CN113646709A - Hydrostatic working machine and control method thereof - Google Patents
Hydrostatic working machine and control method thereof Download PDFInfo
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- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
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Abstract
A hydrostatic working machine for a mobile working machine is disclosed, having a hydrostatic actuator and an operating device, via which a movement request for the actuator, which is an input variable of a kinematic model of the actuator stored in a control device, can be detected, wherein the actuator can be actuated as a function of an output variable of the control device, wherein a detection device is provided, via which a kinematic state of the actuator, which can be assigned or has been assigned to the movement request or the output variable, can be detected. A method for controlling the working device is also disclosed.
Description
Technical Field
The invention relates to a hydrostatic working machine according to the preamble of claim 1 and to a method for controlling a hydrostatic working machine according to claim 8.
Background
Working apparatuses of the generic type have a large number of rotational and/or translational degrees of freedom. The work machine consists here of a series of hydrostatic actuators.
It is important that the control of the working device is safe and comfortable for the operator. The working device must therefore work in its range of motion without collision with the working machine and its environment. Furthermore, the tool arranged at the tip of the working device should be controllable in all three coordinates with a target correct and comfortable. Even for inexperienced operators (e.g. drivers moving work machines), it should be possible to control with high dynamics and positioning accuracy.
In order to meet these requirements, the solutions known to date use chains consisting of model-based pre-control, measuring technical means for detecting the movement of the working device and adjustments. In this case, it is important to solve the inverse kinematics problem that results therefrom. All known methods are based on an accurate knowledge of the hydro-mechanical system of the actuator, so that the required accuracy can be mapped in the pre-control path by means of model inversion, and the required positioning quality can be achieved in conjunction with the downstream regulation while at the same time achieving sufficiently high dynamics.
However, an exact knowledge of the system behavior is difficult to achieve in practice, so that even with knowledge of the built-in components, a high application effort is required at the time of debugging. The requirements of high dynamics and high positioning accuracy can only be met by a large amount of time and a precise understanding of the system. This procedure has proven to be of course particularly complex for the commissioning and operation of systems with unknown hydraulic components.
Furthermore, the ageing effects of the hydraulic components during the service life of the working device may lead to a deterioration of the behaviour. The deviation between the real system and the system model mapped in the pre-control may cause deterioration of the positioning accuracy. It is also possible to excite oscillations of the operating device, since deviations occurring between the nominal behavior and the actual behavior must be compensated for by the regulator in the closed circuit.
Mobile work machines with complex work kinematics are typically controlled by interpreting joystick signals as a desired speed for individual electrical consumers (e.g., boom, stick, bucket). However, such a verified control concept has proven difficult, in particular for inexperienced drivers or for tasks that place high demands on the accuracy of the positioning of the working device. Assistance is provided by an assistance function which enables the HMI signal to be interpreted as the desired speed of the working equipment tip in the xyz coordinate system, the so-called TCP or coordinate control. This assistance function uses a kinematic model of the actuator to calculate the joint velocity required for the motion demand desired by the driver. A prerequisite for such an assistance function is usually the detection of the joint angle and in general the kinematic configuration, in particular via an angle sensor, a cylinder stroke sensor or an inertial sensor system. To achieve the joint velocity required for the assistance function, a corresponding velocity is required for each participating actuator. Known solutions use inverse models of the steering path from the joystick deflection to the steering of the pump and valve in combination with regulation to achieve the required movement as accurately as possible. The adjustment is required to compensate for errors in the pre-control model, for example due to parameter deviations, and disturbance variables, for example of heavy material with corresponding resistance on the excavating equipment. In particular, high dynamic movements (e.g. rapid levelling in a plane or on an embankment) are premised on a high quality of pre-control, since the dynamics of the regulation are limited. In the known solutions, the use of a pre-control that is as precise as possible is based on modeling of the control chain and corresponding knowledge of system parameters, such as valve block dynamics and pump dynamics, line losses and diesel engine behaviour. As already mentioned, this leads to a considerable expenditure during commissioning, even if known hydraulic assemblies are used. With unknown components, high precision in the pre-control path has not been achieved to date. This significantly deteriorates the positioning accuracy that can be achieved with the aid of the auxiliary function or renders such a function completely unusable.
Disclosure of Invention
In contrast, the object on which the invention is based is to provide a process-reliable controllable hydrostatic working unit and a method for process-reliable control of the working unit.
The first task is solved by a hydrostatic working machine having the features of claim 1, and the second task is solved by a method having the features of claim 8.
