Search

This article proposes a tracking control strategy based on fixed‐time for uncertain nonlinear systems with prescribed performance and actuator faults. Fuzzy logic systems are used to model unknown functions with uncertainties or fuzzy parameter features. The improvement of the conventional backstepping method through the introduction of command filtering technology has effectively addressed the challenge of a sharp increase in computational complexity during controller design. Additionally, a mechanism for error compensation has been established to mitigate the potential impact of errors that may arise during the filtering process on the system. Then, a new fixed‐time performance function is introduced into the adaptive backstepping method to ensure that the tracking signal with output error converges to an arbitrarily small neighborhood within a fixed time. Additionally, in order to enhance the tracking performance of the control method, the controller algorithm incorporates fault‐tolerant control based on the fixed‐time performance function. Finally, a numerical simulation of a power system with a static reactive power compensation device is presented, and demonstrate the effectiveness and feasibility of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

In this article, an event-triggered finite-time neural control strategy is proposed for nonlinear power systems with unknown disturbances and static var compensator (SVC). We first transform the power system with SVC into a three-dimensional uncertain nonlinear system and then extend it to an n -dimensional uncertain nonlinear system. The disturbance observer is established to estimate external disturbances and the unknown nonlinear terms are approximated by the radial basis function neural networks. Moreover, to avoid the complexity explosion problem in the traditional backstepping method, the command filtering technique is adopted, and the error caused by the command filters is compensated. The adaptive event-triggered finite-time controller ensures that all signals are bounded in finite time and excludes Zeno phenomena. In the end, the simulation for the two-area interconnected power system with SVC is presented to verify the availability and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

In this article, the issue of adaptive event-triggered tracking control is investigated for time-delay nonlinear systems with input saturation and external disturbances. In the whole process of control design, the radial basis function neural networks are utilized to approximate uncertain nonlinearities. To estimate the unknown states, a neural network-based observer is constructed. Pade approximation method is adopted to eliminate the effect of input delay. A smooth non-affine function is introduced to replace input saturation, and an auxiliary variable is employed to obtain the actual control input. An event-triggered strategy is designed to reduce the utilization of communication and computation resources. Moreover, the command filtering technique is applied to handle the issue of "explosion of complexity" in the conventional backstepping method. The designed controller can assure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Therefore, the proposed event-triggered neural control scheme can not only save network resources, but also improve the robustness of the system by dealing with input constraints and external disturbances. Finally, two simulation examples are given to verify the availability and feasibility of the designed controller. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on the issue of the adaptive fuzzy fault‐tolerant control for a type of nonlinear system with input delay and disturbances. Fuzzy logic systems (FLSs) are used to estimate the unknown nonlinear quantities of the system. The Pade approximation is applied to counteract the negative effects of input delay on the system. The prescribed performance control based on error transformation helps to guarantee the transient performance of system errors. A fuzzy state observer is established to estimate the unmeasurable states of the system. Then, in presence of disturbances and actuator faults, a finite‐time control scheme is designed using the Lyapunov function and the backstepping technique. Based on Lyapunov stability, it is proved that the tracking error can converge to a specified range in a finite time, and all signals in the system are bounded in the controller design. In the end, the simulations of a second‐order system and a multi‐area interconnected power system certify the feasibility and effectiveness of the control strategy. [ABSTRACT FROM AUTHOR]

For time-varying full state-constrained nonlinear systems with unknown input delay, the finite-time command filtered tracking control issue is considered in this brief. The Barrier Lyapunov functions (BLFs) are employed to ensure that all states in the system are kept within the time-varying constraints. Then, a novel finite-time compensation signal is introduced to eliminate the impacts of the unknown input delay. Combining the backstepping approach and the finite-time command filtering technology, the designed controller can guarantee the convergence of the tracking error at the origin and the boundedness of all closed-loop signals, and reduce the complexity of the controller design. In the end, a practical instance is simulated to verify the availability and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

