IMPROVEMENT OF BIOGAS PRODUCTION IN ANAEROBIC DIGESTION PROCESS

The production of biogas enables environmental preservation and sustainable development of rural areas and landlocked regions, as well as diversification of renewable energy resources. This paper is a contribution to improving the production of biogas by Sliding Mode Control (SMC). In the literature there are many models describing the behaviour of reactions during anaerobic digestion and used for control design. The AM2 model is one of the simplest models and can be exploited easily for the control design purposes. In this paper, the reduced model AM2 was exploited to develop and testing by simulations the robust control law SMC. The results obtained have proved the effectiveness of the control method proposed in this paper. A study of the robustness for monitoring and disturbances rejection demonstrated the great interest of this method, which is a non-linear technique and gives very good results in terms of robustness but it presents the problem of chattering. In practice, the chattering of the control action can cause premature wear of the actuators or parts of the system due to heavy oscillations. The chattering phenomenon is caused by the discontinuous term which appears in the control signal. This paper presents a solution to the chattering problem by replacing the discontinuous term with a continuous one. Different Simulations and comparisons are presented and interpreted with satisfactory results.

Performance of the Boost Converter Controlled with ZAD to Regulate DC Signals

This paper presents the performance of a boost converter controlled with a zero average dynamics technique to regulate direct current signals. The boost converter is modeled in a compact form, and a variable change is performed to depend only on the γ parameter. A new sliding surface is proposed, where it is possible to regulate both the voltage and the current with low relative errors with respect to the reference signals. It is analytically demonstrated that the approximation of the switching surface by a piecewise linear technique is efficient in controlling the system. It is shown numerically that for certain operating conditions, the system is evolved into a chaotic attractor. The zero average dynamics technique implemented in the boost converter has good regulation, due to the presence of zones in the bi-parametric space. Furthermore, the zero average dynamics technique regulates the voltage well and presents a chaotic attractor with low steady-state error.

Ltspice Simulation of Non Linear Technique SSHI Serial and SSHI Parallel of Piezoelectric Vibration Energy Harvesting

in this paper, a simple but effective proposal for piezoelectric energy collectors. synchronized switching harvesting in the SSIH technique (synchronized switch harvesting on parallel inductor consists in placing a switch which will be commanded on closing at the instant when the amplitude of the vibrations passes through the extreme this technique makes it possible to increase the power harvested from a ratio of 8 compared to the power of a harvester based on ac dc converter similarly the SSIH command (synchronized switch harvesting on inductor for LT SPICEs-based simulations of the two techniques is carried out finally a comparison with respect to the standard structure of energy harvesting is made in order to validate theoretical concepts

A Comparison of Linear and Non-Linear Machine Learning Techniques (PCA and SOM) for Characterizing Urban Nutrient Runoff

Urban stormwater runoff represents a significant challenge for the practical assessment of diffuse pollution sources on receiving water bodies. Given the high dimensionality of the problem, the main goal of this study was the comparison of linear and non-linear machine learning (ML) methods to characterize urban nutrient runoff from impervious surfaces. In particular, the principal component analysis (PCA) for the linear technique and the self-organizing map (SOM) for the non-linear technique were chosen and compared considering the high number of successful applications in the water quality field. To strengthen this comparison, these techniques were supported by well-known linear and non-linear methods. Those techniques were applied to a complete dataset with precipitation, flow rate, and water quality (sediments and nutrients) records of 577 events gathered for a watershed located in Southern Italy. According to the results, both linear and non-linear techniques can represent build-up and wash-off, the two main processes that characterize urban nutrient runoff. In particular, non-linear methods are able to capture and represent better the rainfall-runoff process and the transport of dissolved nutrients in urban runoff (dilution process). However, their computational time is higher than the linear technique (0.0054 s vs. 15.24 s, for linear and non-linear, respectively, in our study). The outcomes of this study provide significant insights into the application of ML methods for the water quality field.

Limit Law of the Local Linear Estimate of the Conditional Hazard Function for Functional Data

In this work, we treat a prediction problem via the conditional hazard function of a scalar response variable Y given a functional random variable X by using the local linear technique. The main purpose of this paper is to investigate the asymptotic normality of the nonparametric estimator of the conditional hazard function, under some general conditions. A simulation study, conducted to assess finite sample behavior, demonstrates the superiority of our method than the standard kernel method

Representation of European hydroclimatic patterns with self-organizing maps

Self-organizing maps provide a powerful, non-linear technique of dimensionality reduction that can be used to identify clusters with similar attributes. Here, they were constructed from a 1000-year-long gridded palaeoclimatic dataset, namely the Old World Drought Atlas, to detect regions of homogeneous hydroclimatic variability across the European continent. A classification scheme of 10 regions was found to describe most efficiently the spatial properties of Europe’s hydroclimate. These regions were mainly divided into a northern and a southern subset, linked together with a northwest-to-southeast orientation. Further analysis of the classification scheme with complex networks confirmed the divergence between the northern and southern components of European hydroclimate, also revealing that is not strongly correlated to the Iberian Peninsula. On the contrary, the region covering the British Isles, France and Germany appeared to be linked to both branches, implying links of hydroclimate with atmospheric/oceanic circulation.