You're working on a project that requires control engineering tools. What do you need to know?

1 System modeling

System modeling is the process of creating a mathematical representation of a physical system, based on its inputs, outputs, and internal dynamics. System models can be used to analyze, simulate, and predict the system's behavior under different conditions and scenarios. System modeling can involve various techniques, such as differential equations, transfer functions, state-space models, or block diagrams.

2 Feedback control

Feedback control is the method of using the output of a system to adjust its input, in order to achieve a desired output or performance. Feedback control can be used to reduce errors, disturbances, or uncertainties in the system, and to improve its stability, accuracy, or efficiency. Feedback control can be classified into two types: open-loop and closed-loop. Open-loop control does not use any measurement of the output to modify the input, while closed-loop control does.

3 Control design

Control design is the process of selecting and tuning the parameters of a controller, which is the device or algorithm that determines the input to the system based on the feedback. Control design can involve various methods, such as root-locus, frequency response, or state feedback. Control design can also consider different objectives, such as performance, robustness, or adaptability.

4 Control implementation

Control implementation is the process of applying the controller to the system, either in hardware or software. Control implementation can involve various challenges, such as sensor noise, actuator limitations, or communication delays. Control implementation can also require various tools, such as microcontrollers, programmable logic controllers, or real-time operating systems.

5 Control testing

Control testing is the process of verifying and validating the functionality and performance of the controller and the system. Control testing can involve various steps, such as simulation, emulation, or experimentation. Control testing can also use various metrics, such as error, stability, or efficiency.

6 Control optimization

Control optimization is the process of finding the optimal or best controller and system configuration, according to some criteria or constraints. Control optimization can involve various techniques, such as linear programming, nonlinear programming, or evolutionary algorithms. Control optimization can also address various problems, such as multi-objective, multi-variable, or multi-modal optimization.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?