanisms of annealing have been investigated through analysing interactive phenomena between precipitation and concurrent recovery and recrystallization. It is shown that the interactions between solute elements, clusters, and fine precipitates with dislocations restrict dynamic and static recovery during deformation and subsequent annealing. Inhibition of recovery favours recrystallization that initiates at 300oC and progresses through a nucleation and growth mechanism. Despite localized inhomogeneities, nucleation mainly occurs in non-recovered high energy sites which are uniformly distributed within the entire structure. Growth of the recrystallized nuclei is restricted by pinning precipitates that undergo a concurrent coarsening process. The fine, uniform distribution of recrystallized nuclei and their limited growth result in the formation of a fine-grained microstructure, after completion of recrystallization. The acquired knowledge has been used to develop a computational modeling technique for simulating microstructural evolution of the alloy. Microstructural states are simulated by integrating analytical approaches in a Monte Carlo algorithm. The effects of deformation-induced and pre-existing inhomogeneities, as well as precipitate coarsening and grain boundary pinning on the competitive recovery-recrystallization process are included in the simulation algorithm. The developed technique is implemented to predict the microstructural evolution during isothermal and non-isothermal annealing of AA6xxx sheets. A good quantitative agreement is found between the model predictions and the results from the experimental investigations.

The Markov Chain Monte Carlo (MCMC) method has been widely used in practice since the 1950's in areas such as biology, statistics, and physics. However, it is only in the last few decades that powerful techniques for obtaining rigorous performance guarantees with respect to the running time have been developed. Today, with only a few notable exceptions, most known algorithms for approximately uniform sampling and approximate counting rely on the MCMC method. This thesis focuses on algorithms that use MCMC combined with an algorithm from optimization called simulated annealing, for sampling and counting problems. Annealing is a heuristic for finding the global optimum of a function over a large search space. It has recently emerged as a powerful technique used in conjunction with the MCMC method for sampling problems, for example in the estimation of the permanent and in algorithms for computing the volume of a convex body. We examine other applications of annealing to sampling problems as well as scenarios when it fails to converge in polynomial time. We consider the problem of randomly generating 0-1 contingency tables. This is a well-studied problem in statistics, as well as the theory of random graphs, since it is also equivalent to generating a random bipartite graph with a prescribed degree sequence. Previously, the only algorithm known for all degree sequences was by reduction to approximating the permanent of a 0-1 matrix. We give a direct and more efficient combinatorial algorithm which relies on simulated annealing. Simulated tempering is a variant of annealing used for sampling in which a temperature parameter is randomly raised or lowered during the simulation. The idea is that by extending the state space of the Markov chain to a polynomial number of progressively smoother distributions, parameterized by temperature, the chain could cross bottlenecks in the original space which cause slow mixing. We show that simulated tempering mixes torpidly for the 3-state ferromagnetic Potts model on the complete graph. Moreover, we disprove the conventional belief that tempering can slow fixed temperature algorithms by at most a polynomial in the number of temperatures and show that it can converge at a rate that is slower by at least an exponential factor.

In wireless positioning system, in addition to channel error, the geometric re- lationship between sensor nodes and the target may also affect the positioning accuracy. The effect is called geometric dilution of precision (GDOP). GDOP is determined as ratio factor between location error and measurement error. A higher GDOP value indicates a larger location error in location estimation. Accordingly, the location performance will be poor. The GDOP can therefore be used as an in- dex of the positioning performance. In this thesis, approaches of tracking a moving target with extended Kalman filter (EKF) in a time-difference-of-arrival (TDOA) wireless positioning system are discussed. While the target changes its position with time, the geometric layout between sensor nodes and the target will become differ- ent. To maintain the good layout, the positioning system with mobile sensor nodes is considered. Therefore, the geometric layout can be possibly improved and GDOP effect can be reduced by the mobility of mobile sensor nodes. In order to find the positions that mobile sensor nodes should move to, a time-varying function based on the GDOP distribution is defined for finding the best solutions. Since the simu- lated annealing is capable of escaping local minima and finding the global minimum in an objective function, the simulated annealing algorithm is used in finding the best solutions in the defined function. Thus the best solutions can be determined as the destinations of mobile sensor nodes. When relocating mobile sensor nodes from their current positions to the destinations, they may pass through or stay in high GDOP regions before arriving at the destinations. To avoid the problem, we establish an objective function for path planning of mobile sensor nodes in order to minimize the overall positioning accuracy. Simulation results show that the mobile sensor nodes will accordingly change their positions while the target is moving. All the sensor nodes will maintain a surrounding region to localize the target and the GDOP effect can be effectively reduced.

