In simulation studies, it is demonstrated that the tuning method converges to known analytical solutions for the feedback gain and the Kalman filter gain inthe state observer when the underlying system is known. Furthermore, a study of tuning of a system with parametric uncertainty of themodel parameters has shown that direct tuning of the feedback and the Kalman gains will improve closed loop performance compared to using the certainty equivalence design. The latter choice of tuning parameters is labeled a compensation strategy and will, in general, not lead to optimal performance due to the erroneous parameter estimates used inthe state estimator. A more promising strategy, labeled the adaptation strategy, tunes themodel parameter estimates and readjusts the feedback and observer gain to obtain certainty equivalence in all integrations. This approach will converge to optimal loop performance if themodel parameters converge to the system parameters. Hence, the adaptation strategy is superior to the compensation strategy.
of the array can be described by the inclusion of a distribu- tion of the coercive fields. This method has three important strenghtens; first the two assumptions are based on experi- mental evidence; second, it takes into account the intrinsic non-irreversible character of the hysteresis, and finally it gives an analytical description of theloop. The paper is organized as follows. In Sec. II, themodel is presented and the hysteresis loop of a Ni nanowire array is obtained. Finally, conclusions are presented in Sec. III.
This paper presents the integrated design and control of a buck boost converter (BBC). Inthe proposed methodology the design tool provides simultaneously the controller tuning and BBC design parameters in such a way that some closed- loop pre-specified static and dynamic behavior is obtained. This approach contrasts with the traditional methodology, where the design of BBC is performed without taking into ac- count its dynamical behavior. An optimization procedure is used to obtain the electronic components of the BBC and the tuning parameters of the controller, minimizing an objective function that considers the set of performance specifications. Although the methodology can be applied to any converter and any control strategy, in this particular case an ideal BBC and a Sliding Model Control (SMC) strategy are used. Some simulation results show the advantages and principally the flexibility that can be obtained with this approach.
accelerated the rate of ‘‘0’’ ! ‘‘1’’ substitutions at the second site, or conversely the odds that a ‘‘0’’ at one site became replaced by a ‘‘1’’ with respect to the presence or absence of a ‘‘1’’ at the second site of a pair. In other words, if e ¼ 1, then the paired model was effectively equivalent to a modelin which every site evolved independently. We simulated the evolution of binary sequences comprising 17 coevolving pairs of sites (i.e., f1, 2g, f3, 4g,..., f33, 34g) along the original neighbor-joining tree. Two hundred replicate alignments were generated in this fashion for a range of e parameter values. Each alignment was analyzed by the evolutionary- network method outlined above, i.e., by ﬁtting a model of independently evolving binary characters by maximum like- lihood, assigning substitution events to branches inthe tree, and analyzing the distribution of substitutions as a Bayesian network using an MCMC analysis. We recorded the frequency that edges inthe network with marginal posterior proba- bilities exceeding 0.95 recovered our predeﬁned paired interactions (true positives) or spurious ones (false positives). These results were contrasted with the rates of true and false positives obtained from using the Fisher exact test on the simulated binary sequence alignments (i.e., without correct- ing for the phylogeny). We chose the Fisher exact test as a representative example of pairwise association test statistics. Second, we simulated the evolution of nucleotide sequen- ces along the tree according to a more realistic codon substitution model whose parameters were estimated from the original alignment of V3 sequences. We randomly generated 100 replicate alignments with the same dimensions and characteristics (e.g., expected codon frequencies) as our observed V3 alignment by this method. Because the codon substitution model assumes that an alignment is a set of independently evolving codon sites , any signiﬁcant interactions between sites were false positives caused by founder effects inthe phylogeny. We evaluated the false- positive rate for our method against the rate for a more conventional pairwise association test, in which we applied the Fisher exact test to every pairwise combination of codon positions inthe simulated V3 loop sequences, enumerating consensus and nonconsensus residues to generate a 2 3 2 contingency table.