Advantageous developments of the invention are described in the dependent claims, respectively.
A hydrostatic working machine for a mobile working machine, in particular for an excavator, a crawler excavator, a mobile excavator, a mini excavator, a backhoe loader or a concrete pump or a forestry machine, has a hydrostatic actuator, in particular a kinematically coupled hydrostatic actuator. The actuator may be rotary or translational, such as a rotary motor or a lift cylinder. A tool or a tool receiving device is preferably provided at the end section of the working apparatus. The working device has an operating device via which a movement request for the actuator can be detected. The operating device is preferably in signal connection with a control device of the working apparatus. The motion demand is an input variable of at least a kinematic model of the actuator, which model is stored in a control device of the working machine. The actuator can be controlled by the control device at least as a function of an output variable of the control device, in particular of the model, in particular by means of a pressure medium source and a valve device. Furthermore, a detection device is provided, via which a kinematic state of the actuator, which can be or can be assigned to the kinematic demand or output variable, can be detected. According to the invention, the working device, in particular the control device thereof, has an adaptation or learning device which is designed such that the model or the inversion thereof, i.e. the inverse model, can be adapted at least as a function of the motion requirements and/or the output variables and the detected, assignable or assigned states. Thus, according to the present invention, the control device can learn. In other words, an adaptation or learning algorithm is realized by means of the adaptation means.
This results in a reduction in the development and commissioning effort of the working device, since the model for controlling the working device (adaptation means) can be adapted independently. It is then no longer a prerequisite to have an accurate knowledge of the hydromechanical behavior of the working equipment and the actuator in order to be able to meet the requirements of high dynamics and high positioning accuracy. After the learning or adaptation operation is completed, the adjusting device can be omitted or omitted to the greatest possible extent and the requirements based on the quality of the (adapted) model can be met completely or almost completely by control. In particular, it is no longer necessary for the hydraulic components, such as pumps or valves, to be known a priori, or rather the behavior of these hydraulic components, in order to apply the control device. Even without a precise knowledge of the working device and its actuators, pumps, valves, it is possible to carry out a commissioning, which reduces the time consumption, but still meets the requirements. If aging effects occur over the service life, for example by wear of actuators or by other processes, deviations between reality and model can be compensated by adapting the model according to the invention by means of the adaptation or learning device.
The adaptation means, in particular the learning or adaptation algorithms stored in the adaptation means for execution, may have different embodiments. In a first variant, the model has at least one state space model of the working device, in particular a static model and a dynamic model, respectively, in combination with a recursive least squares algorithm (RLS algorithm) adapted to the effect of the state space model or models. In a second variant, the model has a characteristic curve and/or a family of characteristic curves of the working device with fixed support points whose values can be learned and/or adapted by an RLS algorithm. In a third variant, the learning or adaptation algorithm is formed by at least one neural network and a deep learning method. The weights can be learned and adapted by means of back propagation. For this purpose, the detection data of the detection means can preferably be stored in the control means. A fourth variant of the learning or adaptation algorithm is configured as Reinforcement Learning (RL). Migration behavior can thus be learned over a large range without using the model.
The adaptation means may be designed such that the adaptation may be performed periodically or in batches (in particular after the end of a work task) or continuously.
Preferably, the learning or adaptation algorithm is stored in the adaptation means for execution.
In one development, the control device is universal. Preferably, the control device is universal in construction. This has the following advantages: the control device can be adapted to the embodiment of the working apparatus and/or the mobile working machine by the adaptation device.
In one development, one or more parameters of the model can be adapted by the adaptation means, in particular as a function of the movement requirements and the detected and assigned states.
In one development, the adaptation means are designed via which the parameters of the model can be estimated recursively from the motion requirements and the detected, assignable or assigned states.
In one development, the adaptation device has, for the adaptation, a termination condition depending on the state predicted by the model and the detected state.
In one development, the model has a static part, in particular a static input nonlinearity, a value look-up table or a family of characteristic curves, and a dynamic part, in particular a linear state space model. The two parts are for example combined in a Hammerstein model.
In one development, the working device has an adjustment device by means of which deviations of the state from the movement requirement can be compensated. During the adaptation, the regulating device leads to a continuous improvement of the learned/adapted model/the parameters, so that the deviation between the movement requirement and the actually achieved (assigned) state becomes smaller and smaller.
In one development, the adaptation means can be deactivated after the adaptation has taken place, in particular after a termination condition has been reached, and can be activated, in particular when required.
