Extruder for food product (otak–otak) with heater and roll cutter

Food extrusion is a form of extrusion used in food industries. It is a process by which a set of mixed ingredients are forced through an opening in a perforated plate or die with a design specific to the food, and is then cut to a specified size by blades [1]. Summary of the invention principal objects of the present invention are to provide a machine capable of continuously producing food products having an’ extruded filler material of meat or similarity and an extruded outer covering of a moldable food product, such as otak-otak, that completely envelopes the filler material

Design and Simulation of a Novel Clustering based Fuzzy Controller for DC Motor Speed Control

This research article proposes the speed control of a DC Motor (series as well as shunt motor). The noveltyof this article lies in the application of kernel based hybrid c-means clustering (KPFCM) in the design offuzzy controller for the speed control of DC Motor. The proposed approach provides a mechanism to obtainthe reduced rule set covering the whole input/output space as well as the parameters of membershipfunctions for each input variable. The performance of the proposed clustering based fuzzy logic controlleris compared with that of its corresponding conventional fuzzy logic controller in terms of severalperformance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) andintegral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improvedperformance over its conventional counterpart. Also it shows that the proposed controller scheme givesmuch faster results as it reduces the computational time.Keywords: DC Motor, Fuzzy control, Kernel, Clustering, Validity inde

Fuzzy optimisation based symbolic grounding for service robots

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySymbolic grounding is a bridge between task level planning and actual robot sensing and actuation. Uncertainties raised by unstructured environments make a bottleneck for integrating traditional artificial intelligence with service robotics. In this research, a fuzzy optimisation based symbolic grounding approach is presented. This approach can handle uncertainties and helps service robots to determine the most comfortable base region for grasping objects in a fetch and carry task. Novel techniques are applied to establish fuzzy objective function, to model fuzzy constraints and to perform fuzzy optimisation. The approach does not have the short comings of others’ work and the computation time is dramatically reduced in compare with other methods. The advantages of the proposed fuzzy optimisation based approach are evidenced by experiments that were undertaken in Care-O-bot 3 (COB 3) and Robot Operating System (ROS) platforms