The presence of quadratic divergences inloop corrections to the scalar Higgs boson self-energy is responsible for the so-called hierarchy problem of the Standard Model (SM); namely, there is no natural way of having a “light” mass (i.e. ∼ 10 2 GeV) for the Higgs given that loop corrections induce mass terms of the order of the scale at which new physics enters– be it the GUT scale or any other above a few TeV. In Supersymmetric extensions this problem is absent since the divergence in bosons and fermions are related and the latter can only be logarithmic.. It is also absent in models where scalar particles are not fundamental but composite.
As seen in Figure 5, the V-model divides each phase of the control system lifecycle into elementary activities and balances each specification and design activity (left-hand activities, top-down) with an adequate and targeted test and verification activity (right- hand activities, bottom-up). The main verification activities on the left-hand side are design reviews and different desktop analyses. At the bottom level, the actual product is built in different modules and further integrated bottom-up on the right-hand side. At each level of integration some form of testing, such as internal module and integration testing and inthe end HIL testing and full-scale trials, is necessary to assure system integrity.
Our analysis has used a particular physical situation to emphasize the general feature that conclusions which are spurious and incompatible with observations can be obtained from theoretical analysis, if limited modeling is utilized for description of situations which are beyond the range of validity of a model, and that more accurate modeling can put the analysis back in consonance with observations. Other similar situations can be found in different physical contexts. For instance, some analogy can be found with a mechanical situation, related to the inertia of a body. The current does not diverge in a perfectly conducting loop of wire under the effect of an induced eletromotive force, due to the self-inductance, inthe same way as the velocity of a body does not
Abstract - Two multi-objective optimization based tuning methods for model predictive control are proposed. Both methods consider the minimization of the error between the closed-loop response and an output reference trajectory as tuning goals. The first approach is based on the ranking of the outputs according to their importance to the plant operation and it is solved by a lexicographic optimization algorithm. The second method solves a compromise optimization problem. The former is designed for systems in which the number of inputs is equal to the number of outputs, while the latter can also be applied to non-square systems. The main contribution is an automated tuning framework based on a straightforward goal definition. The proposed methods are tested on a finite horizon model predictive controller in closed-loop with a 3x3 subsystem of the Shell Heavy Oil Fractionator benchmark system. The simulation results show that the methods proposed here can be a useful tool to reduce the commissioning time of the controller. The methods are compared to an existing multi-objective optimization based tuning approach. The computational time required to run the proposed tuning algorithms is considerably reduced when compared to the existing approach and, moreover, it does not need an a posteriori decision to select a solution from a set of Pareto optimal solutions.
efficient technique for designing a robust controller can be alternatively used to design the robust controller for the system. Uncertainties in this approach are modeled as normalized co prime factors; this uncertainty model does not represent actual physical uncertainty, which usually is unknown in real problems. This technique requires only two specified weights, pre compensator and post compensator, for shaping the nominal plant so that the desired open loop shape is achieved. Fortunately, the selection of such weights is based on the concept of classical loop shaping which is a well known technique in controller design. By the reasons mentioned above, this technique is simpler and more intuitive than other robust control techniques. However, the controller designed by H ∞ loop shaping is still complicated and has high
