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.

DFIG Voltage Control Based on Dynamically Adjusted Control Gains

The increasing penetration of wind power presents many technical challenges to power system operations. An important challenge is the need of voltage control to maintain the terminal voltage of a wind plant to make it a PV bus like conventional generators with excitation control. In the previous work for controlling wind plant, especially the Doubly Fed Induction Generator (DFIG) system, the proportional-integral (PI) controllers are popularly applied. These approaches usually need to tune the PI controllers to obtain control gains as a tradeoff or compromise among various operating conditions. In this paper, a new voltage control approach based on a different philosophy is presented. In the proposed approach, the PI control gains for the DFIG system are dynamically adjusted based on the dynamic, continuous sensitivity which essentially indicates the dynamic relationship between the change of control gains and the desired output voltage. Hence, this control approach does not require any good estimation of fixed control gains because it has the self-learning mechanism via the dynamic sensitivity. This also gives the plug-and-play feature of DFIG controllers to make it promising in utility practices. Simulation results verify that the proposed approach performs as expected under various operating conditions.

Adaptive adjustment of iterative learning control gain matrix in harsh noise environment

For the robustness problem of open-loop P-type iterative learning control under the influence of measurement noise which is inevitable in actual systems, an adaptive adjustment algorithm of iterative learning nonlinear gain matrix based on error amplitude is proposed and two nonlinear gain functions are given. Then with the help of Bellman-Gronwall lemma, the robustness proof is derived. At last, an example is simulated and analyzed. The results show that when there exists measurement noise, the proposed learning law adjusts the learning gain matrix on line based on error amplitude, thus can make a compromise between learning convergence rate and convergence accuracy to some extent： the fast convergence rate is achieved with high gain in initial learning stage, the strong robustness and high convergence accuracy are achieved at the same time with small gain in the end learning stage, thus better learning results are obtained.

Fixed-Time Stabilization of a Class of Strict-Feedback Nonlinear Systems via Dynamic Gain Feedback Control

This paper presents a novel fixed-time stabilization control(FSC)method for a class of strict-feedback nonlinear systems involving unmodelled system dynamics.The key feature of the proposed method is the design of two dynamic parameters.Specifically,a set of auxiliary variables is first introduced through state transformation.These variables combine the original system states and the two introduced dynamic parameters,facilitating the closed-loop system stability analyses.Then,the two dynamic parameters are delicately designed by utilizing the Lyapunov method,ensuring that all the closed-loop system states are globally fixed-time stable.Compared with existing results,the“explosion of complexity”problem of backstepping control is avoided.Moreover,the two designed dynamic parameters are dependent on system states rather than a time-varying function,thus the proposed controller is still valid beyond the given fixedtime convergence instant.The effectiveness of the proposed method is demonstrated through two practical systems.

Single-Stage Wide-Range CMOS VGA with Temperature Compensation and Linear-in-dB Gain Control

A novel wide-range CMOS variable gain amplifier （VGA） topology is presented. The proposed VGA is composed of a variable transconductor and a novel variable output resistor and can offer a high gain variation range of 80dB while using a single variable-gain stage. Temperature-compensation and decibel-linear gain characteristic are achieved by using a control circuit that provides a gain error lower than ±1.5dB over the full temperature and gain ranges. Realized in 0.25μm CMOS technology, a prototype of the proposed VGA provides a total gain range of 64.5dB with 55.6dB-linear range,a P-1dB varying from - 17.5 to 11.5dBm,and a 3dB-bandwith varying from 65 to 860MHz while dissipating 16.5mW from a 2.5V supply voltage.

Influence of mill modulus control gain on vibration in hot rolling mills

The rolling mill vibration is characterized by the coupling effects among mechanical,electrical,hydraulic and interfacial subsystems.The influence of the mill modulus control gain in automatic gauge control on the vibration in hot rolling mills was investigated.Firstly,an experiment related to the mill modulus control gain was carried out in the hot rolling mill process,and it was found that the rolling mill vibration increases with the mill modulus control gain.Then,based on the Sims rolling force method,the coupling dynamic model was established to explain this phenomenon.Finally,the influence of mill modulus control gain on the vibration was analyzed numerically on the basis of the coupling dynamic model.Moreover,the agreement between the experimental results and the simulation results was confirmed and the measure reducing the mill modulus control gain was obtained to relieve mill vibration.

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.

Improved control of intelligent excavator using proportional-integral-plus gain scheduling

Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to autonomously dig trenches without human intervention. One stumbling block is the achievement of adequate, accurate, quick and smooth movement under automatic control, which is difficult for traditional control algorithm, e.g. PI/PID. A gain scheduling design, based on the true digital proportional-integral-plus (PIP) control methodology, was utilized to regulate the nonlinear joint dynamics. Simulation and initial field tests both demonstrated the feasibility and robustness of proposed technique to the uncertainties of parameters, time delay and load disturbances, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner. The tracking error magnitudes for oblique straight line and horizontal straight line are less than 20 mm and 50 mm, respectively, while the velocity reaches 9 m/min.

