集成结构、信息架构和控制设计：张拉整体系统的应用
Integrating Structure, Information Architecture and Control Design: Application to Tensegrity Systems
摘要：
提出了一种新的结构设计参数、作动器和传感器精度以及控制器参数联合优化的统一方法。联合优化问题是作为一个协方差控制问题，其中的可行性是通过约束的输出以及控制信号的协方差。将该方法应用于张拉整体系统的优化设计，对初始预应力参数、传感器和执行器精度以及控制律进行了联合优化。张拉整体系统动力学模型线性化的平衡点用于系统设计，其中最小值是由约束投影确保。假设反馈回路具有一个全阶动态补偿器，其特征矩阵被选为优化变量。这个非凸系统设计问题的次优解是通过使用凸化势函数迭代近似凸问题，使收敛到一个稳定点。结果表明，对于线性动力系统，近似的联合优化问题，可以制定使用线性矩阵不等式（LMI）。
英文摘要：
A novel unified approach to jointly optimize structural design parameters, actuator and sensor precision and controller parameters is presented in this paper. The joint optimization problem is posed as a covariance control problem, where feasibility is achieved by bounding the covariance of the output as well as that of the control signals. The formulation is used to design a tensegrity system, where the initial prestress parameters, sensor and actuator precisions, and the control law are jointly optimized. Tensegrity system dynamics models linearized about an equilibrium point are used for system design, where minimality is ensured by constraint projection. The feedback loop is assumed to have a full-order dynamic compensator with its characteristic matrices chosen as optimization variables. The suboptimal solution of this non-convex system design problem is found by iterating over an approximated convex problem through the use of a convexifying potential function that enables the convergence to a stationary point. It is shown that for a linear dynamical system, the approximated joint optimization problem can be formulated using Linear Matrix Inequalities (LMIs).
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