PLB mIL-3 predominantly uses a slipknotting mechanism (Figure 5A) . However, we observe that the N-terminal PLBs with covalent loops $68 residues, predominantly use a plugging mechanism where the C-terminal inserts itself through its covalent loop. Hence, as theloop becomes larger/bigger, the mechanism switches from a slipknot- to a plugging mechanism. This is the first evidence, to date, that directly demonstrates a change in threading mechanism based on covalent loop length in structurally homologous proteins. Smaller covalent loops form more local native contacts with hairpins or turns because these structures allow for building up interaction surfaces that provide the driving force to pierce the lasso via a slipknotting mechanism. Therefore, slipknotting is more likely to occur when threading smaller covalent loops. Increasing the size of the covalent loop increases the ‘‘open’’ space inside the lasso. This leads to a larger number of possible conformations capable of threading a terminal and there are more possible entry encounters with the larger loop that will be productive. As the size of theloop becomes even bigger the terminal is no longer restricted by topological constraints. However in contrast to a polymer [17,36], which will perform a random motion without forming any native contacts, the protein terminal will make native contacts on the other side of loop and be stabilized, leading to a knot-like native conformation. We use a native-centric model although threading also involves many non- native interactions. It has indeed been shown that including non- native interactions inthemodel can facilitate knotting  and
Different from the studies carried out in de Oliveira et al. (2010b), in this work the methodology is also applied to tune AVRs. After generating parameter ranges just for PSSs, the approach was employed to generate parameter ranges just for AVRs (with nominal PSSs in operation, but with their param- eters unchanged) and also for AVRs and PSSs, simultane- ously. This evaluation took into account a minimum damp- ing ratio of 5% and the same operating conditions employed inthe previous test. Since the AVR gains are usually higher than the PSS gains, the calculation of the parameter ranges for the AVR consider gain deviations of 20 p.u. for the al- gorithm iterations (i.e., ∆ρ=20 p.u.). The nominal parame- ters of the AVRs employed inthemodel of test system 1 are Ke=200 p.u. and Te=0.01 s. Fig. 12 presents the parame- ter box determined for the simultaneous tuning of the AVRs placed in generators G1 and G3. The parameter box gener- ated for the simultaneous tuning of the AVR and PSS placed in generator G3 is presented in Fig. 13. Fig. 14 shows the eigenvalues related to the closed-loopmodel of test system 1, inthe base case operating condition, after the retuning of the AVR and PSS (different values of static gains belonging to the parameter box presented in Fig. 13 were considered).
which is due to the fact that the a priori information on the soil texture, taken from the FAO map, is in considerable agreement with the field measurements of grain size. In case that the FAO information would stronger deviate, much higher uncertainties inthemodel simulations can be expected. The soil moisture rms error as well as themodel efficiency for these open loop simulations are given in Table 2 for the upper (5 cm) and
The paper is organized according to the following out- line: in Sec. I, we present themodel, derive the Feynman rules, and calculate the one-loop effective potential; in Sec. II, we calculate the two-loop vacuum diagrams and show that, after integrating over the superspace coordi- nates, the remaining expressions are written in terms of usual space-time integrals; in Sec. III, we solve the space- time integrals and obtain the final expression for the renormalized two-loop effective potential. Concluding remarks are finally cast in Sec. IV. There follow two Appendices. In Appendix A, we present useful algebraic relations in superspace and explicitly calculate two of the superspace integrals presented in Sec. II. We collect inthe Appendix B some of the intermediate steps of our supergraph calculations, which may be helpful to get the final expressions reported in Sec. III.
On Example 8, the algorithm converged to the same model, irrespective of initial model. This is good news, because an iterative algorithm should preferably con- verge to the optimal solution, irrespective of initial val- ues. This is investigated further in Section 8 of exam- ples, see e.g., Tables 4 and 5. However, it is well known as described in Ljung (1999) on p.338 that e.g. the it- erative prediction error method only is guaranteed to converge to a local solution and to find the global solu- tion one have to start the iterations at different feasible initial values. On our MIMO Example 8.2 we observed that local solutions of the bootstrap subspace identifi- cation exists, and starting with a zero model for this example resulted in a biased model. However, starting with an initial model from the higher order ARX strat- egy resulted in a unbiased model with approximately as optimal parameter estimates as as the corresponding PEM estimates. This is further documented in Exam- ple 8.2.
