This article presents an optimal control strategy (OCS) for semiactive vehicle suspensions with road profile sensors. The suspension is modeled as a quarter‐car model with a magnetorheological (MR) damper. The OCS main objective is to minimize the fourth‐power acceleration of the sprung mass. In addition, three pointwise constraints of the model are taken into account when the optimal control problem is solved: suspension travel limits (upper and lower) and tyre vertical force. In order to deal with a large number of constraints, we implement the gradient optimization method based on the method of moving asymptotes routine, which shows very good performance reaching optimal controls while satisfying the constrains. The solution has been compared with two passive MR damper configurations (low and high damping) as well as Skyhook and Balance control strategies for three different road inputs. Results show that OCS fulfills the constraints and reduces the sprung mass acceleration peak and the root‐mean‐quad acceleration up to 59%, in comparison to passive strategies.

中文翻译：

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半主动车辆悬架的按点约束最优控制

本文提出了一种具有道路轮廓传感器的半主动车辆悬架的最优控制策略（OCS）。悬架建模为带有磁流变（MR）阻尼器的四分之一车模型。OCS的主要目标是最大程度地减小簧载质量的四次方加速度。此外，在解决最佳控制问题时，还要考虑模型的三个点约束：悬架行程极限（上下）和轮胎垂直力。为了处理大量的约束，我们基于移动渐近例行程序的方法实现了梯度优化方法，该方法在满足约束的同时达到了最优控制的效果非常好。该解决方案已与两种被动MR阻尼器配置（低阻尼和高阻尼）以及针对三种不同道路输入的Skyhook和Balance控制策略进行了比较。结果表明，OCS满足了约束条件，并减小了簧上质量加速度峰值和均方根加速度，直至与被动策略相比，占59 ％。