Stability analysis and stabilization of wireless networked control systems based on deadband control scheduling

The stability analysis and stabilization problems of the wireless networked control systems（WNCSs） with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.     

Robust tracking control design for a flexible air-breathing hypersonic vehicle简

A nonlinear robust controller was presented to improve the tracking control performance of a flexible air-breathing hypersonic vehicle （AHV） which is subjected to system parametric uncertainties and unknown additive time-varying disturbances. The longitudinal dynamic model for the flexible AHV was used for the control development. High-gain observers were designed to compensate for the system uncertainties and additive disturbances. Small gain theorem and Lyapunov based stability analysis were utilized to prove the stability of the closed loop system. Locally uniformly ultimately bounded tracking of the vehicle＇s velocity, altitude and attack angle were achieved under aeroelastic effects, system parametric uncertainties and unknown additive disturbances. Matlab/Simulink simulation results were provided to validate the robustness of the proposed control design. The simulation results demonstrate that the tracking errors stay in a small region around zero.     

Adaptive robust controller for supercavitating vehicle using guaranteed cost theory

Regarding to the problems that supercavitating vehicles have special characteristics from traditional underwater vehicles,robust control problem was studied in this paper for the supercavitating vehicles with mismatched uncertainties.The nonlinear dynamic model was improved.For mismatched uncertainties,the robust sliding mode function was proposed based on guaranteed cost theory,and sufficient condition for the existence was given in terms of linear matrix inequality (LMI).Continuous sliding mode controller was designed,with an adaptive technology which was used to estimate the unknown upper bound of mismatched uncertainties.Meanwhile,upper bound of parameter uncertainties was not required.Simulation results demonstrated that the system responds rapidly and has good robust stability.Due to application of guaranteed cost theory,the controlled plant is not only stable but also guarantees an adequate level of performance.Therefore,it provides theoretical references for further study on control problems of supercavitating vehicles.     

On guaranteed cost control of linear systems with input saturation

This work studies the problem of control design for linear systems with input saturation.It is well known that integral quadratic constraints（IQC） can be used to describe input saturation and that the use of IQC in analysis can lead to less conservative performance bound and larger domain of attraction.In this work,it is shown that a class of commonly used IQCs may not help in control synthesis.That is,the use of these IQCs does not enlarge the guaranteed domain of performance for synthesis.     

Robust H∞ directional control for a sampled-data autonomous airship

A robust H∞ directional controller for a sampled-data autonomous airship with polytopic parameter uncertainties was proposed. By input delay approach, the linearized airship model was transformed into a continuous-time system with time-varying delay. Sufficient conditions were then established based on the constructed Lyapunov-Krasovskii functional, which guarantee that the system is mean-square exponentially stable with H∞ performance. The desired controller can be obtained by solving the obtained conditions. Simulation results show that guaranteed minimum H∞ performance γ=1.4037 and fast response of attitude for sampled-data autonomous airship are achieved in spite of the existence of parameter uncertainties.     

Soft sensor for ratio of soda to aluminate based on PCA-RBF multiple network

Based on principal component analysis, a multiple neural network was proposed. The principal component analysis was firstly used to reorganize the input variables and eliminate the correlativity. Then the reorganized variables were divided into 2 groups according to the original information and 2 corresponding neural networks were established. A radial basis function network was used to depict the relationship between the output variables and the first group input variables which contain main original information. An other single-layer neural network model was used to compensate the error between the output of radial basis function network and the actual output variables. At last, The multiple network was used as soft sensor for the ratio of soda to aluminate in the process of high-pressure digestion of alumina. Simulation of industry application data shows that the prediction error of the model is less than3%, and the model has good generalization ability.     

Robust reliable H_∞ control for a class of uncertain time-delay systems

This paper deals with the problem of robust reliable H∞ control for a class of uncertain nonlinear systems with time-varying delays and actuator failures. The uncertainties in the system are norm-bounded and time-varying. Based on Lyapunov methods, a sufficient condition on quadratic stabilization independent of delay is obtained. With the help of LMIs (linear matrix inequalities) approaches, a linear state feedback controller is designed to quadratically stabilize the given systems with a H∞ performance constraint of disturbance attenuation for all admissible uncertainties and all actuator failures occurred within the prespecified subset. A numerical example is given to demonstrate the effect of the proposed design approach.     