In this article, the problem of adaptive finite-time control is studied for a category of nonstrict-feedback nonlinear time-delay systems with input saturation and full state constraints. The fuzzy logic systems are applied to model the unknown nonlinear terms in the systems. Then, a novel tan-type barrier Lyapunov function is adopted to overcome the problem of full state constraints. By utilizing the finite-time control theory and the backstepping technique, a finite-time fuzzy adaptive controller is designed. The controller can guarantee that the tracking error is adjusted around zero with a small neighborhood in a finite time and all the signals in the closed-loop system are bounded. Finally, two simulation examples are included to verify the validity and feasibility of the control scheme. [ABSTRACT FROM AUTHOR]

To ensure the stability of nonlinear power systems with actuator faults and time delays, this study aims to design an adaptive fuzzy finite-time control scheme. To deal with this control issue, firstly, we propose an adaptive fault-tolerant finite-time controller using backstepping technique. To aid the controller design, fuzzy logic systems are applied to approximate the uncertain nonlinear terms without the prior information. Then, it is proved that the designed controller can ensure the stability in a finite time for the nonlinear power systems with actuator faults and time delays using Lyapunov–Krasovskii method. Finally, numerical simulations of a 4-machine power system with Thyristor Controlled Series Compensation (TCSC) illustrate the applicability of the proposed control methodology. • A novel fuzzy backstepping-based control scheme is proposed for the nonlinear power systems. • The realization of finite-time stability greatly saves the stability time of power systems, and improves operational efficiency. • The robustness of the nonlinear power systems with time delays and actuator faults is improved with the fault-tolerant control scheme. [ABSTRACT FROM AUTHOR]

The adaptive finite‐time event‐triggered quantized control for the nonlinear systems considering uncertain parameters and external disturbances is investigated in this article. First, for the parametric nonlinear systems with external disturbances, an adaptive finite‐time event‐triggered control scheme with input quantization is proposed. The designed controller can ensure the semiglobal finite‐time stability of the closed‐loop system. Then, to deal with the global finite‐time control problem for the parametric nonlinear systems, a novel adaptive quantized event‐triggered control scheme is constructed. Finally, two simulation examples are utilized to illustrate the effectiveness of the adaptive event‐triggered control schemes. [ABSTRACT FROM AUTHOR]

This brief studies the control problem for nonlinear systems with uncertain actuator failures and input quantization. First, a hysteretic quantizer is applied to reduce chattering in the quantized signals. Then, using the backstepping technique, a finite-time fault-tolerant controller is designed. In addition, the control input is quantized by the hysteretic quantizer. It is proved that the global finite-time stability can be ensured for the nonlinear systems with uncertain actuator failures and quantized input signals. Finally, the simulation example of the hydraulic system is presented to verify the established control method. [ABSTRACT FROM AUTHOR]

In modern control theory, it is more applicable for digital computers using a sampled-data controller than a continuous-time controller. Meanwhile, input saturation and disturbance inevitably exist in control systems. Thus, how to propose an applicable sampled-data controller for nonlinear systems considering input saturation together with external disturbances is essential for applications. To deal with this control problem, a novel auxiliary control signal is designed in this paper. Then, by using Lyapunov method, the control design process is simplified compared with the traditional backstepping technique, and only one Lyapunov function is needed. In addition, the state and disturbance observers are proposed with the new auxiliary control signal to track the unavailable states and external disturbances. Finally, we propose a novel controller reflecting the sampled-data output-feedback for the nonlinear systems to ensure the system stability. The effectiveness of proposed control method in this paper is confirmed through two sets of numerical simulation results. [ABSTRACT FROM AUTHOR]

This paper aims at the fault-tolerant adaptive control for the nonlinearly parameterized systems with mismatched disturbances. A novel adaptive control scheme is developed in this paper by adding a power integrator technique. The mismatched disturbances are estimated by a designed disturbance observer. A new fault-tolerant control method is proposed to deal with the uncertain actuator faults including actuator stuck. The proposed adaptive controller ensures that the closed-loop system is input-to-state stable. Simulation results for a robotic arm system are given to present the effectiveness of the developed control technique. [ABSTRACT FROM AUTHOR]

