초록 ▼

A method to supervise a local dynamical system having multiple preset control objectives and operating in conjunction with other dynamical systems. The method includes receiving state input from dynamical systems in an environment at a distributed soft computing level, generating weights and applyin

A method to supervise a local dynamical system having multiple preset control objectives and operating in conjunction with other dynamical systems. The method includes receiving state input from dynamical systems in an environment at a distributed soft computing level, generating weights and applying the weights to the preset control objectives using soft computing methods to form weighted control objectives. The weights are computed based on the received state input. The method also includes generating a command signal for the local dynamical system based on the weighted control objectives and transmitting the command signal to a controller in the local dynamical system.

대표청구항 ▼

The invention claimed is: 1. A method to supervise a dynamical system having multiple preset control objectives and operating in conjunction with other dynamical systems comprising: receiving state input from dynamical systems in an environment at a distributed soft computing level from an informat

The invention claimed is: 1. A method to supervise a dynamical system having multiple preset control objectives and operating in conjunction with other dynamical systems comprising: receiving state input from dynamical systems in an environment at a distributed soft computing level from an information exchanger at an information coordination level; generating weights and applying the weights to the multiple preset control objectives using soft computing methods to form weighted control objectives, wherein the weights are generated based on the received state input, and wherein a priority of multiple preset control objectives is shifted as the inputs to the information exchanger change; generating a command signal for the dynamical system based on the weighted control objectives; and transmitting the command signal to a controller in the dynamical system. 2. The method of claim 1, wherein the command signal is a target value for a selected state of the dynamical system. 3. The method of claim 1 further comprising: modifying a reasoning/inference system in the distributed soft computing level based on the receiving state input and applying. 4. The method of claim 1, wherein receiving state input further comprises: receiving state input regarding the dynamical system at an information coordination level from the dynamical system; receiving other-system state input regarding the other dynamical systems at the information coordination level from other dynamical systems; receiving external environment input at the information coordination level from an environment of the dynamical system; generating other state input at the information coordination level based on receiving the other-system state input and the external environment input; and transmitting the other state input regarding the other dynamical systems and the state input regarding the dynamical system to the distributed soft computing level as the state input. 5. The method of claim 4, wherein the dynamical system and the other dynamical systems are on a dynamical system level at a lower level than the information coordination level. 6. The method of claim 4, wherein the information coordination level is internal to the distributed soft computing level. 7. The method of claim 1, wherein the distributed soft computing level comprises one or more soft computing methodologies including fuzzy logic, fuzzy inference schemes, neural networks, evolutionary computation schemes, neural networks with on-line training, simulated annealing schemes, genetic algorithms and randomized heuristical algorithms located in a distributed intelligence system. 8. A system comprising: a dynamical system at a dynamical system level; an intelligence system at a distributed soft computing level in communication with the dynamical system, wherein the distributed soft computing level is higher than the dynamical system level; and other dynamical systems at the dynamical system level in communication with respective other intelligence systems at the distributed soft computing level, wherein the intelligence system generates a command signal for the dynamical system and the respective other intelligence systems generate other command signals for the respective other dynamical systems wherein the command signal is generated based on a weighting of preset control objectives. 9. The system of claim 8, wherein the intelligence system is co-located with the dynamical system and the other intelligence systems are co-located with respective other dynamical systems, wherein the dynamical system and the other dynamical systems are autonomous dynamical systems. 10. The system of claim 8, wherein the intelligence system is remotely located from the dynamical system and the other intelligence systems are remotely located from respective other dynamical systems, wherein the dynamical system and the other dynamical systems are semi-autonomous dynamical systems. 11. The system of claim 8 further comprising: an information exchanger at an information coordination level, the information coordination level between the dynamical system level and the distributed soft computing level, wherein the other dynamical systems communicate with the intelligence system via the information exchanger, and wherein the information coordination level includes other information exchangers. 12. The system of claim 11, wherein the intelligence system and the information exchanger are co-located with the dynamical system and other intelligence systems and respective other information exchangers are co-located with respective other dynamical systems, wherein the dynamical systems and the other dynamical systems are autonomous dynamical systems. 13. The system of claim 11, wherein the intelligence system and the information exchanger are remotely located from the dynamical system, wherein the other intelligence systems and respective other information exchangers are remotely located from respective other dynamical systems, and wherein the dynamical systems and the other dynamical systems are semi-autonomous dynamical systems. 14. The system of claim 8, wherein the intelligence system includes: a soft computing based supervisor receiving a state input of the dynamical system; a memory storing the preset control objectives of the dynamical system; a mixing system to apply weights to a respective preset control objectives, wherein the weights are based on the state input; and a summation processor to generate command signals, wherein the soft computing based supervisor modifies an initial set of intelligent reasoning algorithms based on the received state input. 15. The system of claim 8, wherein the dynamical system comprises: a controller operable to initiate an action for the dynamical system based on the command signal; a plant operable to be modified according to the initiated action; sensors to sense selected states; and a transceiver to transmit the sensed selected states and to receive the command signal. 16. The system of claim 8, wherein the other dynamical systems are similar in structure and function to the dynamical system, and wherein the dynamical system is an other dynamical system for the other dynamical systems. 17. The system of claim 8, further comprising: an environment in which the dynamical system and the other dynamical systems are located; environmental sensors to sense selected states of the environment; and a transmitter to transmit the sensed environmental selected states to the intelligence system. 18. The system of claim 8, wherein the intelligence system comprises one or more soft computing methodologies including fuzzy logic, fuzzy inference schemes, neural networks, evolutionary computation schemes, neural networks with on-line training, simulated annealing schemes, genetic algorithms and randomized heuristical algorithms. 19. A computer readable medium storing a computer program, comprising: computer readable code to receive state input from a dynamical system and other dynamical systems in an environment at a distributed soft computing level; computer readable code to generate weights and to apply the weights to preset control objectives to form weighted control objectives, wherein the weights are generated using a soft computing methodology to determine a priority of the preset control objectives based on the received state input; computer readable code to generate a command signal for a dynamical system based on the determined priority of the preset control objectives; and computer readable code to transmit the command signal from the distributed soft computing level to the dynamical system. 20. The medium of claim 19, further comprising: computer readable code to modify a reasoning/inference system in the distributed soft computing level.