| With the rapid development of robot technology, robot is widely applied in many fields of remote, unstructured, and hazardous environments such as space and undersea exploration, mining, and construction. Fixed configuration robots have been uniquely designed to perform a specific task in the limited environments. In some situations, using robots with different parameters for a variety of task is possible when the task requirements are specified in advance. However, in many unstructured and less predictable environments, such as a nuclear waste retrieval site, aboard a space station, or a lunar base construction site, it is very difficult or impossible to design a single robotic system that can meet a wide range of task requirements. In these circumstances, it might be advantageous to deploy a reconfigurable and modular robot system which can be reconfigured itself into robots with different parameters which are individually well suited to the diverse task requirements. A reconfigurable modular robotic system consists of various link and joint modules with standardized connecting interfaces that can be easily separated and reassembled into many different configurations according to the changing task and changing environment. Such a robotic system has several advantages over conventional fixed-parameter design. First of all, it is very flexible and adaptable to different tasks requirements and working environments. The standardized design is easy for maintenance, modification, and transportation, and economical for manufacturing. Furthermore, it allows the re-use of the same part for different purposes, and thus reduces the total inventory of modules and the cost of redesign and repair. Scholars in the world have deeply studied the reconfigurable and modular robots, but focus on its automatic generation in kinematics and dynamics, kinematics calibration and distributed control. There are many challenging, just underway and marginal aspects, for example, inverse kinematics solution, uncertainty control, dynamic control, fault detection & diagnosis and tolerant control. These problems still need scholars pay much attention and effort. Hence, it is very necessary and significant to study further on reconfigurable and modular robot.In this paper, the domestic and foreign researching status are analyzed, main research contents of reconfigurable and modular robots are summarized, the kinematics and dynamics function of reconfigurable and modular robot are researched, and as the key points the control schemes indirect and direct adapative fuzzy decentralized control are studied. The important content of this paper are as follows:First, the kinematics function of reconfigurable and modular robot is set up by exponential product method. Base on rigid body Newton-Euler iterative algorithm, a iterative Newton-Euler function of the system is got by iterative of generalized velocity generalized acceleration and inverted iterative of generalized force. The dynamics function of reconfigurable and modular robot is set up.Second, the indirect adaptive fuzzy decentralized control scheme is proposed for the dynamic control for trajectory tracking problem of reconfigurable and modular robots. The dynamics of reconfigurable and modular robots are firstly represented as a set of interconnected subsystems. Based on the sub-system dynamic function of reconfigurable and modular robot we have set up, indirect adaptive fuzzy decentralized controller is designed. Suppose subsystem dynamic model parameters are known, the ideal controller for ith subsystem is designed based on feedback linearization approach. The fuzzy logic systems are employed to approximate to two unknown functions in ideal controller using universal approximation property of fuzzy systems, and subsystem dynamic fuzzy modeling is implemented. The effect of interconnection and fuzzy approximation error are removed by fuzzy logic systems. Adaptive laws are designed to adjust parameters of fuzzy systems. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that stability of the closed-loop system can be guaranteed. Simulation examples are presented to obtain a good tracking performance and demonstrate the effectiveness of the proposed decentralized controller. In this way fuzzy logic systems are employed to approximate to unknown function of plant model to implement fuzzy modeling for nonlinear uncertain systems. The control structure is slightly more complicated.Third, the direct adaptive fuzzy decentralized control scheme is proposed for the sub-system dynamic function of reconfigurable and modular robots. There is no need of fuzzy modeling for nonlinear uncertain systems, fuzzy logic system acts as a controller. For sub-system dynamic function of reconfigurable and modular robot we have set up, suppose subsystem dynamic model parameters are known, the ideal controller for ith subsystem is designed based on feedback linearization approach. The fuzzy logic systems are employed to approximate to ideal controller using universal approximation property of fuzzy systems. The effect of interconnection and fuzzy approximation error are removed by fuzzy logic systems. Adaptive laws are designed to adjust parameters of fuzzy systems. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that stability of the closed-loop system can be guaranteed. Because this method has no needs of fuzzy modeling, and directly approximate to ideal controller. A fuzzy system is less used than the preceding method. The control structure is more simplified than indirect adaptive fuzzy decentralized control scheme. The result of simulation shows that this method not only makes system to obtain a good tracking performance, but also greatly decrease the computing time than indirect adaptive fuzzy decentralized control.At last, all the work is concluded in the summary, and combining what I have learned, prospect for some questions is laid out. |
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