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.
In this technical note, we consider adaptive control of single input uncertain nonlinear systems in the presence of input saturation and unknown external disturbance. By using backstepping ...approaches, two new robust adaptive control algorithms are developed by introducing a well defined smooth function and using a Nussbaum function. The Nussbaum function is introduced to compensate for the nonlinear term arising from the input saturation. Unlike some existing control schemes for systems with input saturation, the developed controllers do not require assumptions on the uncertain parameters within a known compact set and a priori knowledge on the bound of the external disturbance. Besides showing global stability, transient performance is also established and can be adjusted by tuning certain design parameters.
A new method for the state of charge (SOC) estimation of lithium-ion batteries is proposed based on an inclusive equivalent circuit model in this brief. In particular, we propose to utilize the ...neural network to estimate the uncertainties in the battery model online. A radial basis function neural network-based nonlinear observer is then designed to estimate the battery's SOC. Following Lyapunov stability analysis, it is proved that the SOC estimation error is ultimately bounded and the error bound can be arbitrarily small. Experimental and simulation results illustrate the performance of the proposed approach. Furthermore, we compare the SOC estimation results of the extended Kalman filter with the proposed radial basis function neural network-based nonlinear observer. The proposed approach has faster convergence speed and higher precision.
This paper utilizes the concept of a transport partial differential equation (PDE) representation of delayed input to solve the classic problem of output feedback control for a common category of ...uncertain minimum phase linear time-delay systems in spite of co-existence of unknown plant parameter and actuator delay, as well as unmeasurable ordinary differential equation (ODE) and PDE state. In the case of measurable distributed input, the time-varying trajectory tracking is established while in the other case of unmeasurable distributed input, the constant set-point regulation is accomplished. The applicable output feedback control design incorporates the adaptive backstepping technique for ODE plants with the prediction-based boundary control method for PDE systems. There is not any limitation on relative degree of the considered systems. The Lyapunov-based analysis shows the local stability of the closed-loop ODE-PDE cascade systems.
Hysteresis exists in a wide range of physical actuators. Furthermore, such actuators may be subject to failures or faults which are often uncertain in time, value and pattern during system operation. ...However, the available results based on adaptive approaches to compensate for unknown failures of hysteretic actuators are very limited. The work of this note is aimed at addressing such a problem by considering controlling a class of strict feedback systems. A scheme designing smooth adaptive control is proposed for this purpose. It is shown that the designed adaptive controller can ensure all signals are bounded and the tracking error asymptotically approaches a pre-defined bound, no matter whether the hysteretic actuators operate in normal or faulty modes.
In this technical note, a robust adaptive control scheme is proposed based on backstepping techniques for a class of nonlinear systems with unknown parameters. A modeling error may also exist in ...every state equation or channel and it is bounded by a known function which is allowed to depend on all system states. It is shown that the proposed adaptive control scheme can ensure all signals in the closed-loop system bounded, if the strength of system modeling errors is sufficiently weak. Transient performance is also established. Thus stabilizing systems in classical strict-feedback forms with sufficiently small non-triangular structural perturbations is successfully addressed. In the case that system parameters are known, a non-adaptive robust controller is designed to globally exponentially stabilize such a class of nonlinear systems. Finally simulation studies are used to verify the effectiveness of the proposed scheme.
Electric vehicles are beneficial to the environment owing to its nonproduction of emissions and excessive noise; however, they have their own limitations with respect to charging difficulties and ...mileage anxiety. In order to address these problems, dynamic wireless power transfer (DWPT) technology has been developed. In this article, we replace a conventional open-loop method without dc-dc converter with the proposed dc-dc converter in the energy receiver in order to improve output power. Moreover, to make sure that the DWPT system is reliable when the coupling coefficient changes rapidly over a wide range of values, we propose model predictive control (MPC) to ensure optimal dynamic-tracking performance. Considering the fact that sampling delay will cause an error in the controller output, the system is modeled accurately in order to improve the MPC performance. In addition, the MPC and double closed-loop proportional-integral-differential control are compared with simulations and experiments, the results of which demonstrate the effectiveness of MPC-based DWPT.
The paper is concerned with the H ∞ and I 2 -I ∞ filtering design problems for discrete-time nonlinear switched systems with quantized measurements using the Takagi-Sugeno (T-S) fuzzy model. The ...systems under consideration inherently combine features of the switched hybrid systems and the T-S fuzzy systems. The sector bound approach is employed to deal with quantization effects. Based on the fuzzy-basis-dependent Lyapunov function, sufficient conditions are established such that the filtering error system is stochastically stable and a prescribed noise attenuation level in an H ∞ or I 2 -I ∞ sense is achieved. Both numerical and practical examples are provided to show the feasibility and efficiency of the design schemes.
In this paper, a sampled-data fuzzy controller is designed to stabilize a class of chaotic systems. A Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic systems. Based on this ...general model, the exponential stability issue of the closed-loop systems with an input constraint is first investigated by a novel time-dependent Lyapunov functional, which is positive definite at sampling times but not necessary between the sampling times. Then, two sufficient conditions are developed for sampled-data fuzzy controller synthesis of the underlying T-S fuzzy model with or without input constraint. All the proposed results in this paper depend on both the upper and lower bounds on a sampling interval, and the available information about the actual sampling pattern is fully utilized. The proposed sampled-data fuzzy control scheme is successfully applied to the chaotic Lorenz system, which is shown to be effective and less conservative compared with existing results.
This paper is concerned with the problem of dissipative control for Takagi-Sugeno fuzzy systems under time-varying sampling with a known upper bound on the sampling intervals. Based on the ...time-dependent Lyapunov-Krasovskii functional approach, which makes full use of the available information about the actual sampling pattern, a sufficient condition is established to guarantee the sampled-data systems to be exponentially stable and strictly (Q, S, R)-γ-dissipative. Based on the criterion, a design algorithm for the desired sampled-data controller is proposed. The effectiveness and benefits of the results developed in this paper is demonstrated by a controller design for a truck-trailer system.
