Design, test and implementation of control software & associated components. Comprehensive end to end solution, using the latest model-based design and simulation tools to deliver high-integrity software and reliable hardware, covering all stages of the development cycle – from plant modeling to designing and tuning control algorithms and supervisory logic, all the way to deployment and system verification, validation and test.
Strategies and methodologies used successfully on a wide range of applications covering land, sea and air.
Rapid test and iteration of control strategies with real hardware such as drives and motors (PM synchronous motor, brush-less DC motor, stepper motor).
High fidelity closed-loop controls leveraging low-latency I/Os and FPGAs
Real-time testing of controls algorithms
Embedded design optimization using a real-time system data
- Agile System Development – Deliver software-enabled systems through rapid and continuous development, to deliver designs faster while supporting changing requirements
- Preventative maintenance – Used to detect & prevent impending failures of critical equipment
- Real-Time Simulation and Testing – Test control systems and signal processing algorithms on hardware in real time
- Physical Modeling – Accelerate control design and system-level analysis with physical system models
Solutions successfully applied to:
- Flight avionics systems
- High power density EV (Electric Vehicle) motor and battery systems
- Intelligent controller-based energy management systems for solar power systems and AC & DC distributed power networks
- High altitude applications using energy efficient control and monitoring systems
- Remote vehicle operation using cutting-edge communication & connectivity technology
- Control systems for hydro-foiling sailing craft
- Control systems for manned & unmanned vehicles
LinearLab utilizes MBD tools to support projects in engineering, science and sport. Enabling rapid turnaround of software and hardware implementation requirements into generated code for embedded deployment and creating sophisticated test suites for system verification, saving time and avoiding the introduction of manually coded errors.
LinearLab’ s continued investment in the latest MDB design tools have proven to be key in our ability to deliver a high-quality product and reduce development time.
Key features of a Model-Based Design environment:
- Links a common design environment across multi-discipline platforms and teams
- Efficiently connect designs directly to requirements
- Integrate testing with design
- Refine algorithms through multidomain simulation
- Automatically generate embedded software code and documentation
- Continued development and reuse of test suites for multiple sub-systems
Reduce Risks and Save Costs
- Systems are configured to meet the project specific I/O, sample rate, and environmental requirements now and in the future.
- No need to redesign complete controller designs in early stages: Systems can be expanded with additional I/O in the future, and CPU with higher capacity in case sample rate and frequency requirements increase.
- Automate extensive tests with physical hardware at a very early stage, and reduce the likelihood of costly design flaws
Reduce Design-to-Implementation time
- Seamless design and engineering workflow support along the entire development cycle including modeling, prototyping, testing, documentation, and embedded integration
- Continuously try new ideas and concepts using an independent development platform, while not losing any time or emphasis on the design target
- Hydro foil motion control systems
- Autopilot systems for sea-based vehicles using custom trajectory-planning techniques
Human-machine Interface (HMI) Controllers & Design
In-depth knowledge and experience used for specialist interface design between the physical control system and its operator(s) to greatly impact effectiveness and ease of use and promote a harmonized connection between the two.
Compliance with all relevant ergonomic, safety, and engineering standards is required to complete each step of the design and implementation process.
Clear definitions of the functional requirements, the operator’s level of expertise, and any communications and interactions with other sub-systems provide the starting point in this knowledge-intensive design process.
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