Übersetzung für "Reglerentwurf" in Englisch

The controller was designed and simulated using Matlab/Simulink software.

The existing controller structures are complex and have decoupled controllers for the two manipulated variables, which usually makes a systematic controller design impossible.

It is therefore the object of the invention to provide a method and a device for controlling the outlet pressure of a compressor unit which has a simple structure and makes a systematic controller design possible.

DE 199 40 137 describes a design method, in which the parameters C r and L r are used in the controller design.

Once the bypassing service and the associated bypass hooks are integrated in the ECU code, control engineers can perform controller design in the Simulink model, flexibly defining which ECU variables are to be read or written as input or output variables for the internal bypass functions and which bypass functions are to be triggered by the hooks.

Typical steps include the control design, the iterative validation and verification (based on simulation), and the code integration on the ECU.

For the actual exemplary controller design, use is made of what is referred to as an envelope curve model which describes the dynamics of the Fourier coefficients of the system variables.

For the actual controller design, preferably what is referred to as an envelope curve model is used, which model describes the dynamics of the Fourier coefficients of the system variables.

However, without consideration of the robustness during the controller design, erroneous models would result in losses in performance and possibly even in stability.

A typical application here is the control unit design, that—depending on which authoring tool is used—can, for example, can be carried out in line with so-called rapid control prototyping (RCP).

From these observations, it follows that, for the design of the regulator, the load current during the turn-on operation is determined as the sum of the current in the MOS channel imos and that component of the bipolar current (left-hand summand in (1)) which is determined by the coupling of the hole and electron transport.

The proposed control design approaches lead to stable closed loops but the reference step responses (if considered at all) are slow and exhibit underdamped oscillations.

For controller design, the battery emulator and the load are modeled separately and then combined into one system model.

In the next step, in the so-called rapid control prototyping (RCP), the abstract controller prototype is converted by means of code generators to an executable program, which is operated on a usually very high-performance, real-time-capable control system, not comparable to the series control system ultimately to be used. This RCP control system then interacts via corresponding I/O interfaces with the real process being influenced.

However, the differential equations (22) and (23) are not suitable for the regulator design because of the strong nonlinearity.

In a further advantageous embodiment of the engineering tool, the automatically determined weighting factors are not used directly for the controller design but rather can be altered beforehand by an operator using an operator control appliance to which they are output.

A typical application here is the control unit design, that—depending on which authoring tool is used—can, for example, can be carried out in line with so-called rapid control prototyping (RCP).

It should be pointed out that the evaluation presented here is a summary of the observations which are especially intended to serve for the design of the controller described below rather than to serve for the interpretation of the results.

Model-based control design is the time-saving, cost-effective approach, because control engineers work with just a single model of a function or complete system in an integrated software environment.

The objective is to train and apply the methods presented in the lecture for modern modelbased controller design for linear systems and the design of the required design tools.

You can use these operating points to initialize a simulation at steady state or as a basis for linearization and control design.

The area of instrumention and control is a technically profound field involving mechanical, thermodynamic, physical, chemical or biological systems, mathematical modelling and controller design. It requires extensive knowledge and understanding of processes and systems as well as a high level of engineering competency.

The dSPACE prototyping systems allow developers to concentrate completely on the new function design without having to worry about computing power and memory space – the system offers plenty of both, ensuring maximum flexibility.

The development of a control system that is ultimately usable in series production is generally accomplished in the following steps: during function development, by means of mathematical modeling tools, an abstract controller prototype is initially made from the later target hardware and environment, during which the controller so developed is only tested in a simulation with the process image, which also only exists as a mathematical model.