In this paper, a novel composite adaptive fuzzy control (AFC) based on the command filtered backstepping and event-triggered mechanism is proposed for nonstrict-feedback nonlinear systems with input saturation and time-varying full-state constraints. A fuzzy observer is designed to estimate the unmeasured states. Simultaneously, by introducing a serial-parallel estimation model, a fuzzy control tactic with the composite adaptive law of parameters is established which greatly increases the precision of unknown term estimation. In addition, the command filtering technique is employed to solve the issue of "explosion of complexity" and compensate for the errors caused by the command filters. The event-triggered mechanism is utilized to effectively decrease the data redundancy. By using the time-varying barrier Lyapunov functions (BLFs), all the states can remain within a prescribed time-varying interval. The designed controller can guarantee the convergence of the tracking error at the origin and the boundedness of all closed-loop signals. Finally, two simulation examples are carried out to validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The adaptive finite-time anti-disturbance fuzzy control method for n -dimensional uncertain nonlinear systems with input delay is proposed in this paper. For unknown nonlinear terms of the controlled system, the fuzzy logic systems (FLSs) are utilized to approximate them. To further improve the robustness of the controlled system, the disturbance observer is established to estimate external disturbances, facilitating the designed controller to compensate for the influence of external disturbances. Moreover, the Pade approximation method is used to transform the time-delay system model, which is convenient for controller design. With the aid of the finite-time command filtered backstepping technique, the adaptive finite-time disturbance rejection controller with low computational complexity is designed, which can compensate for the errors caused by the filters and assure that system state variables are stable and bounded in a finite time. In the end, the simulation for the single-machine infinite bus (SMIB) system with static var compensator (SVC) is presented to illustrate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

In this article, a fuzzy adaptive command filtered event-triggered control issue is considered for a category of nonstrict-feedback nonlinear systems under the conditions of asymmetric state constraints and time-varying input delay. Firstly, the nonlinear state constrained system is transformed into a new system without state constraints by utilizing nonlinear mappings, which achieves state constraints while removing the feasibility conditions of virtual control signals. Secondly, unknown nonlinear terms in the novel system are approached by using the fuzzy logic systems, a state observer is established to estimate the unmeasurable states in the system, and an auxiliary system is constructed to make up for the influence of time-varying input delay. In addition, the command filtered technology is introduced to overcome the complexity explosion problem in the conventional backstepping design process. It is shown that the fuzzy adaptive event-triggered control scheme can not only ensure the convergence of the tracking error at the origin and the boundedness of all closed-loop signals, but also lighten the communication burden from the controller to the actuator. Finally, a numerical example and an underwater vehicle system are simulated to verify the availability and feasibility of the developed approach. [ABSTRACT FROM AUTHOR]

• Different with the relevant literature, the nonlinear systems in the existence of computation burden while sustaining dead-zone constraints is considered in this paper. An adaptive controller and an auxiliary system are cooperatively constructed to compensate for the mismatch between the controller signal and the actuator signal and offset the effect of dead-zone nonlinear function. Integrated with the backstepping method, an adaptive compensation control scheme is developed. • By utilizing the DSC technique combined with the ETC algorithm, the system's operating rate can be effectively promoted and transmission resources can be greatly saved. Accordingly, the control property of the system can be well enhanced. Moreover, the collaborative devise of the adaptive fuzzy controller and the ETC algorithm eliminates the input-to-state stability hypothesis in the existing literature. • The BLF candidates proposed in this article can make the state variables maintain within the prescribed ranges, which is aligned with the requirements of the actual engineering. Furthermore, a variable separation technology is adopted to handle the algebraic loop issue generated by nonstrict-feedback nonlinear systems. Compared with the existing literature, by employing the characteristics of the fuzzy membership function in the FLSs, the construction procedure for the nonstrict-feedback system is simplified. Therefore, the difficulty coefficient of establishing the control algorithm is reduced. In this paper, a novel adaptive fuzzy dynamic surface control (DSC) via the event-triggered mechanism is developed for nonstrict-feedback nonlinear state constrained systems preceded by actuator dead-zone. The utilization of the dynamic surface technique avoids the issue of repeated differentiation of virtual control law and eliminates the drawback of the explosion of complexity with the backstepping technique. By utilizing the universal approximation property of fuzzy logic systems (FLSs), the unknown function is approximated successfully. By combining the DSC and event-triggered control (ETC) scheme, communication and computation strain are alleviated contemporaneously. An adaptive controller and an auxiliary system are cooperatively constructed to offset the effect of dead-zone nonlinear function. By employing the barrier Lyapunov functions (BLFs), all the states can remain within a prescribed interval. The tracking error can be restricted at the origin and all signals of closed-loop systems can be kept within the boundaries by the designed parameter adaptive laws and event-triggered controller. Finally, a numerical simulation result and a practical simulation result of the pendulum are proposed to guarantee the effectiveness of the presented control theory. [ABSTRACT FROM AUTHOR]

