Dynamics & Control
Current literature Aircraft Dynamics Models in the open loop situation are categorized as having Phugoid and Short-Period Modes and are designed for closed loop stability separating the dynamics under `fast dynamics (short period)' and `slow dynamics (phugoid)' type time scale separation viewpoint which introduces non-robustness. Our RES CSSP Tool-Box designs do not need such assumptions. They promise very high robust stability margins for various types of perturbations.
Dynamics & Control
Rotorcrafts such as Helicopters and multi-copters operate under more stringent air mobility constraints and have very little or even no static margins at all making them much more difficult to control than fixed wing aircrafts. So these applications need much more reliable and sophisticated robust control systems such as those offered by RES CSSP Tool-Box.
Altitude & Orbit Control Systems
Satellite and Orbit Control systems operate under very stringent performance requirements such as micro-radian pointing accuracies under the presence of many external disturbance torques and orbital perturbations. In addition, complex orbit maneuvers (like docking) and station keeping requirements make satellite attitude control and dynamic stability issues a challenging task. Hence for such complex space applications, a highly robust, trustworthy and performance achieving intelligent control algorithms such as those offered by RES CSSP Tool-Box become a necessity.
Dynamics & Control
Together, Robotics and AI dance on the edge of certainty, their steps guided by algorithms and sensors, yet swayed by the winds of randomness. They promise efficiency, convenience, and progress, but their journey is one of perpetual adaptation - a tango with the unknown.
Dynamics & Control
Autonomy, the beacon of self-governance, illuminates the path for a new breed of systems - Autonomous Systems. These digital entities, akin to sentient chess players, navigate the intricate board of reality with minimal human intervention.
Dynamics & Control
Smart material structures, like intricate puzzles, combine the elegance of design with the unpredictability of their responses. These structures - woven from shape-memory alloys, piezoelectric ceramics, and other responsive materials - hold immense promise across various domains. However, their implementation demands a delicate dance between innovation and pragmatism.
Dynamics & Control
ML models learn from data and make predictions or decisions based on patterns they discover. RL agents learn by interacting with an environment to maximize a reward signal. DL models, especially neural networks, have revolutionized various domains. Uncertainty arises due to various factors like Data Quality, Model Complexity, Hyperparameters, Environment Dynamics.
Dynamics & Control
Turbine-based combined cycle (TBCC) engines are considered ideal for reusable air-breathing supersonic aircraft. During mode transition, the operating point of the engine changes significantly, leading to fluctuations in airflow. Integrated control methods aim to optimize both flight trajectory and TBCC control law for TBCC-powered aircraft.
