A sensibility meter detects biometric information relating to an operator corresponding to an output from a target appliance, and determines a comfort level of the operator based on the biometric information. A first control unit determines a second target value relating to the output based on a difference between a first target value relating to the comfort level and the comfort level. A second control unit determines a control input to the target appliance based on a difference between the second target value and the output. A δ setting unit performs weighting corresponding to an operation level of the operator, for an operation input to the target appliance by the operator, and for the control input. An adder adds the weighted operation input and control input, and inputs the resultant to the target appliance.

In an embodiment an electro-thermal device includes a heater, a readout circuit, a digital controller having a first input coupled to a first output of the readout circuit and a digital sigma-delta modulator having a first input coupled to an output of the digital controller and an output coupled to the heater.

In an embodiment an electro-thermal device includes a heater, a readout circuit, a digital controller having a first input coupled to a first output of the readout circuit and a digital sigma-delta modulator having a first input coupled to an output of the digital controller and an output coupled to the heater.

An apparatus for human-computer interaction and a vehicle including the same are provided. The apparatus includes a first magnetic component, a control module, a data transmission module and a second magnetic component. The first magnetic component has a preset surface area and is fixed on a device where the apparatus is located. The control module generates a control instruction. The data transmission module sends the control instruction to a main controller of the device. The second magnetic component is connected to the control module and the data transmission module, and attracts the control module and the data transmission module to the first magnetic component, where an attraction position is changeable. The user can control the second magnetic component to move to a suitable position on a surface of the first magnetic component, avoiding usage barriers caused by the user's inaccessibility of the apparatus for human-computer interaction.

An apparatus for human-computer interaction and a vehicle including the same are provided. The apparatus includes a first magnetic component, a control module, a data transmission module and a second magnetic component. The first magnetic component has a preset surface area and is fixed on a device where the apparatus is located. The control module generates a control instruction. The data transmission module sends the control instruction to a main controller of the device. The second magnetic component is connected to the control module and the data transmission module, and attracts the control module and the data transmission module to the first magnetic component, where an attraction position is changeable. The user can control the second magnetic component to move to a suitable position on a surface of the first magnetic component, avoiding usage barriers caused by the user's inaccessibility of the apparatus for human-computer interaction.

A state estimation apparatus includes: a current information acquisition part that acquires information about a current at a power supply part of a refrigerating/freezing apparatus; a current information storage part that holds current information in a normal state of the refrigerating/freezing apparatus; an evaluation part that derives a degree of change based on the acquired current information and the current information in the normal state of the refrigerating/freezing apparatus; a filter cleaning determination part that estimates a clogging state of a filter of the refrigerating/freezing apparatus based on the degree of change to determine whether cleaning of the filter is necessary; and an output part that provides, for a determination result indicating that the cleaning of the filter is necessary, an output to that effect.

A state estimation apparatus includes: a current information acquisition part that acquires information about a current at a power supply part of a refrigerating/freezing apparatus; a current information storage part that holds current information in a normal state of the refrigerating/freezing apparatus; an evaluation part that derives a degree of change based on the acquired current information and the current information in the normal state of the refrigerating/freezing apparatus; a filter cleaning determination part that estimates a clogging state of a filter of the refrigerating/freezing apparatus based on the degree of change to determine whether cleaning of the filter is necessary; and an output part that provides, for a determination result indicating that the cleaning of the filter is necessary, an output to that effect.

A method and system for set point control of a liquid level in a conical tank is disclosed. The method includes receiving set point signal, R(s), summing the set point signal, R(s), with a negative feedback signal, d{tilde over (f)}(s), and generating set point error signal, E(s), which is used as feedback at the input to drive the liquid level in the conical tank to a desired set point, thus controlling the liquid level of conical tank so that external disturbance, df(s), is minimized.

A method and system for set point control of a liquid level in a conical tank is disclosed. The method includes receiving set point signal, R(s), summing the set point signal, R(s), with a negative feedback signal, d{tilde over (f)}(s), and generating set point error signal, E(s), which is used as feedback at the input to drive the liquid level in the conical tank to a desired set point, thus controlling the liquid level of conical tank so that external disturbance, df(s), is minimized.

The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.