论文标题
双重自适应MPC使用精确的设置会员重新构造
Dual adaptive MPC using an exact set-membership reformulation
论文作者
论文摘要
在这项工作中考虑了使用设置会员识别来减少参数不确定性的自适应模型预测控制（MPC）方法。强二元性用于重新重新制定MPC优化范围内的设置会员方程。然后，使用预测的最差成本来实现面向性能的探索。提出的方法保证了强大的约束满意度和递归可行性。结果表明，可以使用状态管的同型管和柔性试管参数化来实现方法，模拟研究表明了对最先进的控制器的性能改善。
Adaptive model predictive control (MPC) methods using set-membership identification to reduce parameter uncertainty are considered in this work. Strong duality is used to reformulate the set-membership equations exactly within the MPC optimization. A predicted worst-case cost is then used to enable performance-oriented exploration. The proposed approach guarantees robust constraint satisfaction and recursive feasibility. It is shown that method can be implemented using homothetic tube and flexible tube parameterizations of state tubes, and a simulation study demonstrates performance improvement over state-of-the-art controllers.
