Event-Triggered Neural Control of Nonlinear Systems With Rate-Dependent Hysteresis Input Based on a New Filter
TL;DR: In this paper, a second-order filter is proposed to overcome the design conflict between the quantized networked control signal and the rate-dependent hysteresis characteristics, and a novel adaptive control strategy is developed from a neural network technique and a modified backstepping recursive design.
Abstract: In controlling nonlinear uncertain systems, compensating for rate-dependent hysteresis nonlinearity is an important, yet challenging problem in adaptive control. In fact, it can be illustrated through simulation examples that instability is observed when existing control methods in canceling hysteresis nonlinearities are applied to the networked control systems (NCSs). One control difficulty that obstructs these methods is the design conflict between the quantized networked control signal and the rate-dependent hysteresis characteristics. So far, there is still no solution to this problem. In this paper, we consider the event-triggered control for NCSs subject to actuator rate-dependent hysteresis and failures. A new second-order filter is proposed to overcome the design conflict and used for control design. With the incorporation of the filter, a novel adaptive control strategy is developed from a neural network technique and a modified backstepping recursive design. It is proved that all the control signals are semiglobally uniformly ultimately bounded and the tracking error will converge to a tunable residual around zero.
Citations
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TL;DR: In this paper, an adaptive fuzzy hierarchical sliding mode control method was proposed to deal with the control problem for uncertain under-actuated switched nonlinear systems with actuator control in the presence of uncertain underactuated switches.
Abstract: This paper aims at putting forward an adaptive fuzzy hierarchical sliding mode control method to deal with the control problem for uncertain under-actuated switched nonlinear systems with actuator ...
65Â citations
TL;DR: A novel adaptive inverse control strategy is established to eliminate vibration, tackle backlash, and compensate for system uncertainties, and the bounded stability of the controlled system is analyzed and demonstrated by exploiting the Lyapunov's criterion.
Abstract: This article involves the adaptive inverse control of a coupled vessel-riser system with input backlash and system uncertainties. By introducing an adaptive inverse dynamics of backlash, the backlash control input is divided into a mismatch error and an expected control command, and then a novel adaptive inverse control strategy is established to eliminate vibration, tackle backlash, and compensate for system uncertainties. The bounded stability of the controlled system is analyzed and demonstrated by exploiting the Lyapunov’s criterion. The simulation comparison experiments are finally presented to verify the feasibility and effectiveness of the control algorithm.
39Â citations
TL;DR: This paper addresses the finite-time controller design for a class of nonlinear systems in the non-strict feedback form subject to unknown system dynamics and disturbances, arbitrary asymmetric time-varying output constraints, four types of input nonlinearities, and unknown control direction.
36Â citations
TL;DR: In this paper , a decentralized adaptive control method for fractional-order interconnected systems with unknown control directions is proposed, where smooth functions are introduced to compensate for unknown interactions among subsystems adaptively.
Abstract: This paper concentrates on the study of the decentralized fuzzy control method for a class of fractional-order interconnected systems with unknown control directions. To overcome the difficulties caused by the multiple unknown control directions in fractional-order systems, a novel fractional-order Nussbaum function technique is proposed. This technique is much more general than those of existing works since it not only handles single/multiple unknown control directions but is also suitable for fractional/integer-order single/interconnected systems. Based on this technique, a new decentralized adaptive control method is proposed for fractional-order interconnected systems. Smooth functions are introduced to compensate for unknown interactions among subsystems adaptively. Furthermore, fuzzy logic systems are utilized to approximate unknown nonlinearities. It is proven that the designed controller can guarantee the boundedness of all signals in interconnected systems and the convergence of tracking errors. Two examples are given to show the validity of the proposed method.
31Â citations
01 Jan 2022
TL;DR: In this paper , a novel event-triggered adaptive fuzzy output-feedback control scheme was proposed for a class of nonstrict-feed back nonlinear systems with asymmetric and time-varying output constraints, as well as unknown nonlinear functions.
