Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

Compensation for secondary uncertainty in electro-hydraulic servo system by gain adaptive sliding mode variable structure control

Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.

Adaptive Output Regulation of a Class of Nonlinear Output Feedback Systems With Unknown High Frequency Gain

This paper presents an output feedback design approach based on the adaptive control scheme developed for nonlinearly parameterized systems,to achieve global output regulation for a class of nonlinear systems in output feedback form.We solve the output regulation problem without the knowledge of the sign and the value of the high frequency gain a priori.It is not necessary to have both the limiting assumptions that the exogenous signal co and the unknown parameter ju belong to a prior known compact set and the high frequency gain has a determinate lower and upper bounds.The effectiveness of the proposed algorithm is shown with the help of an example.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

Adaptive Fuzzy Backstepping Output Feedback Control of Nonlinear Time-delay Systems with Unknown High-frequency Gain Sign

In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and singleoutput （SISO） strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.

Fuzzy Adaptive Control of Stochastic Nonlinear Systems with Unknown Virtual Control Gain Function

The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.

Adaptive augmentation of gain-scheduled controller for aerospace vehicles

This paper proposes an adaptive augmentation control design approach of the gain-scheduled controller.This extension is motivated by the need for augmentation of the baseline gainscheduled controller.The proposed approach can be utilized to design flight control systems for advanced aerospace vehicles with a large parameter variation.The flight dynamics within the flight envelope is described by a switched nonlinear system,which is essentially a switched polytopic system with uncertainties.The flight control system consists of a baseline gain-scheduled controller and a model reference adaptive augmentation controller,while the latter can recover the nominal performance of the gainscheduled controlled system under large uncertainties.By the multiple Lyapunov functions method,it is proved that the switched nonlinear system is uniformly ultimately bounded.To validate the effectiveness of the proposed approach,this approach is applied to a generic hypersonic vehicle,and the simulation results show that the system output tracks the command signal well even when large uncertainties exist.

Using Adaptive Gain Scheduling LQR Method Control of Arm Driven Inverted Pendulum System Based on PIC18F4431

The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum with variable position of the ann. To solve this problem, this paper presents a mathematical model for arm driven inverted pendulum in mid-position configuration and an adaptive gain scheduling linear quadratic regulator control method for the stabilizing the inverted pendulum. The proposed controllers for arm driven inverted pendulum are simulated using MATLAB-SIMULINK and implemented on an experiment system using PIC 18F4431 mieroeontroller. The result of experiment system shows the control performance to be very good in a wide range stabilization of the arm position.

Dynamic Balance Control Based on an Adaptive Gain-scheduled Backstepping Scheme for Power-line Inspection Robots

This paper presents an adaptive gain-scheduled backstepping control(AGSBC) scheme for the balance control of an underactuated mechanical power-line inspection(PLI) robotic system with two degrees of freedom and a single control input.First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points,an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control(GSBC) scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.

Variable Structure Model Reference Adaptive Control with Unknown High Frequency Gain Sign

可变结构模型引用为有比一个和未知高频率获得符号大的相对的度的工厂的适应控制被建议。一个切换的计划基于为靠近的环系统的第一个辅助错误设计的监视功能被介绍。在至多切换和追踪的错误的一个有限数字收敛到能被适当地选择一些设计参数使任意地小的一个剩余集合以后，在监视函数的管理下面，切换停止，这被显示出在至多切换和追踪的错误的一个有限数字收敛到能被适当地选择一些设计参数使任意地小的一个剩余集合以后。

Excessive 5-year weight gain predicts metabolic syndrome development in healthy middle-aged adults

AIM:To quantitatively examine the impacts of an easyto-measure parameter-weight gain-on metabolic syndrome development among middle-aged adults. METHODS:We conducted a five-year interval observational study.A total of 1384 middle-aged adults not meeting metabolic syndrome(MetS)criteria at the initial screening were included in our analysis.Baseline data such as MetS-components and lifestyle factors were collected in 2002.Body weight and MetS-components were measured in both 2002 and 2007.Participants were classified according to proximal quartiles of weight gain(WG)in percentages(%WG≤1%,1%< %WG≤5%,5%<%WG≤10%and%WG>10%, defined as:control,mild-WG,moderate-WG and severe-WG groups,respectively)at the end of the follow-up. Multivariate models were used to assess the association between MetS outcome and excessive WG in the total population,as well as in both genders. RESULTS:In total,175(12.6%)participants fulfilled MetS criteria within five years.In comparison to the control group,mild-WG adults had an insignificant risk for MetS development while adults having moderate-WG had a 3.0-fold increased risk for progression to MetS [95%confidence interval(CI),1.8-5.1],and this risk was increased 5.4-fold(95%CI,3.0-9.7)in subjects having severe-WG.For females having moderate-and severe-WG,the risk for developing MetS was 3.6(95% CI,1.03-12.4)and 5.5(95%CI,1.4-21.4),respectively. For males having moderate-and severe-WG,the odds ratio for MetS outcome was respectively 3.0(95%CI, 1.6-5.5)and 5.2(95%CI,2.6-10.2). CONCLUSION:For early-middle-aged healthy adults with a five-year weight gain over 5%,the severity of weight gain is related to the risk for developing metabolic syndrome.