Optimal Design of Materials for DJMP Based on Genetic Algorithm

The genetic algorithm was used in optimal design of deep jet method pile. The cost of deep jet method pile in one unit area of foundation was taken as the objective function . All tire restrains were listed following the corresponding specification. Suggestions were proposed and the modified. The real-coded Genetic Algorithm was given to deal with the problems of excessive computational cost and premature convergence. Software system of optimal design of deep jet method pile was developed.     

Convergence of shape optimization calculations of mechanical components using adaptive biological growth and iterative finite element methods

Shape optimization of mechanical components is one of the issues that have been considered in recent years. Different methods were presented such as adaptive biological for reducing costs and increasing accuracy. The effects of step factor, the number of control points and the definition way of control points coordinates in convergence rate were studied. A code was written using ANSYS Parametric Design Language (APDL) which receives the studied parameters as input and obtains the optimum shape for the components. The results show that for achieving successful optimization, step factor should be in a specific range. It is found that the use of any coordinate system in defining control points coordinates and selection of any direction for stimulus vector of algorithm will also result in optimum shape. Furthermore, by increasing the number of control points, some non-uniformities are created in the studied boundary. Achieving acceptable accuracy seems impossible due to the creation of saw form at the studied boundary which is called "saw position".     

Decentralized H∞ state feedback control for large-scaleinterconnected uncertain systems with multiple delays

Decentralized H∞ control was studied for a class of interconnected uncertain systems with multiple delays in the state and control and time varying but norm-bounded parametric uncertainties. A sufficient condition which makes the closed-loop system decentralized asymptotically stable with H∞ performance was derived based on Lyapunov stability theorem. This condition is expressed as the solvability problem of linear matrix inequalities. The method overcomes the limitations of the existing algebraic Riccati equation method. Finally, a numerical example was given to demonstrate the design procedure for the decentralized H∞ state feedback controller.     

Effect analysis of friction and damping on anti-backlash gear based on dynamics model with time-varying mesh stiffness

A nonlinear model of anti-backlash gear with time-varying friction and mesh stiffness was proposed for the further study on dynamic characteristics of anti-backlash gear. In order to improve the model precision, applied force analysis was completed in detail, and single or double tooth meshing states of two gear pairs at any timing were determined according to the meshing characteristic of anti-backlash gear. The influences of friction and variations of damping ratio on dynamic transmission error were analyzed finally by numerical calculation and the results show that anti-backlash gear can increase the composite mesh stiffness comparing with the mesh stiffness of the normal gear pair. At the pitch points where the frictions change their signs, additional impulsive effects are observed. The width of impulsive in the same value of center frequency is wider than that without friction, and the amplitude is lower. When gear pairs mesh in and out, damping can reduce the vibration and impact.     

A novel stabilization approach for small signal disturbance of power system with time-varying delay

Small signal instability may cause severe accidents for power system if it can not be dear correctly and timely. How to maintain power system stable under small signal disturbance is a big challenge for power system operators and dispatchers. Time delay existing in signal transmission process makes the problem more complex. Conventional eigenvalue analysis method neglects time delay influence and can not precisely describe power system dynamic behaviors. In this work, a modified small signal stability model considering time varying delay influence was constructed and a new time delay controller was proposed to stabilize power system under disturbance. By Lyapunov-Krasovskii function, the control law in the form of nonlinear matrix inequality （NLMI） was derived. Considering synthesis method limitation for time delay controller at present, both parameter adjustment method by using linear matrix inequality （LMI） solver and iteration searching method by solving nonlinear minimization problem were suggested to design the controller. Simulation tests were carried out on synchronous-machine infinite-bus power system. Satisfactory test results verify the correctness of the proposed model and the feasibility of the stabilization approach.     

