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).

中文翻译：

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张力系统的集成结构，信息架构和控制设计

本文提出了一种新的统一方法，用于联合优化结构设计参数，执行器和传感器精度以及控制器参数。联合优化问题作为协方差控制问题提出，其中通过限制输出和控制信号的协方差来实现可行性。该公式用于设计张力系统，在该系统中，共同优化了初始预应力参数，传感器和执行器的精度以及控制律。围绕平衡点线性化的Tensegrity系统动力学模型用于系统设计，其中通过约束投影来确保最小化。假定反馈环路具有一个全阶动态补偿器，其特征矩阵被选作优化变量。该非凸系统设计问题的次优解决方案是通过使用使能收敛到固定点的凸势函数对近似凸问题进行迭代来找到的。结果表明，对于线性动力学系统，可以使用线性矩阵不等式（LMI）来表达近似联合优化问题。