Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

Study on the Principle Model and Simplification of Subway Station Itemized Energy Consumption

Owing to the constant modernization and urbanization of China,most cities have subways,and the total power consumption of subway stations has been rising,which contradicts with China’s green goals.In this regard,energy consumption indicators for major energy use projects in subway stations should be established,comprehensive evaluation and detailed research on the current situation of subway operation should be conducted,and specific energy-saving measures should be taken from a diversified perspective.It is crucial to systematically sort out the principle of sub-item energy consumption in subway stations,and practice and explore the specific simplification measures of the principle model of sub-item energy consumption,so as to lay a solid foundation for achieving the goal of reducing energy consumption of subway stations.

MIMO Soft-sensor Model of Nutrient Content for Compound Fertil- izer Based on Hybrid Modeling Technique

In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-sensor technique becomes an indispensable method to implement real-time quality control. In this article, a new model of multi-inputs multi-outputs （MIMO） soft-sensor, which is constructed based on hybrid modeling technique, is proposed for these interactional variables. Data-driven modeling method and simplified first principle modelingmethod are combined in this model. Data-driven modeling method based on limited memory partial least squares（LM-PLS） al.gorithm is used to build soft-senor models for some secondary variables.then, the simplified first principle model is used to compute three primary variables on line. The proposed model has been used in practicalprocess; the results indicate that the proposed model is precise and efficient, and it is possible to realize on line quality control for compound fertilizer process.

Rural Tourism Development in China:Principles,Models and the Future

Rural tourism in China,has undergone a rapid development in the last three decades.It is an emerging and effective catalyst that promotes industrial restructuring,agricultural development and the upgrading of rural areas.However,there remains little understanding about the core issues of rural tourism in China:the exact connotation,the principles,the development models and the future directions.This review paper identifies the key issues based on literature analysis,national statistics and press reports to form a general picture of the past,the current and the future prospects of China's rural tourism.The paper firstly addresses the definition,content and principles of rural tourism,and then provides an overview and brief evaluation of the progress and the current development models in China.Finally,based on the analysis of the experiences and problems,the authors sum up with five pathways of the future development of China's rural tourism from the perspective of rural tourism resources,product,market and promotion.

Super-resolution amplification of bitmap images based on 3D modeling theory

As a general format of the image,bitmap(BMP)image has wide applications,and consequently it is an important part of image processing.By segmenting the bitmap and combining the three-dimesional(3D)model of the discrete algorithm with the scanning line compensation algorithm,a mathematical model is built.According to the topological relations between several control points on the model surface,the surface of the model is discretized,and a planar triangle sequence is used to describe 3D objects.Finally,the bitmap is enlarged by combining the borrowing compensation based on 3D modeling principle of discrete algorithm with the scanning line compensation algorithm of binary lattice image,thus getting a relatively clear enlarged BMP image.

Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction

The equilibrium model for multicomponent rare earth extraction is developed using neural networks, which combined with the material balance model could give online prediction of component content in countercurrent rare earth (extraction) production. Simulation experiments with industrial operation data prove the effectiveness of the hybrid soft-(sensor).

Global disturbance rejection of a class of nonlinear systems with unknown exosystems

An asymptotic rejection algorithm is proposed for a class of nonlinear systems that have not only additive nonlinear uncertainties but also unknown disturbances. The disturbances are generated from an unknown exosystem, and are assumed to be sinusoidal disturbances with unknown amplitude and frequency. By using the technique of backstepping and adaptive control, a nonlinear state feedback controller is designed. Under the proposed controller, the system＇s state variables asymptotically converge to zero, and the disturbances are rejected completely. The approach used is an integration of the robust stabilization technique, adaptive technique, and backstepping technique.

Distributed Robust Containment Control of Linear Heterogeneous Multi-Agent Systems:An Output Regulation Approach

In this paper,we consider the robust output containment problem of linear heterogeneous multi-agent systems under fixed directed networks.A distributed dynamic observer based on the leaders’measurable output was designed to estimate a convex combination of the leaders’states.First,for the case of followers with identical state dimensions,distributed dynamic state and output feedback control laws were designed based on the state-coupled item and the internal model compensator to drive the uncertain followers into the leaders’convex hull within the output regulation framework.Subsequently,we extended theoretical results to the case where followers have nonidentical state dimensions.By establishing virtual errors between the dynamic observer and followers,a new distributed dynamic output feedback control law was constructed using only the states of the compensator to solve the robust output containment problem.Finally,two numerical simulations verified the effectiveness of the designed schemes.

