Observer-based Intelligent Control Strategy Research For A Nonlinear Strict Feedback Systems

With the continuous advancement of world science and technology,China's modern industrial production system is also evolving towards high complexity,high information technology,and high intelligence.The more complex the system is,the more it will be interfered by internal and external factors and will malfunction.Therefore,the resulting loss is difficult to calculate.Among these failures,the dead zone phenomenon is the most common.How to deal with the impact of the dead zone on the system and reduce the system maintenance cost is an urgent need in the actual industrial site.In the actual project site,if you want to maintain the healthy operation of the system and reduce the downtime for maintenance,you need to obtain a large amount of real-time system status data.In some industrial scenarios,the cost of collecting key status data of some systems is high,or even difficult to collect..These unmeasured system states need to be estimated by observers.In addition,due to the high complexity of modern industrial systems and the high coupling of internal states,the system itself is subject to internal or external constraints.The requirements of industrial systems for estimation of dead zones,state constraints,and system unmeasurable states have led the author to combine intelligent control methods and anti-stepping methods based on the research of other scholars,each based on his own strengths,and carry out comparisons with the above-mentioned problems.The main content of this article consists of the following three parts:1.For a class of strictly feedback nonlinear systems with limited output and bounded disturbances,a controller design method based on Backstepping and Lyapunov stability criterion is proposed.The RBF neural network in the intelligent control strategy is used to approximate and estimate the unknown nonlinear term of the controlled system,and the logarithmic obstacle Lyapunov function is used to constrain the output of the system.Afterwards,it is proved that the designed controller can ensure that all signals in the entire closed-loop system are bounded,and the output of the system can also track the reference signal well.2.Aiming at the tracking control problem of a class of strict feedback nonlinear systems with unmeasured states,dead zone characteristics and limited output.With the help of the fuzzy logic system in the intelligent control strategy,a fuzzy observer for the unmeasured state is constructed,the median value theorem is used to deal with the characteristics of the nonlinear dead zone,and finally the tangent obstacle Lyapunov function is used to constrain the output of the system.The designed controller and observer can ensure that all signals of the closed-loop system are bounded and the accuracy of the observed state,and the output of the system can also track the reference signal well.3.Aiming at the tracking control problem of a kind of rigid manipulator system.The fuzzy observer and the traditional observer are used to simultaneously estimate the unmeasurable state of the system,and the logarithmic obstacle Lyapunov function and the tangent obstacle Lyapunov function are used to constrain the output of the system.Under the condition that the designed controller can ensure that the states in the closed-loop system are bounded,compare the effects of using different observers and obstacle Lyapunov functions on the tracking performance of the system output,as well as the differences in the difficulty of constructing observers and the observation accuracy.