Unknown Desired Trajectory Tracking Control Of Uncertain Perturbed Nonlinear Systems

Most control problems in practice can be formulated as trajectory tracking,for this reason,trajectory tracking control problem has attracted much attention from the control community and has thus been extensively studied.However,the vast majority of the existing tracking control methods are based on the assumption that the desired target trajectory is known a priori.It should be noted that,in many practical applications,the desired trajectory to be tracked might not be available precisely.It is therefore of theoretical and practical importance to investigate the tracking control problem where the desired trajectory to be tracked is unavailable for control design.Considering that there are uncertainties and nonlinearities in most practical systems,the primary objective of this work is to investigate the unknown desired trajectory tracking control problem of nonlinear systems in the presence of multiple other uncertainties.Firstly,the unknown target tracking control problem of uncertain perturbed strict-feedback systems is investigated.Linear combination of basis functions is used to reconstruct the unknown desired trajectory.By estimating the unknown parameters of the linear combination,the unknown desired trajectory is estimated and used for controller design.By introducing boundary layer errors and first-order filters,backstepping and dynamic surface technique based controller is designed to achieve close target tracking and maintain system stability.Simulation is conducted to validate the effectiveness of the proposed control scheme.Secondly,the problem of unknown desired trajectory tracking control for uncertain perturbed nonlinear systems in pure-feedback form with dead-zone is investigated.The mean value theorem,implicit function theorem and RBF neural networks are utilized to deal with the uncertainties of the system.The unknown desired trajectory is reconstructed via the linear combination of basis functions.Improved backstepping algorithm is used to design the adaptive control laws.It is proved that the proposed control scheme guarantees satisfactory tracking performance,with all the close-loop signals being bounded.Finally,numerical simulation results verify the feasibility of the developed method.Lastly,the unknown target tracking control problem of uncertain perturbed pure-feedback systems with unknown time delays and undetectable actuation failures is investigated.Lyapunov Krasovskii functions are introduced to cope with the unknown time delays.Through dynamic surface technique,robust adaptive fault-tolerant control scheme is developed to ensure close tracking of the unknown target,while guaranteeing the stability of the system and the boundedness of all the closed-loop signals.In the end,the effectiveness and feasibility of the proposed control scheme is confirmed by numerical simulations.In this part,the investigated systems consider more practical factors,which not only makes the systems more similar to the actual systems but also makes it more challenging to design the control algorithms.