Steering control for an autonomous underwater glider （AUG） is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identifica...Steering control for an autonomous underwater glider （AUG） is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identification via in-field trials to capture current dynamic characteristics for control law reconfiguration. Hence, an online polynomial estimator is designed to update the yaw dynamic model of the AUG, and an adaptive model predictive control （MPC） controller is used to calculate the optimal control command based on updated estimated parameters. The MPC controller uses a quadratic program （QP） to compute the optimal control command based on a user-defined cost function. The cost function has two terms, focusing on output reference tracking and move suppression of input, respectively. Move-suppression performance can, at some level, represent energy-saving performance of the MPC controller. Users can balance these two competitive control performances by tuning weights. We have compared the control performance using the second-order polynomial model to that using the filth-order polynomial model, and found that the tbrmer cannot capture the main characteristics of yaw dynamics and may result in vibration during the flight. Both processor-in-loop （PIL） simulations and in-lake tests are presented to validate our steering control performance.展开更多
当静止无功发生器(Static var generator,SVG)电压外环使用传统PI控制时,存在直流侧电容电压动态响应较差、参数设计较为复杂等问题。针对这些问题,采用了基于滑模变结构的控制策略。该控制策略以dq旋转坐标系下的数学模型为基础进行研...当静止无功发生器(Static var generator,SVG)电压外环使用传统PI控制时,存在直流侧电容电压动态响应较差、参数设计较为复杂等问题。针对这些问题,采用了基于滑模变结构的控制策略。该控制策略以dq旋转坐标系下的数学模型为基础进行研究,电流内环采用PI解耦控制,电压外环采用滑模变结构控制。运用处理器在环测试(Processor in loop,PIL)将控制策略模型置于代码层面进行验证,结果证明:在电流内环参数相同的条件下,滑模变结构控制相较于传统PI控制,提高了直流侧电容电压的动态响应速率,并且避免了SVG在启动阶段出现电网侧功率因数过低的情况。展开更多
基金supported by Beihang University and Institution of China Academy of Aerospace Aerodynamics
文摘Steering control for an autonomous underwater glider （AUG） is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identification via in-field trials to capture current dynamic characteristics for control law reconfiguration. Hence, an online polynomial estimator is designed to update the yaw dynamic model of the AUG, and an adaptive model predictive control （MPC） controller is used to calculate the optimal control command based on updated estimated parameters. The MPC controller uses a quadratic program （QP） to compute the optimal control command based on a user-defined cost function. The cost function has two terms, focusing on output reference tracking and move suppression of input, respectively. Move-suppression performance can, at some level, represent energy-saving performance of the MPC controller. Users can balance these two competitive control performances by tuning weights. We have compared the control performance using the second-order polynomial model to that using the filth-order polynomial model, and found that the tbrmer cannot capture the main characteristics of yaw dynamics and may result in vibration during the flight. Both processor-in-loop （PIL） simulations and in-lake tests are presented to validate our steering control performance.
文摘当静止无功发生器(Static var generator,SVG)电压外环使用传统PI控制时,存在直流侧电容电压动态响应较差、参数设计较为复杂等问题。针对这些问题,采用了基于滑模变结构的控制策略。该控制策略以dq旋转坐标系下的数学模型为基础进行研究,电流内环采用PI解耦控制,电压外环采用滑模变结构控制。运用处理器在环测试(Processor in loop,PIL)将控制策略模型置于代码层面进行验证,结果证明:在电流内环参数相同的条件下,滑模变结构控制相较于传统PI控制,提高了直流侧电容电压的动态响应速率,并且避免了SVG在启动阶段出现电网侧功率因数过低的情况。
