Ensenada Center for Scientific Research and Higher Education

About: Ensenada Center for Scientific Research and Higher Education is a facility organization based out in Ensenada, Mexico. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 1934 authors who have published 3733 publications receiving 63115 citations.

Development of an integrated aquafarming system

Abstract: The integration of aquaculture into agricultural production systems to intensify profitable food production without the usual environmental degradation appears to be a promising option for a large number of small farmers in many developing countries. However, for the adoption of novel production systems, economic considerations are the main driving force. The farmer has to be convinced of the long- and short-term benefits and profits of different farming systems options. The potential farmer-aquaculturist needs site-specific holistic information packages of different production options, as contrasted with packages of technology only, in order to combine traditional knowledge with modern scientific results. These all-embracing data packages for different production systems must take into account the environmental conditions, the availability and price of the stocking material for aquaculture, of farm animals and seeds, seasonal farm and off-farm labour demands, and the socio-economic situation of the farmer and the neighbourhood. The possible production intensities, profits and risks have to be quantified, and the impacts on the environment, the family and society have to be determined. Such information would serve as a guideline for the selection of management options best suited to his/her farming system and would allow a choice of alternatives in case of unforeseen events. The multifaceted obstacles to developing a sustainable integrated aquafarming system are presented for a case in the Philippines.

Adaptive distributed parameter systems identification with enforceable identifiability conditions and reduced order spatial differentiation

Abstract: Presents synthesis of adaptive identifiers for distributed parameter systems (DPS) described by partial differential equations (PDEs) of parabolic and hyperbolic type. The features of the PDE setting are utilized to obtain the not directly intuitive parameter estimation algorithms that use spatial derivatives of the output data with the order reduced from that of the highest spatial plant derivative. The plant parameter estimates are computed in terms of their orthogonal expansion through the integration of the adjustable identifier parameters. In this regard, the approach of the paper is in the spirit of finite dimensional observer realization in terms of integrating rather than differentiating the output data, only applied to the spatial rather than temporal domain. The constructively enforceable identifiability conditions, formulated in terms of the sufficiently rich input signals referred to as generators of persistent excitation, are shown to guarantee the existence of a unique zero steady state for the parameter errors. Under such inputs, the adjustable parameters in the adaptive identifiers proposed are shown to converge in L/sub 2/ to their nominal space-varying values guaranteeing the pointwise convergence of their orthogonal expansions, which represent plant parameter estimates, to the actual plant parameters.