Using simulation software to simplify DSP-based Electro-Hydraulic Servo Actuator Designs: Part 3
Now that we have modelled the basic equations and dynamics we need in
1 and Part
2 in this series, how does this work in a typical
For the purposes of this series of articles we will use data based on a symmetrical, double-ended actuator with a total stroke of around 100mm and an active piston area of around 1 inch. Piston mass may be specified by the manufacturer, or can be calculated from a knowledge of the geometry of the actuator. For a piston of this size, a mass of around 9 Kg would be typical.
The DSP controller used in this design is a TMS320C28x DSP with a 32-bit fixed-point DSP core, a low latency interrupt mechanism, and an instruction set including "atomic" instructions. Pertinent information on the actuator and servo-valve is summarized in Table 1 and Table 2, below.
|Table 1: Actuator data|
|Table 2: Servo-valve data|
Other useful data is derived from knowledge of the system. Leakage and frictional effects could be modelled using coefficient values estimated from empirical data, as shown in Table 3, below.
|Table 3: Miscellaneous system data|
Matlab Simulation results
A simple test which yields useful information about the performance of the system is to apply a small step signal to the input and monitor the response. In Simulink, this can be simply achieved using a 'scope' block to monitor command and response signals.
The vertical axis is graduated in volts measured at the error amplifier. The controller is scaled to a range of +/- 10V, so for a 100mm stroke actuator, a step input of +2V corresponds to a piston displacement of +10mm from the central position.
Controller gain terms are adjusted and the step test repeated to tune the actuator response as required. The plot shown in Figure 12 below represents a satisfactory compromise between rise time and overshoot, and the corresponding controller settings would serve as a useful starting point for the control engineer when testing the real system.
|Figure 12. Simulated Actuator Step Response|
By configuring the actuator chamber pressures as test points in Simulink, a 'floating scope' block may be used to monitor these and other signals during the step response test.
The graph below in Figure 13 shows the behavior of the chamber pressures during the step response simulation. Chamber B pressure (Pb) is shown as a continuous line, and chamber A pressure (Pa) a dashed line. The vertical axis is in Pascals (N/m). The slight asymmetry results from the change in chamber volumes as the piston is displaced to its new position.
|Figure 13. Step Response of Piston Chamber Pressures|
Figure 14 below shows the step response of a real high-performance linear actuator with dimensions similar to those describe earlier. The sharp rising and falling edges and minimal overshoot represent the optimum response that can be obtained with a PID control strategy and a good quality actuator.
|Figure 14. Step Response of High-Performance Linear Actuator|
The dynamic performance of the system is limited by the capacity of the hydraulic power supply as well as the performance of the servo-valve. This is illustrated by Figure 15 below, in which a large sinusoidal command input is applied and the frequency gradually increased.
|Figure 15. Frequency Response of High-Performance Linear Actuator|
The curve shows two high frequency asymptotes: the first occurs at about 8 Hz and is caused by the limited flow capacity of the power supply. The second, at about 40 Hz, is the high frequency response limit of the servo-valve.
The importance of friction in a high performance actuator is demonstrated by the following two displacement/time graphs below. Both show the behavior of a linear servo-actuator when subjected to a low-frequency, low amplitude sinusoidal command input. The first in Figure 16 shows a low friction actuator, and the second in Figure 17 illustrates an actuator with higher friction caused by tighter piston and end cap oil seals.
|Figure 16. Low Frequency Test on Low Friction Linear Actuator|
|Figure 17. Low Frequency Test on Linear Actuator with Significant Friction|
Response losses caused by friction in the actuator can be reduced to
some extent by the addition of "dither" to the controller output. This
is a relatively high frequency, constant amplitude oscillation, which
keeps the valve spool in constant motion and reduces the break-away
force needed to overcome any
static friction present in the system.
The use of Simulink to model and design the system allows enhancements such as this to be easily added to the digital controller.
The principal non-linear effects in hydraulic systems arise from the compressibility of hydraulic fluid, the complex flow properties of the servo-valve, and internal friction in the actuator. These depend on physical factors which are difficult to measure accurately and for this reason simulation results should be supported by experimental testing whenever possible.
Conventional feedback control techniques work well in cases where dead reckoning of the above factors is possible or where their influence is sufficiently small that they can safely be ignored. However, for true high-performance control advanced digital control techniques are required and in this the DSP excels.
The performance of a high quality hydraulic actuator is very dependent on the servo-controller and DSPs lend themselves well to implementing real-time control algorithms necessary. Moreover a DSP allows the designer of a PID or servo controller to implement advanced control strategies, including multi-variable and complex control algorithms using modern intelligent methods such as neural networks and fuzzy logic.
Also available is the ability to perform adaptive control, in which the algorithm dynamically adapts itself to match variations in system behavior. A DSP-based PID controller allows the developer to implement complex topologies such as multi-axis control where synchronization of multiple force patterns is required and perform diagnostic monitoring, including frequency spectrum analysis to identify mechanical vibrations and predict failure modes.
As pressure grows for faster time to market of new products with more stringent safety features, increasing emphasis is being placed on the use of high-level tools and software for application development. These afford a level of abstraction from the processor core, and permit rapid application development and re-use of material.
For complex control applications, the ability to simulate controller
and plant behavior at the design phase is invaluable, and the use of
embedded auto-code generation and validation features affords the
designer the ability to move quickly and easily from simulation to
prototyping. This is a powerful advantage and we may expect the trend
towards integrated system simulation and code development to continue
in the coming years.
To read Part 2, go to "Using modelling tools to simplify hydraulic PID system design."
Richard Poley is Field Application Engineer at Texas Instruments with focus on digital control systems.
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