Learn about the common types of control algorithms for robot motion planning and navigation, and how to select the best one for your environment and goal. Agree & Join LinkedIn ...

This article presents a new fast and robust algorithm that provides fuel-optimal impulsive control input sequences that drive a linear time-variant system to a desired state at a specified time. This ...

This paper proposes a novel optimal adaptive event-triggered control algorithm for nonlinear continuous-time systems. The goal is to reduce the controller updates, by sampling the state only when an ...

The core area of expertise are embedded optimization algorithms, i.e. methods for real-time optimization on embedded platforms, with a focus on nonlinear systems. The work of the group spans from ...

Learn about five popular control techniques for nonlinear systems in electrical engineering and how to select the best one based on performance, robustness, complexity, and stability.

The DDPG algorithm was based on and developed from the DQN algorithm. It mainly uses an actor network to make up for the shortcoming that DQN cannot deal with continuous control problems. The DDPG is ...

This project was delivered as part of the Optimal Control course held by professor Notarstefano at University of Bologna.. The related task description can be read here. The report where we discuss in ...

New machine learning algorithm promises advances in computing Digital twin models may enhance future autonomous systems Date: May 9, 2024 Source: Ohio State University ...