Abstract: This article addresses the event-triggered adaptive fuzzy output-feedback control problem for a class of nonstrict-feedback nonlinear systems with asymmetric and time-varying output constraints, as well as unknown nonlinear functions. By designing a linear observer to estimate the unmeasurable states, a novel event-triggered adaptive fuzzy output-feedback control scheme is proposed. The barrier Lyapunov function (BLF) and the error transformation technique are used to handle the output constraint under a completely unknown initial tracking condition. It is shown that with the proposed control scheme, all the solutions of the closed-loop system are semiglobally bounded, and the tracking error converges to a small set near zero, while the output constraint is satisfied within a predetermined finite time, even when the constraint condition is violated initially. Moreover, with the proposed event-triggering mechanism (ETM), the Zeno behavior can be strictly ruled out. An example is finally provided to demonstrate the effectiveness of the proposed control method.
27Â citations
References
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Book•
01 Jan 1995
TL;DR: In this paper, the focus is on adaptive nonlinear control results introduced with the new recursive design methodology -adaptive backstepping, and basic tools for nonadaptive BackStepping design with state and output feedbacks.
Abstract: From the Publisher:
Using a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties. The focus is on adaptive nonlinear control results introduced with the new recursive design methodology--adaptive backstepping. Describes basic tools for nonadaptive backstepping design with state and output feedbacks.
6,923Â citations
TL;DR: A direct adaptive tracking control architecture is proposed and evaluated for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible.
Abstract: A direct adaptive tracking control architecture is proposed and evaluated for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible. The architecture uses a network of Gaussian radial basis functions to adaptively compensate for the plant nonlinearities. Under mild assumptions about the degree of smoothness exhibit by the nonlinear functions, the algorithm is proven to be globally stable, with tracking errors converging to a neighborhood of zero. A constructive procedure is detailed, which directly translates the assumed smoothness properties of the nonlinearities involved into a specification of the network required to represent the plant to a chosen degree of accuracy. A stable weight adjustment mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with example systems. >
2,254Â citations
TL;DR: The controller updates considered here are event-driven, depending on the ratio of a certain measurement error with respect to the norm of a function of the state, and are applied to a first order agreement problem.
Abstract: Event-driven strategies for multi-agent systems are motivated by the future use of embedded microprocessors with limited resources that will gather information and actuate the individual agent controller updates. The controller updates considered here are event-driven, depending on the ratio of a certain measurement error with respect to the norm of a function of the state, and are applied to a first order agreement problem. A centralized formulation is considered first and then its distributed counterpart, in which agents require knowledge only of their neighbors' states for the controller implementation. The results are then extended to a self-triggered setup, where each agent computes its next update time at the previous one, without having to keep track of the state error that triggers the actuation between two consecutive update instants. The results are illustrated through simulation examples.
1,876Â citations
01 Jan 2016
TL;DR: Nonlinear Control Design: Geometric, Adaptive and Robust ... 1.2.3 Adaptive control as dynamic nonlinear feedback 1.1.4 Lyapunov-based design Adaptive Nonlinear Control.
Abstract: Nonlinear Control Design: Geometric, Adaptive and Robust ... 1.1.1 Emergence of adaptive control 1.1.2 Achievements of adaptive linear control 1.1.3 Adaptive control as dynamic nonlinear feedback 1.1.4 Lyapunov-based design 1.1.5 Estimation-based design Adaptive Nonlinear Control 1.2.1 A nonlinear challenge 1.2.2 A structural obstacle 1.2.3 Early results Preview of the Main Topics 1.3.1 Classes of ...
1,272Â citations
TL;DR: It is shown that the proposed control schemes guarantee that all the closed-loop signals are globally bounded and the tracking/stabilization error exponentially converges towards a compact set which is adjustable.
Abstract: In this technical note, the problem of event-trigger based adaptive control for a class of uncertain nonlinear systems is considered. The nonlinearities of the system are not required to be globally Lipschitz. Since the system contains unknown parameters, it is a difficult task to check the assumption of the input-to-state stability (ISS) with respect to the measurement errors, which is required in most existing literature. To solve this problem, we design both the adaptive controller and the triggering event at the same time such that the ISS assumption is no longer needed. In addition to presenting new design methodologies based on the fixed threshold strategy and relative threshold strategy, we also propose a new strategy named the switching threshold strategy. It is shown that the proposed control schemes guarantee that all the closed-loop signals are globally bounded and the tracking/stabilization error exponentially converges towards a compact set which is adjustable.
804Â citations