Driving Target Machines from MATLAB App Designer
Real-time simulation is widely used to develop and validate control systems before they are deployed in vehicles, aircraft, railway equipment, marine systems and industrial machinery. As these systems become more sophisticated, however, the testing problem also grows. An engineer may need to execute hundreds of operating conditions, change parameters systematically, introduce faults, record signals and determine whether the controller responded correctly. Performing every operation manually is inefficient and can introduce inconsistencies between tests. Automation provides a more systematic alternative.
MATLAB App Designer can be used to create dedicated graphical applications that communicate with real-time target machines. Instead of requiring engineers to manipulate models and commands individually, a purpose-built application can provide controls for loading experiments, changing parameters, starting tests, monitoring signals, injecting faults and collecting results.
A capable real-time simulation platform provides the deterministic execution, I/O connectivity and integration with MATLAB and Simulink required to turn such an application into a practical engineering test environment.
From Real-Time Simulation to Automated Testing
A real-time target machine executes a mathematical model at precisely controlled time intervals while communicating with external hardware. In Hardware-in-the-Loop (HIL) testing, the target typically represents the physical plant while a real electronic control unit operates against the simulation.
Traditionally, an engineer could operate this environment manually: load a model, set initial parameters, start execution, observe measurements, stop the simulation and save the results.
That approach is practical for exploratory development but becomes cumbersome during formal validation. Test automation converts these repeated actions into a controlled workflow.
Why MATLAB App Designer?
MATLAB App Designer enables engineers to build graphical applications using familiar interface elements such as buttons, dropdown menus, tables, gauges, graphs and data-entry fields. The important point is that these controls are not merely cosmetic. MATLAB code behind the interface can communicate with the real-time testing environment.
An engineer could therefore create an application containing a Load Test button, operating-condition selectors, fault controls, live signal displays and a Run Test Sequence command. Behind these simple controls, MATLAB can perform considerably more complex operations. This approach also separates test operation from test implementation. The engineer using the test bench does not necessarily need to know the commands required to control the target machine. The application can expose only the parameters and actions relevant to the test. Consequently, a sophisticated real-time system can be operated through an interface designed around the actual engineering task.
Controlling the Real-Time Target
A useful automated test application must be able to control the target machine throughout the test lifecycle. The MATLAB application can establish communication with the target, load the required real-time application and configure parameters before execution begins. During the test, it can start and stop execution and modify selected model parameters. A good simulation platform – such as Speedgoat – provides mechanisms for changing parameters during real-time execution without rebuilding the complete model unnecessarily. This is important when hundreds of variations of essentially the same test must be performed.
Monitoring Signals in Real Time
Automation does not eliminate the need to observe what is happening during a test. Signals generated by the real-time model can be transferred to the MATLAB application and displayed through plots, numeric indicators or gauges. An engineer might monitor speed, pressure, temperature, current, voltage or controller outputs depending upon the application. App Designer can present only the information relevant to a particular test rather than exposing every internal signal in the model. This is particularly useful when a test bench is shared among engineers with different responsibilities. A controls engineer may require detailed loop behaviour, whereas another operator may need only overall status, fault indicators and pass/fail results. The interface can therefore become an application-specific dashboard sitting above the underlying real-time simulation platform.
Automating Fault-Insertion Tests
Consider an automotive braking controller. The target machine may simulate vehicle dynamics and wheel-speed sensors while the physical controller operates normally. The MATLAB application can initiate a test at a specified vehicle speed and subsequently introduce a simulated sensor fault. Instead of relying on the engineer to trigger the fault manually at approximately the correct moment, the test sequence can specify precisely when it occurs. The application can monitor whether the controller detects the failure, measure its response time and determine whether the expected fallback strategy is activated. A capable HIL platform can provide appropriate real-time I/O and fault-insertion interfaces for reproducing electrical and sensor failures. MATLAB automation can then coordinate those capabilities as part of a repeatable test sequence.
Aerospace and Railway Examples
In aerospace engineering, an automated HIL application could test a flight-control computer against a simulated aircraft model. A sequence might begin in normal flight, introduce changing wind conditions and subsequently simulate a sensor discrepancy or actuator problem.
App Designer can provide the test operator with controls for selecting the flight condition and fault scenario while MATLAB manages the underlying sequence. Relevant parameters – perhaps attitude, airspeed and control-surface commands – can be displayed live and recorded for subsequent analysis.
Railway engineering presents similar opportunities. A real traction controller can operate against a simulated train and electrical supply. Automated tests might vary train mass, track gradient, adhesion conditions and commanded acceleration. Another sequence could reproduce wheel slip or changes in supply voltage. The same test can be rerun after controller software is modified, making direct comparison possible.
Repeatability, Regression Testing and Reporting
One of the strongest reasons for automating real-time tests is repeatability. After a controller software update, engineers often need to establish that existing functions still behave correctly. An automated test suite can execute the same operating conditions, disturbances and faults that were applied to the previous software version. This forms the basis of regression testing. Rather than relying upon a limited number of manually repeated checks, extensive test libraries can be executed systematically.
Results can be stored together with test parameters, timestamps and software versions. MATLAB can process the captured data and generate plots, tables and reports for engineering review.
A good real-time simulation platform therefore needs more than computational performance. Deterministic execution, flexible I/O, parameter tuning, signal monitoring, data logging, fault insertion and close integration with MATLAB and Simulink collectively determine how effectively the platform can support automated validation.
Building an Engineering Tool Rather Than a Test Bench
Perhaps the most significant advantage of combining MATLAB App Designer with real-time simulation is that the underlying test bench can be transformed into a dedicated engineering tool. An automotive engineer could see a vehicle-test interface; an aerospace engineer, a flight-test panel; and a marine engineer, a propulsion-system console. Each application can control the same fundamental processes – configuring models, executing tests, changing parameters and analysing results – while presenting them in terminology appropriate to the application.
This also reduces dependence on specialist knowledge of the test infrastructure. Experienced simulation engineers can construct and validate the underlying models and automation logic, while other users interact with a controlled interface that exposes only the functions they require.
As embedded controllers become more complex, validation increasingly involves thousands of combinations of operating conditions and faults. Manually operating real-time test equipment cannot scale indefinitely. MATLAB App Designer provides a means of placing a practical automation layer above real-time target machines, while a platform such as Speedgoat supplies the deterministic computation, physical interfaces and HIL capabilities underneath.
The result is a test environment that can move beyond individual experiments towards systematic, repeatable and increasingly automated engineering validation.