In addressing the adaptive neural backstepping control for multiple-input and multiple-output nonlinear systems in pure-feedback form with time-delay and input quantisation, we construct a high-gain state observer and an output-feedback adaptive control scheme using backstepping method, with neural networks to estimate the uncertain nonlinear functions. Then, we propose an output feedback neural controller that ensures all the state trajectories in the time-delay quantised nonlinear systems are ultimately bounded, with the control signal being quantised by either a hysteretic quantiser or a logarithmic quantiser. An illustrative example is presented to show the applicability of the new control method developed. [ABSTRACT FROM AUTHOR]

This paper proposes a new adaptive controller for a class of uncertain nonlinear systems with a quantized signal. Fuzzy logic systems are utilized to approximate nonlinear terms without imposing prior matching conditions required. A hysteretic type of quantizer is incorporated to reduce chattering. A new adaptive backstepping controller is designed to guarantee that the underlying uncertain nonlinear system is semiglobally uniformly ultimately bounded. Two numerical examples are presented to demonstrate the effectiveness and potential of the proposed techniques. [ABSTRACT FROM PUBLISHER]

The problem of adaptive control is studied for a class of nonlinearly parameterised systems with quantised input signal and unknown control directions. The homogeneous domination approach and the Nussbaum-type gain method are applied to design an adaptive state-feedback controller. A hysteretic type of quantiser is incorporated to reduce actuator chattering. The proposed controller can ensure that all signals of the nonlinear system are globally bounded, and that the system state asymptotically converges to zero. Two numerical examples are presented to demonstrate the effectiveness and potential of the proposed techniques. [ABSTRACT FROM AUTHOR]

This paper considers the sampled-data fuzzy control of nonlinear systems in strict feedback form with disturbances and random missing input data. We propose a novel method in which a state observer and a disturbance observer are combined to construct a sampled-data fuzzy output feedback controller. The stochastic variables with a Bernoulli distributed sequence are used to model missing input data. Fuzzy logic systems are applied to approximate nonlinearities without requiring prior knowledge. The relation between observer gain and sampling period is established. The output feedback controller designed guarantees that the nonlinear system is globally stable. A simulation example of four degrees of freedom robotic arm is used to demonstrate the effectiveness and applicability of the proposed control scheme. [ABSTRACT FROM AUTHOR]

• Compared with the similar non-finite time control methods in the relevant literature, the finite-time adaptive controller designed in this paper has the merits that it can and enhance the transient performance of the entire control system and avoid the ISS assumption. • The nonlinear parametric system proposed in this paper is more general than the relevant literature, since the unknown external disturbances, uncertain system parameters, unknown control gain and unpredictable actuator faults are considered in this work simultaneously. The parameter updated laws are designed to estimate the unknown control gain and uncertain system parameters. Moreover, the FLSs are introduced to approximate the uncertain bias fault, which can compensate for the faults in a wider range, with better accuracy. • In the design of the ETC scheme, compared with the existing literature, the intermediate variable is introduced to embed the ETC signal into the actuator fault model and the adaptive control laws to further effectively eliminate the redundant items and avoid the tedious. In this article, the issue of adaptive finite-time event-triggered tracking control is investigated for nonlinearly parameterized systems with unknown faults and unknown control gain. By establishing the proper parameter adaptive laws with the intermediate variable, the problem of system instability caused by the uncertainty of the parametric system and the unknown faults of the actuator can be effectively handled. Simultaneously, the unknown nonlinear term denotes the bias fault is approximated by the fuzzy logic systems (FLSs). Accordingly, an improved event-triggered controller with a varying threshold strategy is developed to rule out the Zeno phenomenon and demonstrate that all the signals in the closed-loop system are semi-globally practically finite-time stable (SGPFS). Finally, a simulation result of the manipulator system is carried out to validate the proposed control scheme. [ABSTRACT FROM AUTHOR]