Control Design for Harmonic Disturbance Rejection for Robot Manipulators with Bounded Inputs

Currently most of control methods are of one degree of freedom（1-DOF） control structure for the robot systems which are affected by unmeasurable harmonic disturbances,at the same time in order to obtain perfect disturbance attenuation level,the controller gain must be increased.In practice,however,for robotic actuators,there are physical constraints that limit the amplitude of the available torques.This paper considers the problem of tracking control under input constraints for robot manipulators which are affected by unmeasurable harmonic disturbances.A new control scheme is proposed for the problem,which is composed of a parameter-dependent nonlinear observer and a tracking controller.The parameter-dependent nonlinear observer,designed based on the internal model principle,can achieve an estimation and compensation of a class of harmonic disturbances with unknown frequencies.The tracking controller,designed via adaptive control techniques,can make the systems asymptotically track the desired trajectories.In the control design,the continuous piecewise differentiable increasing function is used to limit control input amplitude,such that the control input saturation is avoided.The Lyapunov stability of closed loop systems is analyzed.To validate proposed control scheme,simulation results are provided for a two link horizontal robot manipulator.The simulation results show that the proposed control scheme ensures asymptotic tracking in presence of an uncertain external disturbance acting on the system.An important feature of the methodology consists of the fact that the designed controller is of 2-DOF control structure,namely,it has the ability to overcome the conflict between controller gain and robustness against external disturbances in the traditional 1 -DOF control structure framework.

Effect of Retained Austenite on Corrosion Behavior of Ultrafine Bainitic Steel in Marine Environment

In this study,the impact of retained austenite on corrosion initiation,propagation,and resistance of ultrafine bainitic steels in marine environments based on the one-step and two-step bainitic isothermal transformation was investigated using a combination of theoretical calculations and experimental methods.According to the results,the microstructure of ultrafine bainitic steels was composed of parallel arranged bainite ferrite(BF)and retained austenite(RA).The fraction of the block RA was significantly reduced,whereas the amount of the film RA increased through the two-step bainitic transformation.In the initial stage of corrosion,micro-galvanic effects occurred between the multiphases due to the difference in nobility,leading to the selective dissolution of BF sheaves,which is adjacent to the block RA in the one-step bainitic steel.However,uniformly distributed film RA in the two-step bainitic steel acted as a barrier against corrosion propagation.The electrochemical measurements and neutral salt spray tests revealed a relatively lower corrosion rate for the two-step bainitic steel,indicating a higher corrosion resistance than the one-step bainitic steel.The corrosion products layer mainly consisted ofα-FeOOH,γ-FeOOH,and Fe_(3)O_(4),which were stable and favorable for the formation of a protective rust layer.

Precision attitude regulation of uncertain flexible spacecraft

Consider the precision attitude regulation with vibration suppression for an uncertain and disturbed flexible spacecraft.The disturbance at issue is typically any finite superposition of sinusoidal signals with unknown frequencies and step signals of unknown amplitudes.First we show that the conventional mathematical model for flexible spacecrafts is transformable to a multi-input multi-output(MIMO)strict-feedback nonlinear normal form.Particularly it is strongly minimum-phase and has a well-defined uniform vector relative degree.Then it enables us to develop an adaptive internal model-based controller in the framework of adaptive output regulation to solve the problem.It is proved that asymptotic stability can be guaranteed for the attitude regulation task and the vibration of flexible appendages vanishes asymptotically.Hence,the present study explores a new idea for control of flexible spacecraft in virtue of its system structures.

An Adaptive Regulation Problem and Its Application

This paper studies an adaptive regulation problem for the modified FitzHugh-Nagumo neuron model under external electrical stimulation. We first present the solution of the global robust output regulation problem for output feedback system with an uncertain exosystem which models the external electrical stimulation with unknown frequency and amplitude. Then, we show that the robust control problem for the modified FitzHugh-Nagumo neuron model can be formulated as the global robust output regulation problem and the solvability conditions for the output regulation problem for the modified FitzHugh-Nagumo neuron model are all satisfied. Then, we apply the obtained output regulation result to constructing an output feedback control law for the modified FitzHugh-Nagumo neuron model to achieve global stability of the closed-loop system in the presence of uncertain parameters and external stimulus. An example is given to show that the proposed algorithm can completely reject the external electrical stimulation.