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Design and experiment of the feed cable-suspended structure for the next generation large spherical radio telescope are presented. The optimization design of the telescope structure is performed and the connection between stable cables and twisting stiffness is verified. The inverse kinematic and dynamic model of CPR with non-negligible cable mass is carry out. Furthermore, the inverse dynamic formulation of the mechanical system including servomechanism dynamics is established by using Lagrange’s Equations.

The complete kinematics and dynamics of the cooperative cable parallel manipulators for multiple mobile cranes is studied, which is the foundation for the further research of this new promising and significant engineering equipment. The kinematics of the cooperative three mobile cranes with point-mass is established with elimination method, including both forward and inverse kinematics. Based on Lagrange equation and the kinematics, the complete dynamic model of the CPRMC is derived. A robust iterative learning controller (ILC) of the CPRMC is designed on the basis of the linearization of the dynamics. Numerical simulation is conducted in order to investigate the dynamics and the designed robust ILC of the CPRMC.

To illustrate the advantage of the performance indices, firstly, hybrid-driven based cable-suspended parallel manipulators (HDCPR) is presented, then Kinematics and dynamics of the cable parallel manipulators with and without HDPM are studied based on Lagrange method separately. Finally, some performance indices, such as conditioning index, stiffness index, and payload index are investigated and compared based on above analysis.

The fuzzy plus proportional-integral control (FPPIC) method, which can enhance the control performance for steady state errors, is utilized to control the wind-induced vibration of the trajectory tracking of the feed. Moreover, the simulation and experiment are respectively deployed on the 5-m and 50-m scaled model to test the different dynamic modeling present in former chapter and justify the efficiency of purposed control strategy.

Design model and cooperative localization scheme of the CPRMC are presented, and the improved localization algorithm based on multilateration method is designed. The global path planning of the CPRMC is performed based on the artificial potential field method with the grid method, and the sensor technology is applied to the cooperative obstacle avoidance, and combined with Matlab and LabVIEW, a co-simulation platform is built for cooperative obstacle avoidance analysis. A four-point collaborative leveling method is adopted for automatic leveling control of the platform for the CPRMC.

The dynamic model of the HDCPR is developed on the basis of Lagrange method. Then, an adaptive iterative learning control strategy is designed for the high-precision trajectory tracking. Furthermore, the stability of the controller is proved by means of Lyapunov function. In order to improve the dynamic performance of the HDCPR system, a methodology of simultaneous optimal design of mechanism and control for the HDCPR is presented. The dynamic modeling of the HDCPR is performed based on Newton-Euler method, and the workspace of the manipulator is also analyzed.

The design, dynamic modelling, and workspace of the CPRMC are presented. The design model of the CPRMC is presented. Then, kinematics and dynamics of the CPRMC are performed. Workspace analysis of the CPRMC is provided and illustrative simulation studies highlight its performances. Finally, some concluding remarks are summarized.

The design model of the HDCPR is described. Then, mechanics analysis and error modelling of the HDCPR is described based on the differentiation of kinematic equations. Sensitivity analysis of the HDCPR is provided. Illustrative simulation studies highlight its performances. Finally, conclusions and future studies are summarized.