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In this paper, MASCONTROL, a multiagent system (MAS) for system identification and process control, is presented. This MAS implements a self-tuning regulator (STR) scheme. In this work, an ontology agent (OA) is included, using DAML+OIL as ontology language. From their experience, the authors consider this architecture highly useful for identification and control processes
This paper introduces an adaptive feedback control strategy for (max,+)-linear systems. The feedback loop is tuned following to an estimation of the system transfer and in order to match a given reference model. An application of such an adaptive control strategy is possible for some manufacturing systems in which the feedback control corresponds to an adaptive resource allocation
This paper presents a new method to allow more flexibility on the scheduling of messages across a fieldbus in overload situations. The method proposes the on-line adaptation of the sampling period to the bus load, trying to keep it as low as possible during overloads. The sampling period is allowed to change inside an interval corresponding to 4 to 10 samples per rise time. To assess the solution...
In this paper, an adaptive inverse control with internal model control (IMC) structure is proposed and implemented on a robotic arm manipulator system. The plant is stabilized using a simple lead-lag controller and the inverse of the plant is estimated using normalized least mean square (nLMS) algorithm. Radial base transfer function is used as an input mask to the adaptive algorithm. A delayed version...
In this paper a new kinematic and dynamic adaptive fuzzy control is applied to a trajectory tracking problem of a constrained vehicle with two independent wheels. The vehicle dynamics and kinematics are completely unknown. A dynamical and kinematical adaptive control provide to on line estimation of the dynamic and kinematic parameters of the vehicle model. Moreover the parameters of the kinematic...
In this work we introduce a model for studying the distribution and control of atmospheric pollution from PMiQ. The model is based on the use of a cellular neural network (CNN) and more precisely on the integration of the mass-balance equation; at the same time it simulates the scenario regarding a planar grid describing the whole studied area (the city of Palermo) by means of a CNN and a set of Bayesian...
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