The extreme diversity of HIV-1 strains presents a formidable challenge for HIV-1 vaccine design. Although antibodies (Abs) can neutralize HIV-1 and potentially protect against infection, antibodies that target the immunogenic viral surface protein gp120 have widely variable and poorly predictable cross-strain reactivity. Here, we developed a novel computational approach, the Method of Dynamic Epitopes, for identification of neutralization epitopes targeted by anti-HIV-1 monoclonal antibodies (mAbs). Our data demonstrate that this approach, based purely on calculated energetics and 3D structural information, accurately predicts the presence of neutralization epitopes targeted by V3-specific mAbs 2219 and 447-52D in any HIV-1 strain. The method was used to calculate the range of conservation of these specific epitopes across all circulating HIV-1 viruses. Accurately identifying an Ab-targeted neutralization epitope in a virus by computational means enables easy prediction of the breadth of reactivity of specific mAbs across the diversity of thousands of different circulating HIV-1 variants and facilitates rational design and selection of immunogens mimicking specific mAb-targeted epitopes in a multivalent HIV-1 vaccine. The defined epitopes can also be used for the purpose of epitope-specific analyses of breakthrough sequences recorded in vaccine clinical trials. Thus, our study is a prototype for a valuable tool for rational HIV- 1 vaccine design.
The endogenous time-keeping mechanism is responsible for organizing plant physiology and metabolism according to periodic environmental changes, such as diurnal cycles of light and dark and seasonal progression throughout the year. In plants, circadian rhythms control gene expression, stomatal opening, and the timing component of the photoperiodic responses, leading to enhanced fitness due to increased photosynthetic rates and biomass produc- tion. We have investigated the citrus genome databases of expressed sequence tags (EST) in order to identify genes coding for functionally characterized proteins involved inthe endogenous time-keeping mechanism in Arabidopsis thaliana. Approximately 180,000 EST sequences from 53 libraries were investigated and 81 orthologs of clock com- ponents were identified. We found that the vast majority of Arabidopsis circadian clock genes are present in citrus species, although some important components are absent such as SRR1 and PRR5. Based on the identified tran- scripts, a model for the endogenous oscillatory mechanism of citrus is proposed. These results demonstrate the power of comparative genomics between model systems and economically important crop species to elucidate sev- eral aspects of plant physiology and metabolism.
The first inputs to the structure are the afferent fibers bringing sensory information from different body structures. They enter BELBIC via thalamus and continue on to sensory cortex. In fact thalamus provides a coarse coding of the present sensory condition. This code enters both sensory cortex and amygdala. Sensory cortex provides more detailed analysis of the crude sensory information of thalamus and distributes the differentiated data to both amygdala and orbitofrontal cortex. The thalamus output is also projected to amygdala in order to help it produce a primary fast emotional reaction to the upcoming stimuli. Amygdale associates analyzed stimulus received from sensory cortex with an emotional value through classical emotional conditioning . This emotional value is assigned, based on the reinforcing signal (stress) that enters the structure from environment and its biological origin is not known . Since amygdale is incapable of forgetting the experienced emotional reaction once learned, orbitofrontal cortex takes the responsibility for correcting the unsatisfactory responses and inhibiting amygdala’s reactions. It controls extinguishment of learning in amygdale by responding to elimination of expected reward or punishment.
I think we can answer this question inthe positive: Yes, He can, because He is the most perfect being and His omnipotence is absolutely unlimited. A very important premise underlying the answer to the last question is that the risk is not so great, or even that it is very small. It is so because the nature and mechanism of the created world ensure with a very high proba- bility that all purposes intended by God will be attained without his causal action inthe processes occurring inthe world. The emergence of life inthe universe is almost inevitable, because the universe is large and old enough, and biochemical mechanisms are very effective. The emergence of sentient beings was also almost inevitable because of longstanding and countless mutations and adaptations of living organisms to their environment. All this was very probable and hence in a sense necessary (inevitable). The great advantage of the non-deterministic world is its own creativity, which is possible because of the chance events happening in a way restricted only by the laws of nature. Thus, if one evolutionary path fails another one is opened. Perhaps a mutation suitable for the growth and development of a given species happened by chance and enabled it to survive in hard con- ditions and further develop. Elasticity and redundancy are very typical for the world of chance, but because of these properties, this world has a large number of possibilities and abilities to develop and regenerate after various natural catastrophes (Łukasiewicz 2006).