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Model-based design (MBD) is a mathematical and visual method of addressing problems associated with designing complex control, [1] signal processing [2] and communication systems. It is used in many motion control, industrial equipment, aerospace, and automotive applications. [3] [4] Model-based design is a methodology applied in designing embedded software. [5] [6] [7]
Model-based design provides an efficient approach for establishing a common framework for communication throughout the design process while supporting the development cycle (V-model). In model-based design of control systems, development is manifested in these four steps:
The model-based design is significantly different from traditional design methodology. Rather than using complex structures and extensive software code, designers can use Model-based design to define plant models with advanced functional characteristics using continuous-time and discrete-time building blocks. These built models used with simulation tools can lead to rapid prototyping, software testing, and verification. Not only is the testing and verification process enhanced, but also, in some cases, hardware-in-the-loop simulation can be used with the new design paradigm to perform testing of dynamic effects on the system more quickly and much more efficiently than with traditional design methodology.
As early as the 1920s two aspects of engineering, control theory and control systems, converged to make large-scale integrated systems possible. In those early days controls systems were commonly used in the industrial environment. Large process facilities started using process controllers for regulating continuous variables such as temperature, pressure, and flow rate. Electrical relays built into ladder-like networks were one of the first discrete control devices to automate an entire manufacturing process.
Control systems gained momentum, primarily in the automotive and aerospace sectors. In the 1950s and 1960s, the push to space generated interest in embedded control systems. Engineers constructed control systems such as engine control units and flight simulators, that could be part of the end product. By the end of the twentieth century, embedded control systems were ubiquitous, as even major household consumer appliances such as washing machines and air conditioners contained complex and advanced control algorithms, making them much more "intelligent".
In 1969, the first computer-based controllers were introduced. These early programmable logic controllers (PLC) mimicked the operations of already available discrete control technologies that used the out-dated relay ladders. The advent of PC technology brought a drastic shift in the process and discrete control market. An off-the-shelf desktop loaded with adequate hardware and software can run an entire process unit, and execute complex and established PID algorithms or work as a Distributed Control System (DCS).
The main steps in model-based design approach are:
The disadvantages of model-based design are fairly well understood this late in development lifecycle of the product and development.
While Model-based design has the ability to simulate test scenarios and interpret simulations well, in real world production environments, it is often not suitable. Over reliance on a given toolchain can lead to significant rework and possibly compromise entire engineering approaches. While it's suitable for bench work, the choice to use this for a production system should be made very carefully.
Some of the advantages model-based design offers in comparison to the traditional approach are: [9]
Because of the limitations of graphical tools, design engineers previously relied heavily on text-based programming and mathematical models. However, developing these models was time-consuming, and highly prone to error. In addition, debugging text-based programs is a tedious process, requiring much trial and error before a final fault-free model could be created, especially since mathematical models undergo unseen changes during the translation through the various design stages.
Graphical modeling tools aim to improve these aspects of design. These tools provide a very generic and unified graphical modeling environment, and they reduce the complexity of model designs by breaking them into hierarchies of individual design blocks. Designers can thus achieve multiple levels of model fidelity by simply substituting one block element with another. Graphical models also help engineers to conceptualize the entire system and simplify the process of transporting the model from one stage to another in the design process. Boeing's simulator EASY5 was among the first modeling tools to be provided with a graphical user interface, together with AMESim, a multi-domain, multi-level platform based on the Bond Graph theory. This was soon followed by tool like 20-sim and Dymola, which allowed models to be composed of physical components like masses, springs, resistors, etc. These were later followed by many other modern tools such as Simulink and LabVIEW.
A simulation is an imitative representation of a process or system that could exist in the real world. In this broad sense, simulation can often be used interchangeably with model. Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Another way to distinguish between the terms is to define simulation as experimentation with the help of a model. This definition includes time-independent simulations. Often, computers are used to execute the simulation.
An embedded system is a specialized computer system—a combination of a computer processor, computer memory, and input/output peripheral devices—that has a dedicated function within a larger mechanical or electronic system. It is embedded as part of a complete device often including electrical or electronic hardware and mechanical parts. Because an embedded system typically controls physical operations of the machine that it is embedded within, it often has real-time computing constraints. Embedded systems control many devices in common use. In 2009, it was estimated that ninety-eight percent of all microprocessors manufactured were used in embedded systems.
Computer simulation is the running of a mathematical model on a computer, the model being designed to represent the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics, astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.
