Reconfigurable Fault Tolerant PID Networked Control for Magnetic Levitation Case Study

Quinones-Reyes, P.; Benítez-Pérez, Héctor; Méndez-Monroy, Paul E.; Cárdenas-Flores, F.; Garcı́a-Nocetti, F.

doi:10.1016/b978-008044485-7/50183-4

Cited by 1 publication

(3 citation statements)

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“…So another aspect to consider is the operation opportunistically in the frequency band allocated to a licensed system, on the primary user. In the case of cognitive systems [2] we make a contribution to a complex behavior basically because the design of the controller-reactive agents is based on a local view of different elements, last take into consideration the environment. The controller-reactive agents can have an organization without the external intervention.…”

Section: Resultsmentioning

confidence: 99%

“…Each time we generate an artificial intelligent model, we are inspired by cognitive sciences. These allow us to understand how humans emulate the behavior of cognitive systems [1] [2]. Cognitive systems include both natural and artificial information processing systems responsible for perception, learning, reasoning, communication, action and more.…”

Section: Introductionmentioning

confidence: 99%

“…Cognitive systems include both natural and artificial information processing systems responsible for perception, learning, reasoning, communication, action and more. One of the goals is to understand how natural and artificial processing devices could solve the most complex systems [1] [2]. In the case of the brain the robustness is completed by an ultra massive parallel processing in neural systems that can be compared to continue developing of very large scale integration.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Agent System for Real Time Planning Using Collaborative Agents

Laureano-Cruces¹,

Sánchez-Guerrero²,

Ramírez-Rodríguez³

2014

IJIS

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Autonomous agents are an important area of research in the sense that they are proactive, and include: goal-directed and communication capabilities. Furthermore each goals of the agent are constantly changing in a dynamic environment. Part of the challenge is to automate the process corresponding to each agent in order that they find their own objectives. Agents do not have to work individually, but can work with others and develop a coordinated group of actions. These agents are highly appreciated, when real time problems are involved, meaning that an agent must be able to react within a specific time interval, considering external events. Our work focuses on the design of a multi-agent architecture consisting of autonomous agents capable of acting through a goal-directed with: a) constraints, b) real-time, and c) with incomplete knowledge of the environment. This paper shows a model of collaborative agents architecture that share a common knowledge source, allowing knowledge of the environment; where we analyze it and its changes, choosing the most promising way for achieving the goals of the agent, in order to keep the whole system working, even if a fault occurs.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%