This work presents a multivariable predictive controller applied on a redundant robotic manipulator with three degrees of freedom. The article focuses on the design of a discrete model‐based predictive controller (DMPC) using the Laguerre function as a control effort weighting method to enhance the solution of Hildreth's quadratic programming and to minimize the trade‐off problem in constrained case. The Laguerre functions are used to simplify and enhance the control horizon effect through parsimonious control trajectory, thus reducing the computational load required to find the optimal control solution. Furthermore, these results can be confirmed by simulations and experimental tests on the manipulator and comparing it to the traditional DMPC approach and the discrete linear quadratic regulator.

中文翻译：

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使用Laguerre函数的机械臂的受限离散模型预测控制

这项工作提出了一种应用于具有三个自由度的冗余机器人操纵器的多变量预测控制器。本文重点介绍使用Laguerre函数作为控制权重加权方法的基于模型的离散预测控制器（DMPC）的设计，以增强Hildreth二次规划的解决方案，并在受限情况下最大程度地减少权衡问题。Laguerre函数用于通过简约控制轨迹简化和增强控制范围效果，从而减少了寻找最佳控制解决方案所需的计算量。此外，这些结果可以通过在机械手上进行的仿真和实验测试得到证实，并将其与传统DMPC方法和离散线性二次调节器进行比较。