ABSTRACT
This paper provides a novel approach to jointly optimize structure parameters, information architecture (actuator/sensor precision) and control law to get the required system performance. The tensegrity paradigm is used to integrate these different yet interdependent fields. A linearized tensegrity model as an affine function of initial prestress and force density as the control input is developed. The optimal initial prestress in the strings; the assumed free structure parameter, is solved to satisfy performance and control energy upper bound. The precision of the sensors to measure the position and velocity of the nodes and the precision of actuators required to control the tension in the strings is also provided by the formulation. The complete problem is set 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 problem is formulated in the Linear Matrix Inequality (LMI) framework, and the feedback loop is assumed to have a full-order dynamic compensator with its characteristic matrices chosen as optimization variables. A sub-optimal solution of this non-convex system design problem is found by iterating over an approximated convex problem. The approximate problem is created using a convexifying potential function. This system-level optimization approach to design and control the tensegrity structures also provides the control law for the system.
