DPC化控技术在棉花上的应用和发展——从防止徒长到系统的定向诱导

本文综述了 DPC 化控技术在中国棉花栽培上的应用和发展。80年代初期,我国棉区开始应用 DPC 防止棉花徒长,随着研究的深入,逐步建立了对棉花生长发育进行系统的定向诱导的化控技术,并推动了常规栽培技术的革新。

Iterative Learning Control With Incomplete Information： A Survey

Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.

Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints

Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions （BLFs） with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closed- loop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach. Index TermsmAdaptive control, neural networks （NNs）, non- linear pure-feedback systems, time-varying constraints.

Hydraulic support stability control of fully mechanized top coal caving face with steep coal seams based on instable critical angle

Analyzed the support instable mode of sliding,tripping,and so on,and believed the key point of the support stability control of fully mechanized coal caving face with steep coal seams was to maintain that the seam true angle was less than the hydraulic support instability critical angle.Through the layout of oblique face,the improvement of support setting load,the control of mining height and nonskid platform,the group support system of end face,the advance optimization of conveyor and support,and the other control tech- nical measures,the true angle of the seam is reduced and the instable critical angle of the support is increased,the hydraulic support stability of fully mechanized coal caving face with steep coal seams is effectively controlled.

Control synthesis for polynomial nonlinear systems and application in attitude control

A method for positive polynomial validation based on polynomial decomposition is proposed to deal with control synthesis problems. Detailed algorithms for decomposition are given which mainly consider how to convert coefficients of a polynomial to a matrix with free variables. Then, the positivity of a polynomial is checked by the decomposed matrix with semidefinite programming solvers. A nonlinear control law is presented for single input polynomial systems based on the Lyapunov stability theorem. The control synthesis method is advanced to multi-input systems further. An application in attitude control is finally presented. The proposed control law achieves effective performance as illustrated by the numerical example.

Observer-based Iterative and Repetitive Learning Control for a Class of Nonlinear Systems

In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.

Energy Efficient Predictive Control for Vapor Compression Refrigeration Cycle Systems

Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.

Intelligent manufacturing system of impeller for computer numerical control(CNC) programming based on KBE

To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering(KBE) was constructed. The structural model of the general knowledge-based system(KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform(i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.

Study on rate ripple and its adaptive suppression method in inertia guidance test equipment

This paper discusses causes of the rate ripple in inertia guidance test equipment IGET, systematically analyses their effects an the rate ripple in IGTE. The analysis result shows： The rate ripple caused by the periodic errors of inductosyn and angular encoder is higher at high speed than that caused by magnetic ripple torque and friction torque, and it cannot be eliminated by adjusting control parameters of the system. And based on the nonlinear adaptive control system theory, the paper puts forward a new control system scheme to eliminate the rate ripple caused by the periodic errors of inductosyn and angular encoder, develops the adaptive control rules and makes simulation and test. Experimental result shows a significant improvement on those tables for the period disturbs under the system scheme designed. By this plan, with the input of rate 200°/s, the rate ripple falls from 5°/s to 0. 4°/s within about 6s adaptive adjustment time, being a twelfth of before adaptation, which can not be reached by common classical controls. The experimental results conform with the simulation, which proves the validity and practicability of the plan.

Discussion on Existing Problems and the Development Trend of Electrical Automation Monitoring System

With the continuous improvement of industrial automation in our country and the use of high technology, promoted the scientific content of traditional industry. The development of electric automation control system inevitably turn towards a systematic, comprehensive development direction. This article first analyze the present problems in electrical automation monitoring system, analyzes its future development trends, so as to provide some reference for the effective application of electrical automation in the future monitoring system, fundamentally realize the resources sharing.