基于模糊补偿的塔式起重机自适应模糊滑模控制

塔式起重机在工作时，负载会产生摆动，且系统具有欠驱动性、非线性和强耦合性的特征，定位与消摆控制难度大。大多数现有控制方法未考虑系统的摩擦项或者考虑系统摩擦项时由固定公式计算得出，而工程实际应用中摩擦项易受到工作环境的影响，引起控制效果的降低。为解决上述问题，本文提出了一种基于模糊补偿的自适应模糊滑模控制器。首先，通过对原有的系统动力学模型进行改造，构造出新的动力学模型，解决了系统由于欠驱动特性导致控制律难以设计的问题。随后采用模糊逼近的方式对系统的摩擦项进行逼近，解决了不确定性的工作环境对摩擦项的影响。其次在此基础上与滑模控制理论相结合设计控制器，并经严格的稳定性分析，证明了系统是渐进稳定的。最后，经仿真和实验结果验证了所提方法的有效性。

Adaptive Fuzzy Sliding Mode Control of Tower Crane Based on Fuzzy Compensation

During tower crane operation, the load induces oscillations, and the system displays traits like underdrive, nonlinearity, and strong coupling. Controlling the positioning and eliminating oscillations is challenging. Most existing control methods either neglect system''s friction term or employ a static formula for its calculation. However, the friction term is highly influenced by the working environment in practical engineering applications, leading to a reduction in control effectiveness. To solve these issues, this paper proposes an adaptive fuzzy sliding mode controller based on fuzzy compensation. Firstly, by adjusting the original system dynamics model, a new model was formulated to address the challenge of designing a control law for the underdriven system. Subsequently, the friction term of the system was approximated using fuzzy approximation, mitigating the impact of the uncertain operating environment on this term. Secondly, the controller was designed on this basis in combination with sliding mode control theory, and the system was proved to be asymptotically stable by rigorous stability analysis. Finally, the proposed method''s effectiveness is validated through simulation and experimental results.