What if AI doesn’t control us through force, but through convenience—predicting our thoughts, smoothing decisions, and quietly shaping our behavior without us noticing?

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

For decades, one of fusion energy’s hardest problems has been keeping superheated plasma from blasting holes in reactor walls. A United States team working on the DIII-D tokamak now reports using ...

Abstract: Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies ...

Abstract: In this paper, an improved multi-step model predictive control (MPC) algorithm is investigated for nonlinear networked control systems (NCSs) subject to stealthy denial-of-service (DoS) ...

While Gemini 3 is still making waves, Google's not taking the foot off the gas in terms of releasing new models. Yesterday, the company released FunctionGemma, a specialized 270-million parameter AI ...

Microsoft's New On-Device AI Model Can Control Your PC The 16.6GB 'Fara-7B' model is smart enough to handle buying something online or booking online travel on behalf of the user. Importantly, it runs ...

(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...

Trajectory tracking control is a core link to ensure the normal operation of robots. However, traditional trajectory tracking control methods have problems such as low operational efficiency and low ...

The goal of this repository is to implement the path tracking algorithm of mobile robot using the Nonlinear Model Predictive Control(NMPC), one of the optimal controllers. The NMPC can provide the ...