Abstract: A control input (DUT) for controlling a heater (13) which heats an active element (10) of an exhaust gas sensor (8) includes at least one of another component depending on the difference between temperature data of the active element (10) and a target temperature, a component depending on the target temperature, and a component depending on the temperature data of the active element (10). The control input is determined by an optimum control algorithm. A component depending on the temperature of an exhaust gas and the component depending on the target temperature are determined based on a predictive control algorithm. The temperature of the active element (10) of the exhaust gas sensor (8) is thus controlled stably at a desired temperature.

Abstract: A control input (DUT) for controlling a heater (13) which heats an active element (10) of an exhaust gas sensor (8) includes at least one of another component depending on the difference between temperature data of the active element (10) and a target temperature, a component depending on the target temperature, and a component depending on the temperature data of the active element (10). The control input is determined by an optimum control algorithm. A component depending on the temperature of an exhaust gas and the component depending on the target temperature are determined based on a predictive control algorithm. The temperature of the active element (10) of the exhaust gas sensor (8) is thus controlled stably at a desired temperature.

Abstract: A control input (DUT) for controlling a heater (13) which heats an active element (10) of an exhaust gas sensor (8) includes at least one of another component depending on the difference between temperature data of the active element (10) and a target temperature, a component depending on the target temperature, and a component depending on the temperature data of the active element (10). The control input is determined by an optimum control algorithm. A component depending on the temperature of an exhaust gas and the component depending on the target temperature are determined based on a predictive control algorithm. The temperature of the active element (10) of the exhaust gas sensor (8) is thus controlled stably at a desired temperature.

Abstract: The temperature of an exhaust gas flowing through an exhaust passage 3 is estimated or detected, and the temperature of an active element of an exhaust gas sensor 8. (O2 sensor) is controlled at a predetermined target temperature by a heater using the estimated or detected temperature of the exhaust gas. For estimating the temperature of the exhaust gas in the vicinity of the exhaust gas sensor 8, the exhaust passage 3 extending up to the exhaust gas sensor 8 is divided into a plurality of partial exhaust passageways 3a through 3d, the temperatures of the exhaust gas in the partial exhaust passageways 3a through 3d are estimated successively from an exhaust port 2 of an engine 1. The temperature of the exhaust gas is estimated according to an algorithm which takes into account a heat transfer between the exhaust gas and passage-defining members 6a, 6b, 7 which define the exhaust passage 3 and a heat radiation from the passage-defining members into the atmosphere.

Abstract: An apparatus for controlling temperature of an exhaust gas sensor can include a temperature estimating device for sequentially estimating the temperature of an active element based on a predetermined element temperature model, which is representative of a temperature change of the active element due to heat transfer between the active element and an exhaust gas held in contact with the active element. A heater control device can control a heater to equalize the temperature of the active element with a predetermined target temperature using an estimated value of the temperature of the active element from the temperature estimating device.

Abstract: A control system for a plant is disclosed. The control system includes a controller for controlling the plant based on a controlled object model which is obtained by modeling the plant. The controlled object model is modeled using an input and an output of the plant which are sampled at intervals of a sampling period which is longer than a control period of the controller. The sampled input of the plant is a filtered control output which is obtained by filtering an output of the controller. The controller carries out a control process of the plant at intervals of the control period.

Abstract: A control system for a plant is disclosed. The control system includes a controller which controls the plant based on a controlled object model which is obtained by modeling the plant. The controlled object model is modeled using an input and an output of the plant which are sampled at intervals of a period which is longer than a control period of the controller. The controller carries out a control process of the plant at intervals of the control period.

Abstract: A control system for a plant is provided. This control system can control the plant more stably, when the model parameters of the controlled object model which are obtained by modeling the plant, which is a controlled object, are identified and the sliding mode control is performed using the identified model parameters. The model parameter identifier (22) calculates a model parameter vector (?) by adding an updating vector (d?) to a reference vector (?base) of the model parameter. The updating vector (d?) is corrected by multiplying a past value of at least one element of the updating vector by a predetermined value which is greater than “0” and less than “1”. The model parameter vector (?) is calculated by adding the corrected updating vector (d?) to the reference vector (?base).

Abstract: A control system for a plant, having an identifier and a controller. The identifier identifies model parameters of a controlled object model which is obtained by modeling the plant. The controller calculates a control input to the plant so that an output from the plant coincides with a control target value, using the identified model parameters. The controller calculates a self-tuning control input, using the model parameters identified by the identifier. The controller further calculates a damping control input according to the rate of change in the output from the plant or the rate of change in a deviation between the output from the plant and the control target value. The controller calculates the control input to the plant as a sum of the self-tuning control input and the damping control input.

Abstract: The present invention provides a control apparatus for a plant, which can suppress excessive correction for a spiky disturbance being applied and maintain a good controllability, when controlling the plant, which is a controlled object, with the self-tuning regulator. A detected equivalent ratio KACT is input to a high-pass filter 33, and a high-pass filter output KACTHP is input to a parameter adjusting mechanism 42. The parameter adjusting mechanism 42 calculates a corrected updating vector (KID·d?(k)) by multiplying an updating component d? of a model parameter vector by a correction coefficient KID, and adds the corrected updating vector to a preceding value ?(k?1) of the model parameter vector, to thereby calculate a present value ?(k). The correction coefficient KID is changed from “1.0” to a value near “0” upon detection of the spiky response where an absolute value of the high-pass filter output KACTHP increases.

