In this investigation, a smart collision avoidance control design, which integrates a collision avoidance navigation and a nonlinear optimal control method, is developed for unmanned surface vessels (USVs) under randomly incoming ships and fixed obstacle encounter situations. For achieving collision avoidance navigation, a fuzzy collision risk indicator and a fuzzy collision avoidance acting timing indicator are developed. These two risk indicators can offer effective pre-alarms for making the controlled USVs to perform dodge actions in time when obstacles appear. As to nonlinear optimal control law, it provides a precise trajectory tracking ability for the controlled USVs to follow a collision avoidance trajectory, which is generated via a smart collision avoidance trajectory generator. Finally, a power allocation method is used to transform the desired control law into available actuator outputs to guide the USVs to follow a desired collision avoidance trajectory. From simulation results, the proposed collision avoidance strategy reveals a promising collision avoidance performance and an accurate trajectory tracking ability with respect to fixed objects and randomly moving ships under the effect of environmental ocean disturbances.
A novel nonlinear control law for the purpose of lateral control of a missile is presented in this paper. This approach can be applied to generate lateral control commands for a missile operating in flight regimes where the effectiveness of conventional aerodynamic surfaces is reduced (i.e. high angle of attack). The design objective is to specify one control law that satisfies the H2 performance for the nonlinear attitude tracking design of missiles. In general, it is hard to obtain the closed‐form solutions from this nonlinear attitude tracking problem. Fortunately, because of the adequate choice of state variable transformation, the nonlinear H2 attitude tracking problem of the missile can be reduced to solving one nonlinear time varying Riccati‐like equation. Furthermore, one closed‐form solution to this equation can be obtained in a very simple form for the preceding control design.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.