In computing, a visual programming language, also known as diagrammatic programming, graphical programming or block coding, is a programming language that lets users create programs by manipulating program elements graphically rather than by specifying them textually. A VPL allows programming with visual expressions, spatial arrangements of text and graphic symbols, used either as elements of syntax or secondary notation. For example, many VPLs are based on the idea of "boxes and arrows", where boxes or other screen objects are treated as entities, connected by arrows, lines or arcs which represent relations. VPLs are generally the basis of Low-code development platforms.
Simulink is a MATLAB-based graphical programming environment for modeling, simulating and analyzing multidomain dynamical systems. Its primary interface is a graphical block diagramming tool and a customizable set of block libraries. It offers tight integration with the rest of the MATLAB environment and can either drive MATLAB or be scripted from it. Simulink is widely used in automatic control and digital signal processing for multidomain simulation and model-based design.
VisSim is a visual block diagram program for the simulation of dynamical systems and model-based design of embedded systems, with its own visual language. It is developed by Visual Solutions of Westford, Massachusetts. Visual Solutions was acquired by Altair in August 2014 and its products have been rebranded as Altair Embed as a part of Altair's Model Based Development Suite. With Embed, virtual prototypes of dynamic systems can be developed. Models are built by sliding blocks into the work area and wiring them together with the mouse. Embed automatically converts the control diagrams into C-code ready to be downloaded to the target hardware.
Hardware-in-the-loop (HIL) simulation, also known by various acronyms such as HiL, HITL, and HWIL, is a technique that is used in the development and testing of complex real-time embedded systems. HIL simulation provides an effective testing platform by adding the complexity of the process-actuator system, known as a plant, to the test platform. The complexity of the plant under control is included in testing and development by adding a mathematical representation of all related dynamic systems. These mathematical representations are referred to as the "plant simulation". The embedded system to be tested interacts with this plant simulation.
Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mock up of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome.
Dynamic simulation is the use of a computer program to model the time-varying behavior of a dynamical system. The systems are typically described by ordinary differential equations or partial differential equations. A simulation run solves the state-equation system to find the behavior of the state variables over a specified period of time. The equation is solved through numerical integration methods to produce the transient behavior of the state variables. Simulation of dynamic systems predicts the values of model-system state variables, as they are determined by the past state values. This relationship is found by creating a model of the system.
MapleSim is a Modelica-based, multi-domain modeling and simulation tool developed by Maplesoft. MapleSim generates model equations, runs simulations, and performs analyses using the symbolic and numeric mathematical engine of Maple. Models are created by dragging-and-dropping components from a library into a central workspace, resulting in a model that represents the physical system in a graphical form. Maplesoft began development of MapleSim partly in response to a request from Toyota to produce physical modeling tools to aid in their new model-based development process.
SimulationX is a CAE software application running on Microsoft Windows for the physical simulation of technical systems. It is developed and sold by ESI Group.
Continuous Simulation refers to simulation approaches where a system is modeled with the help of variables that change continuously according to a set of differential equations.
MLDesigner is an integrated modeling and simulation tool for the design and analysis of complex embedded and networked systems. MLDesigner speeds up modeling, simulation and analysis of discrete event, discrete time and continuous time systems concerning architecture, function and performance. The tools is based on ideas of the "Ptolemy Project", done at the University if California Berkeley. MLDesigner is developed by MLDesign Technologies Inc. Palo Alto, CA, USA in collaboration with Mission Level Design GmbH, Ilmenau, Germany.
20-sim is a commercial modeling and simulation program for multi-domain dynamic systems, which is developed by Controllab. 20-sim allows models to be entered as equations, block diagrams, bond graphs and physical components. 20-sim is used for modeling complex multi-domain systems and for the development of control systems.
dSPACE GmbH, located in Paderborn, Germany, is one of the world's leading providers of tools for developing electronic control units.
Simcenter Amesim is a commercial simulation software for the modeling and analysis of multi-domain systems. It is part of systems engineering domain and falls into the mechatronic engineering field.
System-level simulation (SLS) is a collection of practical methods used in the field of systems engineering, in order to simulate, with a computer, the global behavior of large cyber-physical systems.
Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products. It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.
Micro Saint Sharp is a general purpose discrete-event simulation and human performance modeling software tool developed by Alion Science and Technology. It is developed using C# and the .NET Framework. Micro Saint Sharp allows users to create discrete-event simulations as visual task networks with logic defined using the C# programming language.
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