Abstract: A control system for a plant is provided. This control system can control the plant more stably, when the model parameters of the controlled object model which are obtained by modeling the plant, which is a controlled object, are identified and the sliding mode control is performed using the identified model parameters. The model parameter identifier (22) calculates a model parameter vector (?) by adding an updating vector (d?) to a reference vector (?base) of the model parameter. The updating vector (d?) is corrected by multiplying a past value of at least one element of the updating vector by a predetermined value which is greater than “0” and less than “1”. The model parameter vector (?) is calculated by adding the corrected updating vector (d?) to the reference vector (?base).

Abstract: A control system for a plant is disclosed. According to this system, a model parameter vector of a controlled object model which is obtained by modeling the plant, is identified. A controller controls the plant using the identified model parameter vector. An identifying error of the model parameter vector is calculated, and the calculated identifying error is limited in a predetermined range. An updating vector is calculated according to the limited identifying error. The model parameter vector is calculated by adding the updating vector to a reference vector of the model parameter vector.

Abstract: A control system for a plant is provided. This control system can control the plant more stably, when the model parameters of the controlled object model which are obtained by modeling the plant, which is a controlled object, are identified and the sliding mode control is performed using the identified model parameters. The model parameter identifier (22) calculates a model parameter vector (?) by adding an updating vector (d ?) to a reference vector (? base) of the model parameter. The updating vector (d ?) is corrected by multiplying a past value of at least one element of the updating vector by a predetermined value which is greater than “0” and less than “1”. The model parameter vector (?) is calculated by adding the corrected updating vector (d ?) to the reference vector (? base).

Abstract: A control system for a plant is disclosed. In this control system, a model parameter vector of a controlled object model which is obtained by modeling said plant, is calculated. A sliding mode controller is included in the control system. The sliding mode controller controls the plant using the identified model parameter vector. A damping input is calculated according to a speed of change in an output of the plant, and an element of the model parameter vector. A control input form the sliding mode controller to the plant includes the calculated damping input.

Abstract: The present invention provides a control system for an internal combustion engine for detecting a torque variation based on a rotational speed of the engine and suppress the torque variation. The system includes a detector for detecting a rotational speed of the engine, a memory for storing a variation pattern of the rotational speed of the engine when a torque of the internal combustion engine is excessive and a controller for calculating a variation component of the rotational speed based on the detected rotational speed, The controller calculates the correlation between the variation component and the variation pattern that is read out from the memory and then determines a torque variation state of the engine based on the correlation.

Abstract: A control input (DUT) for controlling a heater (13) which heats an active element (10) of an exhaust gas sensor (8) includes at least one of another component depending on the difference between temperature data of the active element (10) and a target temperature, a component depending on the target temperature, and a component depending on the temperature data of the active element (10). The control input is determined by an optimum control algorithm. A component depending on the temperature of an exhaust gas and the component depending on the target temperature are determined based on a predictive control algorithm. The temperature of the active element (10) of the exhaust gas sensor (8) is thus controlled stably at a desired temperature.

Abstract: A sensor temperature control means (18) for controlling the temperature of an active element (10) of an exhaust gas sensor (O2 sensor) (8) disposed in an exhaust passage (3) estimates the temperatures of the active element (10) and a heater (13) based on an element temperature model which is representative of a temperature change of the active element due to heat transfer between the active element (10) and the heater (13) which heats the active element and heat transfer between the active element (10) and an exhaust gas, and a heater temperature model which is representative of a temperature change of the heater due to heat transfer between the active element (10) and the heater (13) and the supply of electric power to the heater (13), and controls the heater (13) to equalize the temperature of the active element (10) or the heater (13) with a predetermined target temperature using estimated values of the temperatures.

Abstract: A control system for an internal combustion engine having at least one control device that affects an air-fuel ratio of an air-fuel mixture to be supplied to the engine, is disclosed. An air-fuel ratio correction coefficient is calculated for correcting an amount of fuel to be supplied to the engine so that the detected air-fuel ratio coincides with a target air-fuel ratio. An air-fuel ratio affecting parameter indicative of a degree of influence that an operation of the control device exercises upon the air-fuel ratio, is calculated. A correlation parameter which defines a correlation between the air-fuel ratio correction coefficient and the air-fuel ratio affecting parameter is calculated using a sequential statistical processing algorithm. A learning correction coefficient relating to a change in characteristics of the control device is calculated using the correlation parameter. The air-fuel ratio is controlled using the air-fuel ratio correction coefficient and the learning correction coefficient.

Abstract: A vehicle controller for controlling the air-fuel ratio of an engine is provided. In one embodiment, the controller comprises a first exhaust gas sensor provided downstream of the catalyst for detecting oxygen concentration of exhaust gas, a first decimation filter connected to the first exhaust gas sensor, and a control unit connected to the first decimation filter. The control unit determines a manipulated variable for manipulating the air-fuel ratio. The first decimation filter oversamples, low-pass filters and then downsamples the output of the first exhaust gas sensor. The first decimation filter can remove chemical noise from the output of the exhaust gas sensor. In another embodiment, a second decimation filter is connected to a second exhaust gas sensor provided upstream of the catalyst for detecting the air-fuel ratio of the exhaust gas. The second decimation filter oversamples, low-pass filters and then downsamples the output of the second exhaust gas sensor.

Abstract: A control system for a plant is disclosed. The control system includes a response specifying type controller for controlling the plant with a response specifying type control. The response specifying type controller calculates a nonlinear input according to a sign of a value of a switching function and an output of the plant. The switching function is defined as a linear function of a deviation between the output of the plant and a control target value. A control input from the response specifying type controller to the plant includes the nonlinear input.