Project Balanced Optimal Control for Scalable Technologies (BOOST) focuses on the development of numerically efficient methods for near-optimal control suitable for real-time implementation on embedded platforms. The main consideration is placed on embedded model predictive control (MPC), taking advantage of distributed optimization, complexity reduction, and robustness under physical constraints and uncertainties. The approach ensures closed-loop stability and recursive feasibility while minimizing computational and energy costs. The methods will be validated via simulations and experimental setups, delivering open-source software tools. The project involves international cooperation to integrate state-of-the-art techniques, targeting applications in the chemical industry with scalability to broader industrial domains.