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.

STUDY ON GAIN-SCHEDULING PROBLEM IN FLIGHT CONTROL

Gain-scheduling has got its wide applications in modern flight control, in which control gains are scheduled with variables such as dynamic pressure and Mach number, to meet dynamic response requirements in different flight conditions. Classical gain-scheduling approaches may result in some problems, which can not guarantee global robustness and stability in transitions of different flight conditions. Gain-scheduling problem is systematically investigated from robustness point of view in the paper. Detailed procedures for gain-scheduled controller to achieve both robustness and stability performance are given and applied to a typical flight control system. For switching stability problems of different flight conditions in flight control systems, a new approach is proposed, in which different flight conditions are reduced into a parameter varying plant using interpolation firstly, and then parameter-varying controller design goes next. Though interpolation errors may exist, the robust parameter varying controller design can compensate for those uncertainties and errors, and finally achieve good performance of robustness and switching stability during transitions. Illustrative simulation at last shows satisfactory results.

Gain Scheduling Control of Nonlinear Shock Motion Based on Equilibrium Manifold Linearization Model

The equilibrium manifold linearization model of nonlinear shock motion is of higher accuracy and lower complexity over other models such as the small perturbation model and the piecewise-linear model. This paper analyzes the physical significance of the equilibrium manifold linearization model, and the self-feedback mechanism of shock motion is revealed. This helps to describe the stability and dynamics of shock motion. Based on the model, the paper puts forwards a gain scheduling control method for nonlinear shock motion. Simulation has shown the validity of the control scheme.

Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

This paper studies the consensus control of multiagent systems with binary-valued observations.An algorithm alternating estimation and control is proposed.Each agent estimates the states of its neighbors based on a projected empirical measure method for a holding time.Based on the estimates,each agent designs the consensus control with a constant gain at some skipping time.The states of the system are updated by the designed control,and the estimation and control design will be repeated.For the estimation,the projected empirical measure method is proposed for the binary-valued observations.The algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued observations.And,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’states.Finally,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing literature.Simulations are given to demonstrate the theoretical results.

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.

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.

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。

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 Output Feedback Control Synthesis with Mixed Frequency Small Gain Specifications

这篇论文与混合频率为线性连续时间的系统经由动态输出反馈涉及控制合成问题小获得说明。为设计动态产量反馈控制器的一个新方法被介绍以便结果靠近环的系统是 asymptotically 稳定的并且在两个有限频率范围和全部频率范围满足小获得说明的要求。设计条件以一套线性矩阵不平等(LMI ) 的答案被给。最后，一个数字例子被给与存在那个比较说明设计过程和建议方法的优点。

CMOS Automatic Gain Control Circuit with DC Offset Cancellation for FM/cw Ladar

This paper presented an automatic gain control （AGC） circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier （VGA） chain with a novel DC offset canceller circuit, which contained an improved Gilbert cell and a Gm-C feedback loop. To keep the VGA with a linearity in dB characteristic, an improved exponential gain control circuit was introduced. The AGC was implemented in 0.18 gm standard CMOS process. Simulation and measurement results verified that its gain ranged from -20 dB to 30 dB, and band- width ranged from 100 kHz to 10 MHz. Its power consumption was 19.8 mW under a voltage supply of 3.3 V.

Analytical Structures of Typical Takagi-Sugeno Fuzzy PID Gain Scheduling Controllers

The analytical structure of a class of typical Takagi Sugeno (TS) fuzzy controllers is revealed in this paper.The TS fuzzy controllers consist of three or more trapezoidal input fuzzy sets, Zadeh fuzzy logic AND operator,fuzzy rules with linear consequent, and the centriod defuzzifier. The TS fuzzy controllers are proved to be accurately nonlinear PID controllers with gains continuously changing with process output. The analytical expressions of the variable gains of the TS fuzzy controllers are derived and their mathematical characteristics including the bounds and geometrical shape of the gain variation are analyzed. The resulting explicit structures show that the TS fuzzy controllers are inherently nonlinear PID gain scheduling controllers with variable gains in different regions of input space.

Polytopic LPV modeling and gain-scheduled switching control for a flexible air-breathing hypersonic vehicle

A novel gain-scheduled switching control method for the longitudinal motion of a flexible air-breathing hypersonic vehicle （FAHV） is proposed. Firstly, velocity and altitude are selected as scheduling variables, a polytopic linear parameter varying （LPV） model is developed to represent the complex nonlinear longitudinal dynamics of the FAHV. Secondly, based on the obtained polytopic LPV model, the flight envelope is divided into four smaller subregions, and four gain-scheduled controllers are designed for these parameter subregions. Then, by the defined switching characteristic function, these gain-scheduled controllers are switched in order to guarantee the closed-loop FAHV system to be asymptotically stable and satisfy a given tracking error performance criterion. The condition of gain-scheduled switching controller synthesis is given in terms of linear matrix inequalities （LMIs） which can be easily solved by using standard software packages. Finally, simulation results show the effectiveness of the presented method.