Control Of Time-delay Nonlinear Systems Research Articles

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

Adaptive Prescribed-Time Control of Time-Delay Nonlinear Systems via a Double Time-Varying Gain Approach.

This article studies the global prescribed-time stabilization problem for a class of time-delay nonlinear systems with uncertain parameters. First, we design two time-varying gains with special properties, in which one is introduced into virtual controllers to achieve prescribed-time convergence and the other one is used to construct the Lyapunov-Krasovskii (L-K) functional and Lyapunov function to handle the nonlinear time-delay term and unknown parameters, respectively. Then, by utilizing double time-varying gains and the scaling-free backstepping design approach, a dynamic state feedback controller is constructed, which guarantees that all state variables reach zero within a prescribed time, and the prescribed time can be specified in advance. Then, based on new functionals and regular differential inequality, we figure out the explicit expression for the upper bound of all variables, which plays an important role in proving the boundedness of all system variables. Final, a simulation example is given to demonstrate the effectiveness of the proposed method.

Adaptive Fixed-Time Event-Triggered Fuzzy Control for Time-Delay Nonlinear Systems With Disturbances and Quantization

This work investigates the adaptive fixed-time disturbance rejection control issue for a class of time-delay nonlinear systems subject to event-triggered and quantized input signals. First, a disturbance observer is proposed to promote the controller design. Compared with the related disturbance observer design, the observer designed in this paper can be used to construct the fixed-time control scheme. Then, combined with the backstepping technique and fuzzy logic systems (FLSs), an adaptive fuzzy event-triggered and quantized fixed-time control scheme is designed. Moreover, to deal with the unknown time delays, the Lyapunov-Krasovskii functional method is utilized to achieve the system stability. The proposed control algorithm reduces the transmission burden of data channel with a new combined event-based sampling and quantization, and improves the robustness of the time-delay nonlinear system. Finally, a numerical example and a practical example are given to validate the feasibility of the control scheme.

Hybrid evolutionary robust optimization-based optimal control for time-delay nonlinear systems

Optimal controls receive much attention owing to their remarkable performance for nonlinear systems. However, unknown time-delay disturbances in the optimal control process make it difficult to find high-quality optimal set points. To address this problem, a hybrid evolutionary robust optimization-based optimal control (HERO-OC) method is proposed to reduce the negative effect of time-delay disturbances and enhance the performance of optimal set points. First, a data-driven time-delay disturbance observer (DTDO), based on fuzzy neural networks, is designed to describe the time-delay disturbances of optimal objectives. Then, the expressions and intervals of time-delay disturbances can be estimated to improve the accuracy of optimal objectives. Second, a hybrid evolutionary robust optimization (HERO) algorithm, which combines an expectation robust optimization strategy with a min–max evolutionary robust optimization strategy, is proposed to solve optimal set points. Then, the average robustness and conservative of robustness optimal set points can be improved. Third, an adaptive time-delay controller using Lyapunov–Krasovskii functionals is proposed to track optimal set points. Then, control accuracy is improved while ensuring control stability. Finally, the superior performance of HERO-OC is compared with some novel optimal control methods in a second-order nonlinear system and a wastewater treatment process.

Observer-based event-triggered adaptive neural control for time-delay nonlinear systems with input saturation and external disturbances

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.

Robust output feedback control of time-delay nonlinear systems with dead-zone input and application to chemical reactor system

Robust output feedback control of time-delay nonlinear systems with dead-zone input and application to chemical reactor system

Asymptotic tracking control for time-delay nonlinear systems with parametric uncertainties and full state constraints

This article concentrates on an adaptive backstepping control design of time-delay strict-feedback uncertain nonlinear systems subject to full state constraints. The tan-type barrier Lyapunov functions (tBLFs) and Lyapunov–Krasovskii function are united together, which successfully get over the difficulties of system design in which the first function is involved to ensure full state constraints satisfaction and the second is established to eliminate the effect of delayed states. By employing a new control scheme, asymptotic tracking performance is arrived, and all the states remain in the desirable regions for all the system running time. Meanwhile, the boundedness of all signals of the closed-loop system is guaranteed. The performance of the control scheme is illustrated through a class of single degree of freedom (1-DOF) time-delay electrostatic microactuator systems.

High-gain-predictor-based output feedback control for time-delay nonlinear systems

This paper designs a high-gain predictor for output feedback control of nonlinear systems in the presence of input, output, and state delays. The high-gain predictor realizes the states appearing in the output feedback control in terms of predictive state, delayed state, and current state. The system includes internal and external dynamics, and the closed-loop system under state feedback is required to be asymptotically stable and locally exponentially stable. Positively invariant sets are found to verify boundedness, exponential stability, and performance recovery. In the simulation, a saturated sliding mode control is applied to demonstrate the performance recovery of the closed-loop system, and the fact that the high-gain-predictor parameter has a lower bound related to time delays.

Adaptive control for time-delay non-linear systems with non-symmetric input non-linearity

This paper proposes an adaptive control strategy for stabilisation of a class of time-delay systems with both non-linear delayed perturbations and non-symmetric dead-zone and saturating input. The non-linear delayed perturbations are bounded by unrestrained non-linear functions. Based on adaptive and backstepping techniques, the memoryless controller is proposed without knowing the bounds of perturbations, which can guarantee that the closed-loop system state globally converges to zero. Moreover, it removes the assumptions imposed previously that the characteristic parameters are assumed to be known in advance. The results are proved by Lyapunov theorem. Finally, an example is illustrated to show the effectiveness of the proposed control scheme.

The use of a modified sliding-mode controller with time-delay control for unknown systems with uncertain disturbances

A modified sliding-mode controller (SMC) with time-delay control for non-linear systems with disturbance is presented. Unlike a conventional SMC, the proposed approach does not require the identification of system parameters or the estimation of the bounds of disturbances. A novel sliding surface is designed in the modified SMC. The proposed approach provides an easy design method to maintain the convergence of errors by design requirement and uses the lower switching gain to maintain robustness which is in contrast to using a conventional SMC. Simulation results demonstrate that the proposed method is better than a conventional SMC in controlling a non-linear system with disturbances.