摘要
针对一类含有非匹配不确定性的块控型多输入多输出非线性系统,提出一种基于反演技术和RBF神经网络的控制系统设计方案.通过引入一种改进型的Lyapunov函数,避免了控制矩阵未知情况下可能出现的奇异问题.在控制系统设计过程中,充分应用鲁棒自适应控制技术,解决了多输入多输出结构不确定性所带来的设计难题,得到了系统所有状态量将全局指数收敛至原点附近一个邻域的结论.最后的仿真结果表明了设计方案的正确性.
For a class of multi-input multi-output（MIMO） block nonlinear systems with mismatched uncertainties,an adaptive controller design scheme using backstepping and RBF neural networks is proposed.By introducing a modified Lyapunov function,control singularity problem brought by unknown control matrices is avoided.By using of robust adaptive control technique,many difficulties brought by MIMO uncertainties are solved.The conclusion is obtained that all states variables are bounded and will exponentially converge to a neighborhood of the origin globally.Finally,simulation results are given to show the correctness of proposed scheme.
出处
《控制与决策》
EI
CSCD
北大核心
2012年第6期855-860,共6页
Control and Decision
基金
国家自然科学基金项目(61004002)