In one development, the adjusting device is also designed to be deactivated after the adaptation and in particular to be activated when required.
In one development, a defined, in particular standardized, commissioning cycle of the working device is stored in the control device for execution. The model, in particular the parameters of the model, can thus be adapted particularly quickly and in a manner that is easy to reproduce and analyze.
In one development, the working device has a hydrostatic pump and a valve arrangement for supplying pressure medium to the actuator.
A mobile working machine has a working apparatus designed according to at least one of the foregoing aspects of the invention. The applicant reserves the right to make a patent claim or a patent application for such a working machine.
A method for controlling a hydrostatic working machine, which working machine is designed according to at least one aspect of the preceding description, having the steps of: "detecting a movement request", "determining an output variable of a control device from a model", "actuating an actuator from the output variable", "detecting an actuator state that can be assigned or has been assigned to the movement request or to the output variable". According to the invention, one step is "adapting the model or the inversion of the model according to the motion requirements and/or the output variables and according to the detected, assignable or assigned states".
This method has the advantages already mentioned in the description of the working device, so that it is not repeated here.
Furthermore, one advantage of the method is that the method can be migrated to a working facility. The method can be migrated to any supplier's working equipment and has the advantages described above.
The step of adapting, in particular by means of learning or adaptation by means of the adaptation means, may be carried out during a commissioning process, a modification process or a working operation of the working device. Can be performed periodically or batchwise or continuously, in particular can be stored in the adaptation means for periodic, batchwise or continuous execution. The step of adapting is in particular performed by adapting parameters of the model.
In one development, the step of "learning parameters" is performed first.
In one development, the method has the step "compensating for deviations between the states reached in accordance with the motion requirements and the assigned motion requirements". This is preferably done by the aforementioned adjusting means.
Thus, the step/the adjusting means leads to a continuous improvement of the learned/adapted parameters and the deviation between the movement demand and the assigned state becomes smaller and smaller.
After completion of the learning or adaptation phase, the step of compensation can be largely or completely dispensed with, in particular the adjustment device is dispensed with. This may allow for faster working device movements and high positioning accuracy.
In an extension of the method, the above-mentioned steps or a few of them are combined into a debugging cycle, in particular in a standardized manner. The model, in particular the parameters of the model, can thus be adapted particularly quickly and in a manner that is easy to reproduce and analyze.
Drawings
Two embodiments of a hydrostatic working machine according to the invention are shown in the drawings. The invention will now be explained in more detail on the basis of the figures in these drawings.
Figure 1 shows a logic circuit diagram of a working device according to the invention in an adaptation operation according to a first embodiment,
figure 2 shows the working device according to figure 1 in working operation after the adaptation operation,
fig. 3 shows a logic circuit diagram of a working device according to the invention in an adaptation operation according to a second embodiment, an
Fig. 4 shows the working device according to fig. 3 in a working operation after an adaptation operation.
Detailed Description
According to fig. 1, a hydrostatic working Machine 1 has a hydrostatic mechanical unit 2, which is composed of a hydrostatic assembly 4 and a mechanical kinematic element 6, a control device 8 (ECU) and an operator Interface 10, for example a joystick (Human Machine Interface).
The hydrostatic assembly 4 has components for supplying a pressure medium, such as a hydrostatic pump, a valve device or a valve block, which are shown in the form of blocks according to fig. 1. The mechanical kinematic element 6 has a hydrostatic actuator, for example a rotary motor or a lifting cylinder. These are also shown in block form according to fig. 1. Furthermore, the hydrostatic machine unit 2 has a detection device 12, by means of which at least the position and the speed of the mechanical kinematic element 6 and, if appropriate, the acceleration of the mechanical kinematic element 6 can be detected.
The detection by means of the detection device 12 can (additionally) also relate to components of the hydrostatic assembly 4.
The operator interface 10 is connected to interpretation means 14 for interpreting operator expectations regarding the movement of the working device 1. The interpretation means 14 are connected to a model of inverse kinematics 16 of the mechanical kinematic element 6. The kinematic parameters indicated by the thicker arrows are introduced in the kinematics 16.
In the control device 8 there is also stored a learning or adaptation device 18 with a corresponding learning or adaptation algorithm for execution. Furthermore, the control device 8 has a gray-box pre-controller 20, an adjusting device 22 and a signal processing device 27.