Recent developments on applications of sequential loop closing and diagonal dominance control schemes to industrial multivariable system

With a focus on an industrial multivariable system, two subsystems including the flow and the level outputs are analysed and controlled, which have applicability in both real and academic environments. In such a case, at first, each subsystem is distinctively represented by its model, since the outcomes point out that the chosen models have the same behavior as corresponding ones. Then, the industrial multivariable system and its presentation are achieved in line with the integration of these subsystems, since the interaction between them can not actually be ignored. To analyze the interaction presented, the Gershgorin bands need to be acquired, where the results are used to modify the system parameters to appropriate values. Subsequently, in the view of modeling results, the control concept in two different techniques including sequential loop closing control （SLCC） scheme and diagonal dominance control （DDC） schemes is proposed to implement on the system through the Profibus network, as long as the OPC （OLE for process control） server is utilized to communicate between the control schemes presented and the multivariable system. The real test scenarios are carried out and the corresponding outcomes in their present forms are acquired. In the same way, the proposed control schemes results are compared with each other, where the real consequences verify the validity of them in the field of the presented industrial multivariable system control.     

Nonlinear adaptive optimal control for vehicle handling improvement through steer-by-wire system简

A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel, based on the nonlinear adaptive optimal control （NAOC）. A nonlinear 4-DOF model was initially developed, then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers. Then a simplified model was developed for steering system. The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions. Moreover, the hardware in the loop method was implemented to prove the controller ability in realistic conditions. Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.     

Adaptive robust motion trajectory tracking control of pneumatic cylinders

High-accuracy motion trajectory tracking control of a pneumatic cylinder driven by a proportional directional control valve was considered. A mathematical model of the system was developed firstly. Due to the time-varying friction force in the cylinder, unmodeled dynamics, and unknown disturbances, there exist large extent of parametric uncertainties and rather severe uncertain nonlinearities in the pneumatic system. To deal with these uncertainties effectively, an adaptive robust controller was constructed in this work. The proposed controller employs on-line recursive least squares estimation （RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodeled dynamics and disturbances. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology was applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping was used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Extensive experimental results were presented to illustrate the excellent achievable performance of the proposed controller and performance robustness to the load variation and sudden disturbance.     

Dynamic estimation and reliability control of quality assurance for bored piles简

A systematic method was proposed to estimate the occurrence probability of defective piles （OPDP） from a site according to quality assurance inspection. The OPDP was firstly suggested as the criterion to weight the performance of a pile foundation. Its prior distribution and updating distribution were deduced to follow Beta distributions. To calibrate the OPDP, a dynamic estimation model was established according to the relationships between prior mean and variance and updating mean and variance. Finally, a reliability-control method dealing with uncertainties arising from quality assurance inspection was formalized to judge whether all the bored piles from a site can be accepted. It is exemplified that the OPDP can be substantially improved when more definite prior information and sampling formation become available. For the example studied herein, the Bayesian estimator of updating variance for OPDP is reduced from 0.0037 to 0.0014 for the first inspection, from 0.0014 to 0.0009 for the second inspection, and with less uncertainty by incorporating experience information.     

Dynamic inverse control of feedback linearization in ballistic correction based on nose cone swinging

It is a complicated nonlinear controlling problem to conduct a two-dimensional trajectory correction of rockets.By establishing the aerodynamic correction force mathematical model of rockets on nose cone swinging,the linear control is realized by the dynamic inverse nonlinear controlling theory and the three-time-scale separation method.The control ability and the simulation results are also tested and verified.The results show that the output responses of system track the expected curve well and the error is controlled in a given margin.The maximum correction is about ±314 m in the lengthwise direction and ±1 212 m in the crosswise direction from the moment of 5 s to the drop-point time when the angle of fire is 55°.Thus,based on the dynamic inverse control of feedback linearization,the trajectory correction capability of nose cone swinging can satisfy the requirements of two-dimensional ballistic correction,and the validity and effectiveness of the method are proved.     

Dynamic formation control for autonomous underwater vehicles简

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles （AUVs） to collaborate with each other. In this work, a dynamic formation model was proposed, in which several algorithms were developed for the complex underwater environment. Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes. Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles. Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation. The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated. Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness, even with a concave obstacle. It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.     

Decoupling control and zero dynamics stabilization for shunt hybrid active power filter

An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.