Autonomous Balloon Based Adaptive Sliding Mode Control and Infinite-Horizon POMDP
Van Chung Nguyen, An Nguyen, Chuong Le, Gaurav Srikar, Thanh Nho Do, Hung La
Abstract
This paper presents a novel infinite-horizon Partially Observable Markov Decision Process (POMDP) framework with adaptive sliding mode control (ASMC) for autonomous navigation of the balloons. The proposed method integrates an altitude controller designed to account for thermodynamic and real-wind field constraints with an infinite-horizon POMDP for wind-optimal navigation. First, an adaptive sliding mode control is developed to ensure the balloon’s internal stability under uncertainties in pressure, external wind fields, and temperature. Subsequently, a reference strategy is formulated using the infinite-horizon POMDP to exploit wind dynamics for station-keeping. The system estimates wind direction in real time and computes actions based on these observations. Experimental results demonstrate the framework’s ability to converge on efficient navigation policies while compensating for partial observability of wind dynamics. This approach is particularly suited for aerial or underwater vehicles operating in stratified flow environments, offering a computationally tractable solution for real-world deployment.