PubMed · 7629587
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
M Simons, J A Parker. 1995. Fuzzy logic, sharp results.. https://pubmed.ncbi.nlm.nih.gov/7629587/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
A control model of human stance is proposed based on knowledge from behavioral experiments and physiological systems. The proposed model is based on the control of global variables specific to body orientation and alignment, rather than on the control of the body's center of mass within the base of support. Furthermore, the proposed control model is not based on purely inverted pendulum body mechanics where only motion at one joint is controlled, as for instance the ankle. In the proposed model, the degrees of freedom are controlled by using reciprocal and synergistic muscle actions at multiple joints. The control model is based on three sets of different global variables which act in parallel: (1) limb length and its derivative, (2) limb orientation and its derivative, and (3) trunk attitude and its derivative. An important feature of the control model is the use of fuzzy logic, which enables us to model experimental findings and physiological knowledge in a meaningful and explicit way using fuzzy if-then rules. In the control model, 36 fuzzy if-then rules are implemented and applied using a four-linked segment model consisting of a trunk, thigh, shank and foot. Uni- and biarticular limb muscles and trunk muscles are represented as torque actuators at each individual joint. In the model, three sets of global variables act in parallel and make corrective and coordinated responses to internal, self-induced perturbations. The data show that the use of global variables and fuzzy logic successfully enables us to model human standing with sway about a point of equilibrium. Small changes in, for example, total body sway are comparable to those seen during natural sway in human stance. The selected controllers--limb length, limb orientation and trunk attitude--seem to be appropriate for human stance control.
The quality of raw water from major water plants in Wuhan was evaluated by using Fuzzy synthetic evaluation model. It is suggested to select the alternative synthetic evaluation model when the first Fuzzy synthetic model failed in order to increase accuracy.
Fuzzy logic is a mathematical approach to deal with systems that can not be defined precisely. Nutrient requirements fall into this category. Dietary intakes of nutrients are such that if a nutrient is given in graded amounts, with all other nutrients constant, there is no definitive border where, for example, one intake is deficient and another, slightly higher intake, adequate. Thus, fuzzy sets were developed that describe the range of intakes of a nutrient, ranging from deficiency to excess. On the basis of these fuzzy sets and the known nutrient composition of the food, an index is derived that reflects how closely the diet of an individual meets all the nutrient requirements set by the German Society of Nutrition. Because this is a computer-based system, alterations in the diet are suggested if the diet does not meet requirements. The suggested dietary alterations are usually small but nevertheless allow the diet to meet recommendations. It is important that the suggested alterations be small because the fewer the suggested changes in a diet, the greater the change a person will accept the changes. Thus nutrient intake can be described and evaluated by using fuzzy decision making. This has present applicability in nutrition education and could possibly be used as a tool in determining recommended dietary allowances.