The output of the inverse kinematics 16 is connected to an input of a gray box pre-controller 20. The output of the adapter 18 is connected to the input of a gray box pre-controller 20. The output of the inverse kinematics 16 is connected to the input of the adjusting device 22 by means of an operator 26. The output of the regulating device 22 is connected to the output of the gray-box pre-controller by means of an operator 24. The output of the operator 24 is connected to the hydrostatic equipment 4 for operating the same and to the adaptation device 18.
The hydrostatic unit 4 is connected to the mechanical kinematic element 6 in a pressure medium manner.
The detection means 12 are connected to signal processing means 27. An output of the signal processing means 27 is connected to an output of the inverse kinematics 16 by means of an operator 26, wherein an output of the operator 26 is connected to an input of the adjusting means 22. The output of the signal processing means 27 is also connected to the inverse kinematics 16.
As already mentioned, the kinematic parameters of the mechanical kinematic elements 6 or of the hydrostatic actuators of the work machine 1 are introduced into the inverse kinematics 16.
In the learning or fitting operation according to fig. 1, the joystick 10 is deflected by the operator. The interpretation means 14 interpret this deflection as driver expectation and provide a signal to the inverse kinematics 16. The inverse kinematics 16 outputs an output signal to a gray box pre-controller 20 in accordance with the interpreted movement demand/interpreted driver expectations. In a first traversal, the ash tray pre-controller 20 generates signals to the hydrostatic equipment 4, in particular to the pumps and valves, in order to supply the actuators of the mechanical-kinematic elements 6 with pressure medium and to move said actuators. The detection means 12 detect the movement/position changes assigned to the original movement request and forward them to the signal processing means 27. The detected position, velocity and, if applicable, acceleration are thus forwarded from the signal processing device 27 to the arithmetic unit 26 and thus to the control device 22. In order to finally compensate for deviations between the detected position, speed, acceleration and the original and the allocated movement request, the output signal of the regulating device 22 is sent to the arithmetic unit 24 and again to the hydrostatic equipment 4 until the deviation falls below a defined threshold value.
At the same time, the output signal of the signal processing means 27 is introduced into the adaptation means 18 and the inverse kinematics 16. In a learning or adaptation operation, the adaptation device 18 intervenes in the gray-box pre-controller 20 and thus changes its output signal to the operator 24.
Fig. 2 shows the same hydrostatic working machine 1 after the end of the learning or fitting operation. The adapter device 18 is correspondingly deactivated and the gray-box pre-controller 20 is no longer accessible (the arrow marked with a horizontal line). Likewise, the regulating device 22 is deactivated (shown in dashed lines), or no longer requires intervention, since the ash box is pre-controlledThe device 20, in particular the model stored therein, is optimized by a previous intervention of the adaptation means 18 such that the state y of the mechanical kinematic element 6 detected by the detection means 12 isactWith the original assigned motion requirement ydesThere is no longer, or at least no longer, a sufficiently large deviation between them.
Fig. 3 and 4 show a second embodiment of the hydrostatic working machine 101 in a learning or fitting operation (fig. 3) and in a normal working operation (fig. 4), respectively. The features of the control means 8 and the adaptation means 18 are shown in more detail. As models of the working devices 101, they have a Hammerstein model with static input nonlinearities 28 (characteristic field), and thus a linear, dynamic state space model 30 connected in series. Furthermore, the control device 8 or the adaptation device 18 has an executable method of the least squares method 32. In a learning or fitting operation, the operator interface 10 is connected to the inputs of the devices 4, 28 and 32. Sending motion requests y to these inputs in the form of deflections of the joystick 10des. This results in a change in the pressure medium supply on the hydrostatic equipment 4 and in a movement, i.e. a speed and an acceleration, on the mechanical kinematic element 6 (hydrostatic actuator), which movement is detected by the detection device 12. Assigning of an actuator (6) to a motion request ydesActual state y ofactAnd fed back to the device 32. Least squares stored in means 32 for execution to determine the current state yactWith the original motion requirement ydesA comparison is made and parameters, such as parameters A, B, C, are adapted in the characteristic map 28 and in the dynamic state space model 30. The output of the adaptation means 18 is then the predicted movement ypred. The operation of the device 32 is continued until a termination condition is reached, which is dependent on the reached, assigned state yactAnd predicted motion ypredTo make it.
