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Self-Tuning of Adaptive Backstepping Control for Reference Tracking

机译：用于参考跟踪的自适应BackStepping控制的自调整

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This paper presents a nonlinear control approach based on backstepping techniques for a high-speed linear axis driven by pneumatic artificial muscles (PAMs). Its guided carriage is actuated by a nonlinear drive system consisting of two pulley tackles with PAMs mounted at both sides. This allows for an increased workspace as well as higher carriage velocities as compared to a direct actuation. The proposed control scheme has a cascaded structure, where backstepping control concepts are used for a fast inner pressure control loop as well as an outer position control. Hysteresis of the PAMs is not modelled directly but counteracted by an additional adaptive parameter in the outer control loop. The main contribution of this paper is the investigation of a self-tuning algorithm that optimises the controlled system behaviour. Based on several criteria, the gradient of an evaluation cost function (ECF) w.r.t. the control design parameters is approximated and used for an optimisation. Two different variants of the self-tuning adaptive backstepping control are compared with each other using realistic simulations of a given test rig. The obtained results show an excellent closed-loop performance after tuning – compared with the initial design.
机译：此提出了一种基于反推技术线性轴通过气动人工肌肉（PAM中）驱动的高速非线性控制方法。其导向滑块是由包括两个皮带轮铲球用的PAMs安装在两侧上的非线性驱动系统致动。这允许增加的工作空间，以及更高托架速度相比的直接致动的。所提出的控制方案具有级联结构，其中反推控制概念被用于快速内压力控制回路，以及一个外位置控制。所述的PAMs的迟滞不直接建模，但通过在外部控制回路的附加自适应参数抵消。本文的主要贡献是优化控制系统行为的自我调整算法的研究。基于几个标准，评估成本函数的梯度（ECF）w.r.t.控制设计参数被近似，并用于优化。自调谐的自适应反演控制的两个不同的变体彼此使用给定试验台的逼真的模拟比较。将所得到的结果表明调谐后优异的闭环性能 - 与初始设计相比。

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