The roles of hydrogen induced defects in pure ZnO has been studied extensively. However, in a transition metal, such as Co, doped ZnO thin films the effect of hydrogen in electric conduction and magnetic coupling is still unclear and needs further study. Recently model predicts that hydrogen can be a shallow donor as well as an agent to induce ferromagnetism coupling between two adjacent Co ions which substitute the Zn sites at room temperature in a ZnO sample with a high Co doping ratio. However, the experimental supports is rare. In this study, Co-doped(5%) ZnO films are grown by a RF-magnetron sputtering system on glass substrate at room temperature. The growth condition is fixed for RF power in 200W, working press of 70 mtorr and various mixing ratio of H2/Ar+H2 gas. The crystal structure, electric and optical properties and the influence of vacuum annealing on the samples are studied. In this research, we found that the doping of hydrogen in Co-doped ZnO thin films truly increases the electric conductivity which is proportional to the H2/(Ar+H2) ratio. When the ratio of hydrogen is low, the (002) peak taken by a Glazing Angle X-ray Diffractometer dominates, while increasing hydrogen ratio other diffraction peaks appear, indicating an enhancement of crystal structure in all directions, and grain sizes and unit cell volume decrease. From the optical transmittance measurement, it is found that the color of films turned into metallic like and the optical band gap increases linearly with H2 ratio which can be attributed to the Burstein-Moss effect that corresponds to the increasing of carriers in the conduction band by doping of H2. The transmittance data provides the information of the ratio of crystalline and amorphous, which can also be correlated to the AFM results. When the H2 ratio is higher than 30%, more crystals and larger sizes of grains were formed in the films, such that carriers did not need to pass grain boundaries so frequently and experienced less scattering that was actually improve the electric conductivity. The electric conductivity can be even improved by post annealing in H2 environment. Moreover, the Magnetic circular dichroism (MCD) measurement shows that the Co2+ ions does truly substitute on Zn sited in Td symmetry during thin film deposition. The resistance measurement as a function of temperature found the hydrogenated Co-doped thin films are semiconductor conductive. More works are needed to determine the magnetization, identify second phases and Vo by SQUID and X-ray photoelectron spectroscopy.

The phase transformation of anodized Ti film has been studied. Although X-ray diffraction detected only the amorphous TiO2 phase, transmission electron microscopy analysis showed that TiO nanocrystallites less than 10 nm in size were also present, which was further supported by x-ray photoelectron spectroscopy analysis. Anatase was found to appear gradually by annealing the as-anodized specimen in air at 500¡V550 oC, which was accompanied by a simultaneous disappearance of TiO nanocrystallites. In contrast, only rutile is formed by annealing the Ti film at the same temperatures. The results indicate that TiO can induce the formation of anatase, which is explained by the close similarity between their structures. (Chapter 1) Anatase phase of TiO2 has been shown to have very good biocompability. It was frequently observed on Ti surfaces after anodizing and thermal annealing treatments. In this report the mechanisms of the Ti to TiO and the TiO to anatase phase transitions in anodizing and annealing treatments of Ti have been studied by transmission electron microscopy. Ti thin films of two strong textures were first grown on the (001)NaCl substrates. In addition to amorphous TiO2, the anodization treatment caused the formation of TiO with an orientation relationship of (11-20)Ti // (220)TiO with Ti. The subsequent thermal annealing treatment caused the TiO to anatase transition with an orientation relationship of {200}TiO //{200}A. Pure anatase film was prepared by this method. (Chapter 2)

In this work minimally supported D-optimal designs for response surface models with spatially correlated errors are studied. The spatially correlated errors describe the correlation between two measurements depending on their distance d through the covariance function C(d)=exp(-rd). In one dimensional design space, the minimally supported D-optimal designs for polynomial models with spatially correlated errors include two end points and are symmetric to the center of the design region. Exact solutions for simple linear and quadratic regression models are presented. For models with third or higher order, numerical solutions are given. While in two dimensional design space, the minimally supported D-optimal designs are invariant under translation¡Brotation and reflection. Numerical results show that a regular triangle on the experimental region of a circle is a minimally supported D-optimal design for the first-order response surface model.

¡@¡@This paper is refer to the chapter 1 to chapter 5 (except chapter 4 ) of the book, Monte Carlo Statistical Methods(second edition), the author is Robert and Casella(2004). The goal is to translate the chapter 1 to chapter 5 contents of this book into Chinese, modify the mistakes, add the details of the examples, translate the algorithm of the examples into Mathematica(7th) codes, and use the Simulated Annealing method to deal with the estimation of parameters by rounding data, and discuss the results. This paper provides Mathematica(7th) codes of almost every example, and show the actual results, so it can be regarded as a toolbook for those people who are interested in reading this book or may solve some problems related to those examples.

In this thesis, the problem of data transmission in amplify-and-forward (AF) co- operative system which implemented joint channel estimation and data detection at the destination (receiver) is considered. The nonlinear block code is designed to as- sist the above methodology. The design criterion takes into account the uncertainty of channel parameters at the receiver based on joint channel estimation and data detection algorithm and the simulations will prove that it can achieve full diversity that is offered by multiple relay and frequency-selective fading channel. Using an approximation of the union boun on the error probability as the design criterion, such that it can be simulated as a function for simulated annealing algorithm. The designed codewords are applied to the AF cooperative system. In order to assess the performance of joint estimation and detection fashion, the numerical simulations will be carried out the word error rate (WER) performances illustrate that improve- ment over differnt benchmark schemes can be obtained.