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Research on static fault-tolerant control method of thruster based on MPC

机译:基于MPC的推进器静态容错控制方法研究

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摘要

To ensure that the unmanned underwater vehicles (UUVs) can still successfully complete the corresponding tasks in the case of thrusters having faults, a novel fault-tolerant control strategy which combines the model predictive control (MPC) algorithm and the fault-tolerant reconstruction algorithm is presented in this paper. Firstly, a cascade control method based on model predictive control algorithm is introduced, and then the problem when the thrusters in the faulty condition are discussed. For different degrees of thruster fault, the method of weighted pseudo inverse and quantum particle swarm optimization (QPSO) is used for hybrid fault-tolerant control (FTC). At the same time, to overcome the limitations brought by the pseudo inverse reconstruction algorithm, an optimization criterion with the infinite norm as the cost function is introduced into the QPSO algorithm to accelerate the search for the optimal solution in the feasibility space so as to ensure the feasibility of the solution. The simulation results show that the fault-tolerant control method proposed based on MPC (FTC-MPC) in this paper can provide ideal control effects for the unmanned underwater vehicles.
机译:为确保无人驾驶水下车辆(UUV)仍然可以在具有故障的推进器的情况下成功完成相应的任务,这是一种结合模型预测控制(MPC)算法和容错重建算法的新型容错控制策略本文提出。首先,介绍了一种基于模型预测控制算法的级联控制方法,然后讨论了故障条件中的推进器的问题。对于不同程度的推进器故障,用于加权伪逆和量子粒子群优化(QPSO)的方法用于混合容错控制(FTC)。同时,为了克服伪逆重建算法所带来的限制,将与成本函数的无限规范的优化标准引入QPSO算法中,以加速可行性空间中最佳解决方案的搜索,以确保解决方案的可行性。仿真结果表明,本文基于MPC(FTC-MPC)提出的容错控制方法可以为无人水下车辆提供理想的控制效果。

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