A Class Of Nonlinear Systems And Practical Output Of Motor Control

This paper studies the maneuvering control problem. In general, the maneuvering control problem (maneuvering) contains two tasks. The first task is to make the state or output of the system to follow a desired parameterized path; the second task is to satisfy a desired dynamic behavior along the path. The second task is to avoid problems in the tracking process, which can protect the performance of the system. Therefore, the study of the maneuvering control problems has important theoretical value and practical significance.In this paper, the three types of nonlinear systems are studied about the output maneuvering control problems. The article is divided into the following three parts.In the first part, the output maneuvering controller is designed for a class of uncertain nonlinear systems via the backstepping method. The uncertainty in the system not only can mean bounded disturbance, but also be regarded as the uncertainty of the unknown parameters. In the process, we first design the actual control-u, and then give the update law of the speed error. The adaptive controllers can not only guarantee the stability of the system and signal bounded, meanwhile it also makes the path tracking error and the speed tracking error to converge to a certain range.In the second part, the output maneuvering problem is investigated for a class of nonlinear systems with uncertainties and unknown control directions. Based on the Nussbaum function and the backstepping method, an adaptive output maneuvering controller is designed. The controller can guarantee that all the signals of the closed-loop system are uniformly bounded, and then it meets the other control objectives.In the third part, a class of nonlinear systems with unmodeled dynamics is chosen. Based on previous research results, the output maneuvering control problems is studied. The nonlinear system in this chapter, not only owns the uncertainties of the unmodeled dynamics, but also owns nonlinear uncertainties, which increases the complexity and difficulty of the problem. Backstepping approach is applied in the recursive process, and a lemma is cleverly used, which can avoid reconstructing the Lyapunov function of the subsystem when the unmeasured states are dealt with.