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This article presents an effective method to address the tracking control problem arising in uncertain switched high-order nonlinear system in strict-feedback form. The system under consideration contains unknown functions, which causally make the asymptotic tracking performance difficult to be achieved. By adopting the adding a power integrator approach in the framework of backstepping, a novel tracking controller is developed to guarantee an asymptotic tracking performance in the presence of the approximation error cased by neural networks (NNs) under arbitrary switching. The main contributions lie in: 1) the article for the first time embeds the backstepping technique in designing a kind of discontinuous controller with proportional integral (PI) compensation and 2) with the help of Filippov’s theory, a new defined system described by differential inclusions can be first obtained by taking some transformations, and then a novel nonsmooth Lyapunov function approach along with its upper right Dini derivative technique is applied to complete the construction of the discontinuous controller. Finally, two simulation examples are exhibited to verify the validity of the proposed design techniques. [ABSTRACT FROM AUTHOR]

Summary: In this article, the adaptive tracking control issue is addressed for uncertain switched nonstrict‐feedback nonlinear systems with unknown time‐varying delay and backlash‐like hysteresis under neural networks (NNs) estimation framework. In contrast to most existing results of nonlinear systems with time‐delay, the time‐varying delay we consider depends entirely on the number of switching subsystems. Based on the inherent properties of radial basis function NNs, the nonstrict‐feedback structure is effectively compensated. Meanwhile, with the help of the combination of Razumikhin function method, adaptive backstepping scheme, and dynamic surface control approach, the quadratic common Lyapunov function is established for all subsystems, and then an adaptive common control strategy is developed. For arbitrary switching signals, it is shown that all the signals in the closed‐loop system can be remained bounded and the system output can follow a desired signal under the designed controller. Finally, the validity of the presented strategy is verified via two simulation examples. [ABSTRACT FROM AUTHOR]

In this technical note, we present an adaptive fuzzy hierarchical sliding mode control method to deal with the control problem of under-actuated switched nonlinear systems. For the system under consideration, both the issues of unknown uncertain functions and aperiodically updating input are taken into account, which are of practical importance. A bounded time-varying function is employed to make a linear transformation of the control input, leading to a transformed system that can be applied to the control design. By introducing the so-called hierarchical structure, a top layer hierarchical sliding surface containing all the system states' information is obtained. Furthermore, by carrying out fuzzy logic systems' universal approximation, the problem caused by unknown system uncertainties is tackled. The approximation errors together with the measurement error resulted from the effects of the triggering event are lumped into a function, and its upper bound is estimated on-line. Based on these, the boundedness of all the signals are verified by combining the Lyapunov theory and projection algorithm. To testify the validity of our control scheme, a simulation example is carried out. [ABSTRACT FROM AUTHOR]

This paper concerns the stability analysis for singular systems with time-varying delay and nonlinear perturbations. Two cases of time-varying delay, which is differentiable (Case 1) or not differentiable (Case 2), are considered. The considered nonlinear perturbations includes the norm-bounded uncertainties as a special case. Some delay-dependent stability criteria are derived by using a delay decomposition approach. In the delay decomposition approach, the entire delay interval is divided into multiple sub-intervals for which different energy functions are defined for building new Lyapunov–Krasovskii functional. Some numerical and practical examples are given to show the effectiveness and significant improvement of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper describes a novel development of a lower limber exoskeleton for physical assistance and rehabilitation. The developed exoskeleton is a motorized leg device having a total of 4 DOF with hip, knee, and ankle actuated in the sagittal plane. The exoskeleton applies forces and learns the impedance parameters of both robot and human. An adaptive control scheme by incorporating learning control approaches into the exoskeleton system is developed to help the leg movement on a desired periodic trajectory and handle periodic uncertainties with known periods. The proposed control approach does not require a muscle model and can be proven to yield asymptotic stability for a nonlinear muscle model and an exoskeleton model in the presence of bounded nonlinear disturbances (e.g., spasticity and fatigue). The performance of the controller is demonstrated through closed-loop experiments on human subjects. The experiments illustrate the ability of the exoskeleton to enable the leg shank to track single and multiple period trajectories with different periods and ranges of motion. [ABSTRACT FROM PUBLISHER]

The paper presents a combination modeling procedure and the implementation of a nonlinear predictive control scheme for the optimization of industrial chemical processes. The model structure is first based on a simple step response method. This provides a way to use prior knowledge about the dynamics, which has a general validity, while additional information about the process behavior is derived from measured plant data-model error. This data error driven model framework is applicable for a wide range of chemical operating units under a certain control policy. The same idea is also used to solve the online optimization problem in the predictive controller. The efficiency and effectiveness of the modeling training algorithm and the nonlinear predictive control approach are demonstrated through a coke furnace case study. A good model fitting for the nonlinear plant is obtained by using the new method. A comparison with traditional approaches shows that the new algorithm can considerably reduce modeling error and improve control accuracy. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the problem of absolute stability for a class of time-delay singular systems with sector-bounded nonlinearity. Both delay-independent and delay-dependent criteria are presented and formulated in the form of linear matrix inequalities (LMIs). Neither model transformation nor a bounding technique for cross-terms, nor a slack variable method is involved in obtaining the stability criteria. Numerical examples are given to show the effectiveness and improvements over some existing results. [Copyright &y& Elsevier]

Abstract: This paper describes the application of a linear iterative design of nonlinear predictive functional control for chamber pressure of industrial coke furnace. The control target is to maintain the chamber pressure of a coke furnace within a set range while rejecting the effect of disturbances (mainly the coke removing process and the switch of coke towers).The proposed control is easy to implement, as it selects a simple structure and a linear iterative approach instead of nonlinear control schemes to improve control performance in such a way that results compared with traditional PID controllers are improved. Application of industrial plant demonstrates the efficiency of the method. [Copyright &y& Elsevier]

This paper is devoted to the finite-time stability analysis and control for switched stochastic delayed systems (SSDSs). The issue of mean-square finite-time stability for nonlinear switched stochastic delayed systems (NSSDSs) is considered. A stability criterion with average dwell time constraint is proposed to ensure the mean-square value of state is not larger than a prescribed threshold during a given time interval. This result can be extended to analysis and design for nonlinear/linear switched stochastic delayed systems. Then, based on partial-mode-dependent/mode-dependent Lyapunov function approaches, mean-square finite-time stability conditions for linear switched stochastic delayed systems (LSSDSs) are developed. Subsequently, both partial-mode-dependent and mode-dependent state feedback controllers for LSSDSs are designed, respectively. Finally, an illustrative example is provided to demonstrated the effectiveness of the method. [ABSTRACT FROM AUTHOR]