{
    "success": true,
    "data": {
        "id": 1660530,
        "msgid": "brin-develops-ai-based-control-system-for-sea-wave-simulator-1775613252",
        "date": "2026-04-07 11:54:31",
        "title": "BRIN Develops AI-Based Control System for Sea Wave Simulator",
        "author": "",
        "source": "ANTARA_ID",
        "tags": "",
        "topic": "Technology",
        "summary": "Indonesia's National Research and Innovation Agency (BRIN), through its Satellite Technology Research Centre (PRTS) and Hydrodynamics Technology Research Centre (PRTH), has developed an AI-based control system for a sea wave simulator to address limitations in direct maritime technology testing at sea. The system utilises trajectory generation, inverse kinematics, and an optimised Proportional-Integral-Derivative (PID) controller enhanced by the Salp Swarm Algorithm (SSA), achieving superior performance with a 16.8% lower error rate compared to Genetic Algorithm and 8.7% lower than Particle Swarm Optimization. This innovation holds significant potential for applications in ship design, offshore technology, and wave compensation systems on marine platforms, with future research focusing on nonlinear control methods for complex dynamics.",
        "content": "<p>Jakarta (ANTARA) - The National Research and Innovation Agency\n(BRIN), through the Satellite Technology Research Centre (PRTS) and the\nHydrodynamics Technology Research Centre (PRTH), is developing an\nartificial intelligence (AI)-based control system for a sea wave\nsimulator. Wibowo Harso Nugroho, Head of the Marine and Offshore\nStructures Technology Research Group at PRTH BRIN, explained that the\ndevelopment of this simulator provides a solution to the limitations of\ntesting maritime technology directly at sea. In the developed system,\nWibowo stated, the sea wave model is converted into a motion trajectory\nthrough a trajectory generation process, then transformed into platform\nleg movements using the inverse kinematics method. The\nProportional-Integral-Derivative (PID) control system, optimised with\nthe Salp Swarm Algorithm (SSA), subsequently ensures that the platform\u2019s\nmovement can follow the wave pattern with minimal error. He assessed\nthat incorporating AI-based algorithms provides significant advantages\nin the control system optimisation process. Research results show that\nthe SSA method produces the best performance with a lower error value\n(fitness value), namely 16.8 percent compared to the Genetic Algorithm\nand 8.7 percent compared to Particle Swarm Optimization. \u201cThe SSA\napproach allows us to obtain optimal control parameters with a lower\nerror rate compared to other methods such as the Genetic Algorithm and\nParticle Swarm Optimization,\u201d he said. Wibowo mentioned that the\ndevelopment of this sea wave simulator has broad application potential,\nincluding for ship design, offshore technology, and wave compensation\nsystems on marine platforms. In the future, research will be directed\ntowards developing nonlinear control methods to enhance system\nperformance under more complex dynamic conditions.<\/p>",
        "url": "https:\/\/jawawa.id\/newsitem\/brin-develops-ai-based-control-system-for-sea-wave-simulator-1775613252",
        "image": ""
    },
    "sponsor": "Okusi Associates",
    "sponsor_url": "https:\/\/okusiassociates.com"
}