Research On Quantized Control And Fault-Tolerant Control For Uncertain Nonlinear Systems

In recent years,with the sustainable development of science and technology,the computer has been widely used in practice.Due to the wide application of the computer,communication and control technology are developed rapidly,such that the scale of the controlled objects is getting larger and larger,the structure is getting more and more complex,and the control difficulty is getting higher and higher.The traditional control strategy can no longer meet the need of modern production.However,the networked control is different from the traditional control method,it combines the wired or wireless network,intelligent sensor,digital communication technology and other modern technology with the computer networks,and becomes the advanced control technology in the modern control theory.Networked control is widely used in practical engineering subject to its own advantages.However,the networked control systems have a high requirement to the bandwidth and transmission frequency of the communication channels.How to use the limited bandwidth to transmit the signal and ensure the performance of the control system not to be reduced has become an important research topic in networked control.Quantized control is one of the important methods to reduce the frequency of signal transmission and improve the effective utilization of network resources.At the same time,the quantized error has been introduced with the quantization of the control signal,which will affect the performance of the system.Many researchers have widely studied that how to deal with the error caused by the quantization of the signal.However,the existing results are still limited,especially for uncertain nonlinear systems.On the other hand,with the increasing complexity of the modern control system,the reliability and security of the system have been paid more attention during operation.During the actual operation of the system,the components such as actuators or sensors may suffer unexpected failures,which may lead to unstable operation of the system or even catastrophic accidents.How to design an effective fault-tolerant control strategy to tolerate faults has become a hot research topic in the field of control and has very important research significance.In this dissertation,on the basis of the existing results and by using fuzzy logic system or neural network approximation,adaptive technology,backstepping method and other basic methods,the quantized control and fault-tolerant control methods for uncertain nonlinear systems are studied.The main contents are listed as follows:In Chapters 1-2,the research background and development of quantized control and fault-tolerant control are systematically introduced.Also,the preliminary knowledge related to this dissertation are given.In Chapters 3,the problem of adaptive fault-tolerant tracking control for a class of uncertain nonlinear systems in the presence of input quantization and unknown control direction is considered.By choosing a class of particular Nussbaum functions,an adaptive fault-tolerant control scheme is designed to compensate actuator faults and input quantization while the control direction is unknown.Compared with the existing results,the proposed controller can directly compensate for the nonlinear term caused by actuator faults and the nonlinear decomposition on the quantizer without estimating its bound.Furthermore,via Barhalant's Lemma,it is proven that all the signals of the closed-loop system are globally uniformly bounded and the tracking error converges into a prescribed accuracy in prior.Finally,an illustrative example is used for verifying effectiveness of the proposed approach.In Chapters 4,the problem of adaptive fault-tolerant tracking control for strictfeedback nonlinear systems with mismatched external disturbances is investigated.By using the Nussbaum function technique,the difficulty caused by input quantization and infinite number of time-varying actuator faults is handled and a novel fuzzy adaptive control scheme is designed without estimating a lower bound on the quantizer parameter and the time-varying effectiveness factor.Based on the Lyapunov stability theory,it is proven that all the signals in the resulting closed-loop system are bounded and the tracking error satisfies the desired performance all the time.Simulation results are presented to verify the effectiveness of the proposed controller.In Chapters 5,the problem of neural-network-based adaptive fault-tolerant tracking control for a class of uncertain nonlinear time-varying delay systems under output constraints and infinite number of actuator faults is considered.By constructing Lyapunov-Krasovskii functions,introducing a bound estimation approach and using dynamic surface control technique,a novel adaptive fault-tolerant control scheme is designed to compensate actuator faults and unknown time-delay uncertain functions as well as the output constraint is not violated.Compared with the existing results,the proposed controller can be implemented easily.Furthermore,via Lyapunov theory,it is proven that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded.Finally,an illustrative example is used for verifying effectiveness of the proposed approach.In Chapters 6,the problem of adaptive fault-tolerant tracking control for uncertain nonlinear systems subject to input dead-zone and full state constraints is investigated.Firstly,an error transformation approach is introduced to guarantee that all states do not violate their constraint bounds.Then,to avoid the issue of "explosion of complexity" in handling the derivative computation for the virtual control laws and improve the robust control performance,a novel nonlinear filter is proposed together with designing adaptive laws to compensate the bounded layer errors.In addition,the saturation function is employed to handle the difficulty caused by obtaining the explicit bounds for virtual signals at each step.By utilizing fuzzy logic systems to approximate unknown compound nonlinear functions,a novel fault-tolerant control scheme is proposed subject to online estimation technique.Finally,according to Lyapunov stability theory,it is concluded that all signals in the resulting closed-loop system are bounded and the tracking error satisfies the desired performance in presence of input dead-zone and actuator failures.Simulation results verify the effectiveness of the proposed control scheme.In Chapters 7,the author focuses on observer-based fuzzy adaptive fault-tolerant tracking control problem for uncertain nonlinear systems subject to unmeasured states,and unmatched external disturbances.By designing a high gain state observer and a disturbance observer,unmeasured states and unmatched external disturbances are estimated and the robust tracking performance is improved.Moreover,barrier type functions are introduced to the backstepping design procedure to address the problem that all states do not violate their constraint bounds.Finally,a novel fault-tolerant control scheme for output feedback is proposed by combining with projection technique.By designing appropriate Lyapunov functions,it is concluded that all signals of the plant are bounded and the desired tracking error can be regulated to a small neighborhood around the origin.Simulation results show the effectiveness of the designed control scheme.In Chapter 8,the results of the dissertation are summarized and further research topics are pointed out.