Obstacle Modelling Oriented to Safe Motion Planning and Control for Planar Rigid Robot Manipulators

Trajectory planning and tracking are crucial tasks in any application using robot manipulators. These tasks become particularly challenging when obstacles are present in the manipulator workspace. In this paper a n-joint planar robot manipulator is considered and it is assumed that obstacles located in its workspace can be approximated in a conservative way with circles. The goal is to represent the obstacles in the robot configuration space. The representation allows to obtain an efficient and accurate trajectory planning and tracking. A simple but effective path planning strategy is proposed in the paper. Since path planning depends on tracking accuracy, in this paper an adequate tracking accuracy is guaranteed by means of a suitably designed Second Order Sliding Mode Controller (SOSMC). The proposed approach guarantees a collision-free motion of the manipulator in its workspace in spite of the presence of obstacles, as confirmed by experimental results.     

Comparison of shear strength tests on AV119 epoxy-joined ceramics

The results of an experimental investigation on epoxy-joined CVD SiC and alumina tested in shear and apparent shear mode by four different configurations are presented. Ceramics have been joined by an epoxy adhesive (AV119), which is not to be considered as the final joining material for high temperature applications, but just as a model brittle joining material chosen to obtain several joined samples in a reasonable time. Advantages and disadvantages of each configuration are discussed and compared to results obtained with the same epoxy-joined carbon/carbon composites, tested by the same shear tests.     

Groebner Bases and Distance of Cyclic Codes

 Recently some methods have been proposed to find the distance of cyclic codes using Gr?bner bases. We present a similar method, whose computational cost is significantly lower. Received: April 24, 2001; revised version: February 14, 2002     

Mofete geothermal field

This report deals with the Mofete geothermal field, which was discovered in southern Italy by AGIP, the Italian state-owned company for exploration of oil, gas and other alternative energy resources, such as geothermal. AGIP is the main operator in the Mofete geothermal field, in joint venture with ENEL, the National Electricity Board. Seven wells have been drilled, and two producing aquifers found at depths between 500 and 2000 m. The preliminary interpretation of a long-term test (three months), together with the model of the field, suggest that a 10 MW power-plant will operate in the near future in the limited area considered favourable so far for geothermal production.     

Understanding the dynamic behaviour of middle-vessel continuous distillation columns

The fundamental dynamic behaviour of a middle-vessel continuous distillation column is studied in this paper. The interaction between the middle vessel (MV) design and control parameters is identified by means of a linear analysis. Transfer functions relating the dynamics of the product composition responses to changes in the disturbance inputs and manipulated inputs are derived. The role of the MV holdup and MV level controller gain in altering the product composition responses is identified. It is shown that the MV level controller gain can significantly affect the control performance when feed flow disturbances must be compensated for. However, it has a much lower impact in the control performance when feed composition disturbances need to be rejected; in this case, exploiting the “buffering” effect of the MV is more important for control. The analysis is carried out in detail for a LV control configuration, and is subsequently extended to an “on-demand” DB configuration. Finally, simple guidelines for the choice of the MV level controller gain and MV holdup are provided.     

Viable synthesis of a self-assembling regioregular thiophenic copolymer for second-order non-linear optics

Regioregular azobenzene-substituted polythiophenic copolymers were prepared by a regiospecific organometallic polycondensation procedure based on a Grignard metathesis reaction. Copolymers with a high content of chromophoric groups in the side chains and a high degree of configurational order of the backbones were obtained. A sample was also functionalized with hydroxyalkyl chains capable of setting up ordered supramolecular structures through hydrogen bonds. The final materials were fully characterized via NMR, IR, elemental analysis, GPC, DSC and X-ray diffraction. Moreover, measurements of NLO activity on polymer films showed the synthetic strategies adopted and monomers used to be correct. Values obtained by the in situ deprotection of the interacting functional groups after the alignment of the chromophorized side chains were very promising, proving the procedure to be suitable for industrial and commercial applications.     

Land Subsidence Spreading Factor of the Northern Adriatic Gas Fields, Italy

The land subsidence spreading factor χ provides a useful straightforward indication on how much of a gas/oil reservoir compaction induced by field development migrates to ground surface with a possible adverse impact on the stability of low‐lying coastal areas. This factor depends primarily on the ratio between the depth of burial and a representative horizontal dimension of the reservoir. However, an important influence is also exerted by the active bottom/lateral aquifer hydraulically connected to the field (called “waterdrive” in reservoir engineering) that may undergo an extensive depressurization also after the field abandonment, thus contributing to enhance the overall land settlement. In the Northern Adriatic basin, Italy, χ is evaluated using a nonlinear finite element model of three representative gas reservoirs (Chioggia Mare, Dorotea, and Dosso degli Angeli) surrounded by important bottom/lateral aquifers in the interval depth between 1000 and 3300 m. Results show that χ may easily approach and even exceed one for the deepest field as well, contrary to the prediction of land subsidence based on the compaction of the gas‐bearing formations alone, that can thus be largely underestimated.     

A backoff strategy for model‐based experiment design under parametric uncertainty

Model‐based experiment design techniques are an effective tool for the rapid development and assessment of dynamic deterministic models, yielding the most informative process data to be used for the estimation of the process model parameters. A particular advantage of the model‐based approach is that it permits the definition of a set of constraints on the experiment design variables and on the predicted responses. However, uncertainty in the model parameters can lead the constrained design procedure to predict experiments that turn out to be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session. Additionally, in the presence of parametric mismatch, the feasibility constraints may well turn out to be violated when that optimally designed experiment is performed, leading in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe experiment. In this article, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session to keep the system within a feasible region with specified probability. This approach is particularly useful when designing optimal experiments starting from limited preliminary knowledge of the parameter set, with great improvement in terms of design efficiency and flexibility of the overall iterative model development scheme. The effectiveness of the proposed methodology is demonstrated and discussed by simulation through two illustrative case studies concerning the parameter identification of physiological models related to diabetes and cancer care. © 2009 American Institute of Chemical Engineers AIChE J, 2010