Fig. 4 shows the hydrostatic working machine 101 after termination, i.e., after the end of the learning or fitting operation according to fig. 3. The assigned state y reached by the interrupt is then interrupted according to fig. 4actFeedback to the adaptation means 18. The movement of the operator interface 10 is then requested again ydesThe control signals Drv Dmd are introduced into the models 28, 30 and only sent to the hydrostatic equipment 4, thereby resulting in a corresponding pressure medium supply to the mechanical kinematic elements 6 (actuators). The motion requirement y is due to the learning or adaptation phase performed and the adapted parameters A, B, CdesAnd to the movement demand ydesReached state yactThe deviation between them is so small that adjustment and further adaptation can be dispensed with. Thus, there is only a pure control operation with the above advantages.
A hydrostatic working unit having a learning and adaptation device is disclosed, via which a model, in particular a kinematic hydraulic model, stored in a control device can be adapted or optimized for controlling the working unit, so that a deviation between a detected state of the working unit and a movement request assigned to this state is small, negligible or zero.
Also disclosed is a method for controlling the working device, comprising the steps of: the model is adapted or optimized by means of the adaptation means in such a way that the deviation between the detected state of the working device and the motion requirement assigned to this state is small, negligible or zero. In particular, the method is stored in the adaptation means for execution.
Claims (8)
1. Hydrostatic working machine for a mobile working machine, having a hydrostatic actuator (6) and an operating device (10), via which operating device (10) a movement request (y) for the actuator (6) can be detecteddes) The movement request is an input variable of a kinematic model (16, 28, 30) of the actuator (6) stored in a control device (8), wherein the actuator (6) can be actuated as a function of an output variable of the control device (8), and the hydrostatic working unit has a detection device (12), by means of which a kinematic state (y) of the actuator (6) that can be assigned or is assigned to the movement request or the output variable can be detectedact) Which is characterized in thatAn adaptation device (18, 32) designed to be able to adapt via it at least according to the movement requirement (y)des) And the detected assigned status (y)act) To adapt the model (16, 28, 30) or the inversion of the model.
2. Work apparatus as claimed in claim 1, wherein the adaptation means (18, 32) are designed via which parameters (A, B, C) of the model (28, 30) can be adapted.
3. The working apparatus as claimed in claim 1 or 2, wherein the adaptation means (18, 32) are designed via which parameters (A, B, C) of the model (28, 30) can be estimated recursively.
4. Work apparatus according to any one of the preceding claims, wherein the adaptation means (18, 32) have for the adaptation a behaviour (y) dependent on a prediction by the modelpred) And the detected state (y)act) The termination condition of (1).
5. The working apparatus according to any one of the preceding claims, wherein the model (28, 30) has a static part (28) and a dynamic part (30).
6. Work apparatus according to any one of the preceding claims, having an adjustment device (22) via which a detected state (y) can be compensated foract) And the motion requirement (y)des) The deviation of (2).
7. The working apparatus according to any one of the preceding claims, wherein the model (16, 28, 30) is stored in inversion in the control device (8).
8. Method for controlling a hydrostatic working machine (1, 101) designed according to one of the preceding claims, having the steps of:
-detecting said motion requirement (y)des），
-determining the output variable from the model (16, 28, 30),
-manipulating the actuator (6) with the output variable,
-detecting the allocation of the actuator (6) to the motion demand (y)des) State of (y)act），
It is characterized by the steps of
-according to said motion requirement (y)des) And in dependence on the detected allocated status (y)act) To adapt the model (16, 28, 30) or the inversion of the model.
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| DE102019205297.5 | 2019-04-12 | ||
| PCT/EP2020/059728 WO2020207953A1 (en) | 2019-04-12 | 2020-04-06 | Hydrostatic working tool and method for controlling same |
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| CN113646709A true CN113646709A (en) | 2021-11-12 |
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| DE102021204544A1 (en) | 2021-05-05 | 2022-11-10 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method for operating a hydraulic cylinder of a working machine |
| DE102021205386A1 (en) | 2021-05-27 | 2022-12-01 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method for operating a hydraulic cylinder of a working machine |
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- 2020-04-06 KR KR1020217032500A patent/KR20210151812A/en not_active Application Discontinuation
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| US20170226717A1 (en) * | 2016-02-10 | 2017-08-10 | Deere & Company | Force-based work vehicle blade pitch control |
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Also Published As
| Publication number | Publication date |
|---|---|
| WO2020207953A1 (en) | 2020-10-15 |
| DE102019205297A1 (en) | 2020-10-15 |
| EP3953771A1 (en) | 2022-02-16 |
| KR20210151812A (en) | 2021-12-14 |
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