Stable adaptive fuzzy control of nonlinear systems using small-gain theorem and LMI approach

A new design scheme of stable adaptive fuzzy control for a class of nonlinear systems is proposed in this paper.The T-S fuzzy model is employed to represent the systems.First,the concept of the so-called parallel distributed compensation （PDC） and linear matrix inequality （LMI） approach are employed to design the state feedback controller without considering the error caused by fuzzy modeling.Sufficient conditions with respect to decay rate α are derived in the sense of Lyapunov asymptotic stability.Finally,the error caused by fuzzy modeling is considered and the input-to-state stable （ISS） method is used to design the adaptive compensation term to reduce the effect of the modeling error.By the small-gain theorem,the resulting closed-loop system is proved to be input-to-state stable.Theoretical analysis verifies that the state converges to zero and all signals of the closed-loop systems are bounded.The effectiveness of the proposed controller design methodology is demonstrated through numerical simulation on the chaotic Henon system.

Adaptive Processing Gain Data Services in Cellular CDMA in Presence of Soft Handoff with Truncated ARQ

An adaptive data transmission scheme based on variable spreading gain (VSG) is studied in cellular CDMA network in presence of soft handoff (HO). The processing gain is varied according to traffic intensity meet-ing a requirement on data bit error rate (BER). The overall performance improvement due to processing gain adaptation and soft HO is evaluated and compared with a fixed rate system. The influence of soft HO pa-rameters on rate adaptation and throughput and delay performance of data is indicated. Further truncated automatic repeat request (T-ARQ) is used in link layer to improve the performance of delay sensitive ser-vices. The joint impact of VSG based transmission in presence of soft handoff at physical layer and T-ARQ at link layer is evaluated. A variable packet size scheme is also studied to meet a constraint on packet loss.

The Performance Gain of Cognitive Radio in Adaptive Modulation Scheme

Cognitive radio is considered as one of the main enablers for provisioning dynamic and flexible spectrum/channel allocation in wireless communications. The reliable data transmission over cognitive radio should employ modulation, coding etc. and thus the performance of such a new communication system should be realized. In this paper, we provide the performance analysis of adaptive modulation over a cognitive radio system in order to study the potential gain of cognitive radios in terms of spectral efficiency. The results obtained show that the performance gain of cognitive radio in adaptive modulation is remarkable.

Fault diagnosis based on high-gain observer with an update law for a class of nonlinear systems

In this paper,by using the well-known high-gain observer design,an update law for the gain and an adaptive estimation of parameters,a new method of fault diagnosis for a class of nonlinear systems is presented.Without resort to any transformation for the parameters,the estimation errors of the states and the parameters are guaranteed to be globally exponentially convergent by a persistent excitation condition.Compared to the existing results,it can be applied to nonlinear systems with nonlinear terms admitting an incremental rate depending on the measured output.A case study further verifies the validity of the proposed research.

Spatial Optimization and Reconstruction of Old Communities under the Background of Aging

As aging becomes increasingly serious,how to make the life of the elderly more convenient and comfortable has become one of the social problems to be solved urgently.Old residential areas are one of spaces where the elderly gather.In this paper,the prominent problems in the community space of existing old residential areas that are not conducive to the life of the elderly were analyzed,and corresponding countermeasures to transform the community space were put forward.It is hoped that public space can play its due value and make old residential areas glow with new vitality.

自适应增益APA-AG算法的研究

为了提高自适应滤波器的收敛性和跟踪性,提出了一种自适应增益APA-AG算法。通过分析估计输出误差信号,获得了参数迭代步长的一个特定值估计,以实现集平均代价函数最小化。仿真结果表明,相比较于传统的APA算法,文中研究的APA-AG算法具有更快的收敛速率和更好的跟踪特性。

基于鲁棒二自由度增益自适应Smith预估器的冷轧厚度计型AGC

综合考虑冷轧厚度计型AGC(automatic gauge control)控制对象模型的渐变性以及在低速轧制时大时延引起的厚度反馈较大时滞,提出一种冷轧厚度计型AGC控制的改进方法来减弱这些系统不确定性和厚度反馈时滞带来的不利影响.推导出针对任意阶对象的增益自适应调节律,并给出了在保证系统鲁棒稳定条件下的控制器和滤波器参数选取原则.仿真结果证明这一新方法可有效地抑制干扰,而且在对象参数摄动时系统具有鲁棒稳定性.

低银SnAgCu系无铅焊膏的板级工艺适应性研究

新开发了G-SAC105和G-SAC0307两种低银无铅焊膏,对其进行了板级封装的工艺适应性研究。结果表明,在(25±5)℃和120℃环境下,两种焊膏塌落度均为0.15 mm,在150℃环境下放置时,塌落度均为0.20 mm,都具有较好的抗热塌陷性,银含量的降低并不会影响焊膏的塌落度;焊膏印刷质量良好,焊后焊点光亮、饱满,未出现气孔或飞溅现象;焊态下G-SAC105和G-SAC0307金属间化合物厚度比较接近,均小于SAC305。

Smith预估控制策略在AGC系统中的应用

介绍一种新型的ＡＧＣ系统——Ｓｍｉｔｈ－ＡＧＣ系统。给出系统结构；对控制器自适应增益算法进行了推导；对系统稳定性进行了分析并给出Ｓｍｉｔｈ－ＡＧＣ系统稳定的充分必要条件。该ＡＧＣ系统已用于本钢冷连轧机；统计分析表明，成品相对厚差精度优于±１％。