Robust adaptive control for a class of uncertain non-affine nonlinear systems using neural state feedback compensation

A robust adaptive control is proposed for a class of uncertain nonlinear non-affine SISO systems. In order to approximate the unknown nonlinear function, an affine type neural network(ATNN) and neural state feedback compensation are used, and then to compensate the approximation error and external disturbance, a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proven that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method. Finally, two simulation examples show that the proposed method exhibits strong robustness, fast response and small tracking error, even for the non-affine nonlinear system with external disturbance, which confirms the effectiveness of the proposed approach.

Nonlinear adaptive switching control for a class of non-affine nonlinear systems

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

Robust control of a class of non-affine nonlinear systems by state and output feedback

Robust control design is presented for a general class of uncertain non-affine nonlinear systems. The design employs feedback linearization, coupled with two high-gain observers: the first to estimate the feedback linearization error based on the full state information and the second to estimate the unmeasured states of the system when only the system output is available for feedback. All the signals in the closed loop are guaranteed to be uniformly ultimately bounded(UUB) and the output of the system is proven to converge to a small neighborhood of the origin. The proposed approach not only handles the difficulty in controlling non-affine nonlinear systems but also simplifies the stability analysis of the closed loop due to its linear control structure. Simulation results show the effectiveness of the approach.

A Discretization Method for Nonlinear Delayed Non-affine Systems

The input time delay is always existent in the practical systems. Analysis of the delay phenomenon in a continuous-time domain is sophisticated. It is appropriate to obtain its corresponding discrete-time model for implementation via digital computer. This paper proposes a new discretization method for calculating a sampled-data representation of nonlinear time-delayed non-affine systems. The proposed scheme provides a finite-dimensional representation for nonlinear systems with non-a^ne time-delayed input enabling existing nonlinear controller design techniques to be applied to them. The performance of the proposed discretization procedure is evaluated by using a nonlinear system with non-affine time-delayed input. For this nonlinear system, various time delay values are considered.

Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.

Regulating Built-in Polar States via Atomic Self-Hybridization for Fast Ion Diffusion Kinetics in Potassium Ion Batteries

Potassium ion batteries(PIBs)are of great interest owing to the low cost and abundance of potassium resources,while the sluggish diffusion kinetics of K^(+)in the electrode materials severely impede their practical applications.Here,self-hybridized BiOCl_(0.5)Br_(0.5) with a floral structure is assembled and used as anode for PIBs.Based on the systematic theoretical calculation and experimental analysis,the unbalance of charge distribution between Cl and Br atoms leads to an enhanced built-in electric field and a larger interlayer spacing,which can enhance the K^(+)diffusion.Furthermore,the K^(+)insertion causes the energetic evolution of polar states in the BiOCl_(0.5)Br_(0.5) crystal framework,where the dynamic correlation between the K^(+)and the halogen atoms leads to the formation of hole-like polarons,which significantly improves the K^(+)diffusion and reaction kinetics during the charging/discharging process,giving important implications to design the electrode materials with high electrochemical performance by engineering the interaction between electronic structure and interface.Therefore,the BiOCl_(0.5)Br_(0.5) anode obtains an excellent performance of 171 mAh·g^(-1) at 1 A·g^(-1) over 2000 cycles in PIBs.

Discretization of Nonlinear Non-affine Time Delay Systems Based on Second-order Hold

When calculating the sampled-date representation of nonlinear systems second-order hold(SOH) assumption can be applied to improving the precision of the discretization results. This paper proposes a discretization method based on Taylor series and the SOH assumption for the nonlinear systems with the time delayed non-affine input. The mathematical structure of the proposed discretization method is explored. This proposed discretization method can provide a precise and finite dimensional discretization model for the nonlinear time-delayed non-affine system by keeping the truncation order of the Taylor series. The performance of the proposed discretization method is evaluated by doing the simulation using a nonlinear system with the time-delayed non-affine input.Different input signals, time-delay values and sampling periods are considered in the simulation to investigate the proposed method.The simulation results demonstrate that the proposed method is practical and easy for time-delayed nonlinear non-affine systems.The comparison between SOH assumption with first-order hold(FOH) and zero-order hold(ZOH) assumptions is given to show the advantages of the proposed method.

Optimal Controller Design for Non-Affine Nonlinear Power Systems with Static Var Compensators for Hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or State Var System(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function.Combining the inverse system method and the Linear Quadratic Regulation(LQR),an optimized SVC controller is designed.The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

Adaptive accurate tracking control of HFVs in the presence of dead-zone and hysteresis input nonlinearities

A novel accurate tracking controller is developed for the longitudinal dynamics of Hypersonic Flight Vehicles(HFVs)in the presence of large model uncertainties,external disturbances and actuator nonlinearities.Distinct from the state-of-the-art,besides being continuity,no restrictive conditions have been imposed on the HFVs dynamics.The system uncertainties are skillfully handled by being seen as bounded"disturbance terms".In addition,by means of backstepping adaptive technique,the accurate tracking(i.e.tracking errors converge to zero as time approaches infinity)rather than bounded tracking(i.e.tracking errors converge to residual sets)has been achieved.What’s more,the accurate tracking problems for HFVs subject to actuator dead-zone and hysteresis are discussed,respectively.Then,all signals of closed-loop system are verified to be Semi-Global Uniformly Ultimate Boundness(SGUUB).Finally,the efficacy and superiority of the developed control strategy are confirmed by simulation results.

Nonlinear Viscoelastic Response of Thermoplastic-Elastomer Melts

Observations are reported on thermoplastic elastomer(ethylene-octene copolymer)melt in small-amplitude shear oscillatory tests and start-up shear tests with various strain rates in the interval of temperatures between 120 and 210◦C.Based on the concept of heterogeneous non-affine polymer networks,constitutive equations are developed for the thermo-mechanical behavior of a melt at threedimensional deformations with finite strains.Adjustable parameters in the stress–strain relations are found by fitting the experimental data.The model is applied to the analysis of Poiseuille flow.The effects of temperature and pressure gradient on the steady velocity profile are studied numerically.