Claims Analysis
Total Claims: 11
Claim 1
Independent Claim
234 words
A heater controlling unit for controlling an on/off action of a heater to control a surface temperature of heat releasing means which releases heat generated by said heater through conduction, said heater controlling unit comprising: temperature detecting means for detecting an actual temperature of a surface of said heat releasing means; temperature change rate computing means for computing a temperature change rate within a predetermined period using the actual temperature detected by said temperature detecting means; and on-time computing and control means including a fuzzy neural network, said fuzzy neural network receiving the actual temperature detected by said temperature detecting means and the temperature change rate computed by said temperature change rate computing means and computing a period of time during which said heater is turned on using a fuzzy logic to output a computed value, said on-time computing and control means controlling said on/off action based on the output computed value from said fuzzy neural network, said fuzzy neural network including a plurality of layers each having a node for outputting an output signal in response to an input signal, and a plurality of links that interlink the node of said each layer to transmit a signal among layers, a weight of said each link, which indicates signal transmission efficiency among the nodes, being adjusted based on a difference between a target value and the output computed value from said fuzzy neural network.
Claim 2
Dependent Claim
234 words
A heater controlling unit for controlling an on/off action of a heater to control a surface temperature of heat releasing means which releases heat generated by said heater through conduction, said heater controlling unit comprising: temperature detecting means for detecting an actual temperature of a surface of said heat releasing means; temperature change rate computing means for computing a temperature change rate within a predetermined period using the actual temperature detected by said temperature detecting means; and on-time computing and control means including a fuzzy neural network, said fuzzy neural network receiving the actual temperature detected by said temperature detecting means and the temperature change rate computed by said temperature change rate computing means and computing a period of time during which said heater is turned on using a fuzzy logic to output a computed value, said on-time computing and control means controlling said on/off action based on the output computed value from said fuzzy neural network, said fuzzy neural network including a plurality of layers each having a node for outputting an output signal in response to an input signal, and a plurality of links that interlink the node of said each layer to transmit a signal among layers, a weight of said each link, which indicates signal transmission efficiency among the nodes, being adjusted based on a difference between a target value and the output computed value from said fuzzy neural network.
Claim 3
Dependent Claim
152 words
The heater controlling unit as defined in claim 1 further comprising: predictive computing means for, when said heater is turned on by said on-time computing and control means, computing a predictive temperature of the surface of said heat releasing means for a next time said heater is turned on, said predictive temperature being computed using the actual temperature detected by said temperature detecting means and the temperature change rate computed by said temperature-change rate computing means; and comparing and adjusting means for computing a difference between the actual temperature and the predictive temperature, and, when said difference is greater than a predetermined value, said comparing and adjusting means adjusting the weight of said each link within said fuzzy neural network in such a manner to minimize a difference between said target value and said period of time during which said heater is turned on computed by said on-time computing and control means.
Claim 4
Dependent Claim
43 words
The heater controlling unit as defined in claim 2, wherein said fuzzy neural network comprises an input layer, a membership input layer, a membership output layer, a rule layer, and an output layer, each of links among said layers having their respective weights.
Claim 5
Dependent Claim
86 words
The heater controlling unit as defined in claim 3, wherein: each of said input layer and said membership input layer has a structure that divides each of the actual temperature and the temperature change rate into three areas; and said rule layer outputs ANDs of all possible links of an output value from a node corresponding to each area of the actual temperature and an output of a node corresponding to each area of the temperature change rate in said membership layer to said output layer.
Claim 6
Dependent Claim
59 words
The heater controlling unit as defined in claim 3, wherein said comparing and adjusting means adjusts a weight of a link from said input layer to said membership input layer, a weight of a link from said membership input layer to said membership output layer, and a weight of a link from said rule layer to said output layer.
Claim 7
Dependent Claim
84 words
The heater controlling unit as defined in claim 5, wherein said input layer includes a first node for receiving the actual temperature, a second node for receiving the temperature change rate, and a third node for receiving a fixed value, a weight of a link from said third node to said membership input layer being a center value of a membership function, a weight of a link from said membership input layer to said membership output layer being a slope of the membership function.
Claim 8
Dependent Claim
108 words
The heater controlling unit as defined in claim 2, wherein: said temperature change rate computing means computes a first temperature change rate in a period during which said heater is turned on, and a second temperature change rate in a period during which said heater is turned off; and said predictive computing means computes the predictive temperature by adding up (1) a current actual temperature, (2) a product of a preceding first temperature change rate and a following period during which said heater is turned on, and (3) a product of a preceding second temperature change rate and a following period during which said heater is turned off.
Claim 9
Dependent Claim
74 words
The heater controlling unit as defined in claim 1, wherein said fuzzy neural network includes: a rule layer having a plurality of nodes each for processing a signal based on their respective fuzzy rules; and an output layer having a node for outputting said period of time during which said heater is turned on, the node of said output layer being connected to an output side of said each node of said rule layer.
Claim 10
Dependent Claim
67 words
The heater controlling unit as defined in claim 8, wherein said fuzzy neural network further includes: an input layer into which the actual temperature and the temperature change rate are inputted; and a membership input layer and a membership output layer, provided between said input layer and rule layer, for converting the actual temperature and the temperature change rate into a fuzzy variable using a membership function.
Claim 11
Dependent Claim
133 words
The heater controlling unit as defined in claim 1 further comprising: predictive computing means for, when said heater is turned on by said on-time computing and control means, computing a predictive temperature of the surface of said heat releasing means for a next time said heater is turned on, said predictive temperature being computed using the actual temperature means and the temperature change rate computed by said temperature-change rate computing means; and comparing and adjusting means for computing a difference between the actual temperature detected by said temperature detecting means and the predictive temperature computed by said predictive computing means, and, when the difference is greater than a predetermined value, for adjusting a weight of a link within said fuzzy neural network of said on-time computing and controlling means to minimize the difference.