Our Core Competencies
“We choose to do these things, not because they are easy, but because they are hard; because that goal will serve to organize and measure the best of our energies and skills, because that challenge is one that we are willing to accept, one we are unwilling to postpone.” President J.F.K., 1962.
Providing insight into processes and interactions that determine system function, performance, and nonfunctional attributes
Mathematical Modeling
Mathematical Modeling
We use mathematical modeling to understand the key inputs, outputs, parameters, and interrelationships that affect system behavior so that we can explore the decision-space prior to committing to hardware, software, personnel, and financial resources. We believe that it is important to build properly-scoped, credible models that have the appropriate fidelity level relative to the problem and design phase.
We deliver well-documented descriptions of these models and link them to your requirements. We can provide the necessary training in any theory that may be required.
Physical Modeling
Physical modeling is mathematical modeling applied to physical entities: things like motors, generators, gear-trains, sensors, actuators, and other real-world systems. We use bond graphs to perform physical modeling so that we can understand how energy is used, stored, and managed across the system to determine where efficiencies may be obtained and to understand how failures can propagate.
We implement these models using our Simbus Bondgraphs™ product and we will provide a run-time license if required.
Physical Modeling
Simulation
Simulation
We can create shareable Simulation Models that embody the Mathematical Models and Physical Models of your systems and processes. Simulation Model development iterates with Mathematical Modeling and Physical Modeling so that efficient Simulation Models are obtained. Efficient Simulation Models are essential of they are to execute in appropriate timescales and with efficient computing resource usage.
We can deliver models in MATLAB®, Simulink® (including Simbus Bondgraphs™), C / C++, or a combination of them.
Control Systems, Signal Processing, and Algorithm Design
We design and analyze algorithms for cyber-physical systems: algorithms that have an interface with the physical world. These include control systems for accurate positioning, fluid metering, and power regulation but also algorithms for measurement and sensing such as in accelerometers, gyroscopes, and distributed sensors as found in IoT systems.
We have experience in many design techniques including PID, multivariable robust control, Kalman Filter / Extended Kalman Filter, and state machine design.
Control Systems, Signal Processing, and Algorithm Design
Systems Engineering
Systems Engineering
We employ Systems Engineering to perform the following transformations:
Needs into requirements,
Requirements to modes and functions,
Modes and functions to functional architectures, and
Functional architectures to physical architectures (designs).
We balance competing constraints by considering how well candidate solutions accomplish the mission objectives, integrate with the end-user’s organization, and interoperate with other mission applications.
System Architecture
A System Architecture is the end result of an iterative process that considers the Functional Architecture – the relationship between the functions required to perform the required mission – and the Physical Architecture – the relationship between the formal elements used to deliver function.
We identify the key problem to be solved by your new system, identify the essential stakeholders and their needs, define a robust architecture that balances those needs whilst maximizing benefit over cost through the system lifespan. We blend mathematical modeling with qualitative techniques appropriately to identify and evaluate candidate architectures.
System Architecture
