Hierarchical Depth Tracking Control Under Rudder Saturation
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Solution Overview
Problem
Existing underwater vehicles face challenges in achieving high-precision depth tracking due to strong coupling and nonlinearity in dynamics, complex underwater environments, inaccurate hydrodynamic parameter acquisition, and thruster output limits leading to control saturation and instability.
Innovation Solution
A three-layer hierarchical control system incorporating an adaptive line-of-sight guidance algorithm, nonlinear interference observer, and STSMC controller with adaptive saturation compensation to enhance depth tracking performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional control methods are used for underwater vehicle depth tracking, then the control system is simple, but the control precision deteriorates due to strong coupling and high nonlinearity
Solution Approach 1:
The control system is divided into three hierarchical layers: motion control layer (outer loop) for trajectory planning, dynamic control layer (middle loop) for attitude control, and actuator control layer (inner loop) for thruster control. This segmentation allows each layer to handle specific control tasks independently, improving depth tracking precision while maintaining manageable system complexity.
Solution Approach 2:
A nonlinear interference observer is introduced as an intermediary component to estimate and compensate for unknown disturbances and hydrodynamic parameter uncertainties. The observer acts as a mediator between the control commands and the actual system response, enhancing tracking precision without requiring complex model adjustments.
2Measurement precision
If adaptive line-of-sight guidance algorithm is adopted to estimate angle of attack in real time, then guidance accuracy is improved, but device complexity increases
Solution Approach 1:
The adaptive line-of-sight guidance algorithm performs preliminary estimation of the angle of attack and generates expected pitch angle commands before the main control execution. This preliminary action allows the subsequent dynamic control layer to focus on attitude regulation, improving overall guidance accuracy while distributing computational complexity across different time scales.
3Stability of the object's composition
If STSMC controller with adaptive saturation compensation is adopted, then control stability is improved, but device complexity increases
Solution Approach 1:
An adaptive saturation compensator is integrated into the STSMC controller to provide real-time feedback on control saturation status. The compensator monitors the actual thruster outputs and adjusts the control commands accordingly, preventing integral windup and maintaining control stability during saturation conditions. This feedback mechanism enhances stability without requiring fundamental changes to the controller architecture.
Solution Approach 2:
The controller dynamically adjusts control parameters based on the saturation state of the actuators. When saturation is detected, the adaptive compensator modifies the control gains and command signals to maintain stability. This parameter adaptation allows the system to handle nonlinear actuator limitations while preserving the core STSMC control structure.
4Measurement precision
If nonlinear interference observer is adopted to observe unknown interference, then observation accuracy is improved, but device complexity increases
Solution Approach 1:
The nonlinear interference observer utilizes the system's own state measurements and control inputs to estimate unknown disturbances and hydrodynamic parameter uncertainties. By leveraging available sensor data and the known system dynamics, the observer achieves accurate interference estimation without requiring additional external sensors or complex measurement systems.
Data Source
AI summary
This disclosure provides an adaptive STSMC hierarchical control method for depth tracking of an underwater vehicle. The method includes: using an adaptive line-of-sight guidance algorithm to estimate the vehicle's angle of attack in real time and obtain an expected pitch angle; employing a nonlinear interference observer based on a sliding mode surface error to detect unknown interference; and applying an STSMC controller with adaptive saturation compensation to determine the expected control rudder angle from the sliding mode surface error, the expected pitch angle, and the observed interference. The adaptive saturation compensation corrects the rudder angle based on the saturation deviation, which is determined by the previously calculated expected control rudder angle and the actual output rudder angle at the previous moment. By introducing an adaptive saturation compensator in the dynamic control layer, the issue of rudder angle saturation is mitigated, thereby enhancing both control performance and stability.