Vibration Control of the Rail Grinding Vehicle with Abrasive Belt Based on Structural Optimization and Lightweight Design

As a new grinding and maintenance technology,rail belt grinding shows significant advantages in many applications The dynamic characteristics of the rail belt grinding vehicle largely determines its grinding performance and service life.In order to explore the vibration control method of the rail grinding vehicle with abrasive belt,the vibration response changes in structural optimization and lightweight design are respectively analyzed through transient response and random vibration simulations in this paper.Firstly,the transient response simulation analysis of the rail grinding vehicle with abrasive belt is carried out under operating conditions and non-operating conditions.Secondly,the vibration control of the grinding vehicle is implemented by setting vibration isolation elements,optimizing the structure,and increasing damping.Thirdly,in order to further explore the dynamic characteristics of the rail grinding vehicle,the random vibration simulation analysis of the grinding vehicle is carried out under the condition of the horizontal irregularity of the American AAR6 track.Finally,by replacing the Q235 steel frame material with 7075 aluminum alloy and LA43M magnesium alloy,both vibration control and lightweight design can be achieved simultaneously.The results of transient dynamic response analysis show that the acceleration of most positions in the two working conditions exceeds the standard value in GB/T 17426-1998 standard.By optimizing the structure of the grinding vehicle in three ways,the average vibration acceleration of the whole car is reduced by about 55.1%from 15.6 m/s^(2) to 7.0 m/s^(2).The results of random vibration analysis show that the grinding vehicle with Q235 steel frame does not meet the safety conditions of 3σ.By changing frame material,the maximum vibration stress of the vehicle can be reduced from 240.7 MPa to 160.0 MPa and the weight of the grinding vehicle is reduced by about 21.7%from 1500 kg to 1175 kg.The modal analysis results indicate that the vibration control of the grinding vehicle can be realized by optimizing the structure and replacing the materials with lower stiffness under the premise of ensuring the overall strength.The study provides the basis for the development of lightweight,diversified and efficient rail grinding equipment.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Review of Design and Control Optimization of Axial Flux PMSM in Renewable-energy Applications

Axial flux permanent magnet synchronous motors(AFPMSMs)have been widely used in wind-power generation,electric vehicles,aircraft,and other renewable-energy applications owing to their high power density,operating efficiency,and integrability.To facilitate comprehensive research on AFPMSM,this article reviews the developments in the research on the design and control optimization of AFPMSMs.First,the basic topologies of AFPMSMs are introduced and classified.Second,the key points of the design optimization of core and coreless AFPMSMs are summarized from the aspects of parameter design,structure design,and material optimization.Third,because efficiency improvement is an issue that needs to be addressed when AFPMSMs are applied to electric or other vehicles,the development status of efficiency-optimization control strategies is reviewed.Moreover,control strategies proposed to suppress torque ripple caused by the small inductance of disc coreless permanent magnet synchronous motors(DCPMSMs)are summarized.An overview of the rotor-synchronization control strategies for disc contra-rotating permanent magnet synchronous motors(CRPMSMs)is presented.Finally,the current difficulties and development trends revealed in this review are discussed.

Design methodology of a mini-missile considering flight performance and guidance precision

The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.

MODELING, VALIDATION AND OPTIMAL DESIGN OF THE CLAMPING FORCE CONTROL VALVE USED IN CONTINUOUSLY VARIABLE TRANSMISSION

Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.

Thermal Design and Optimization of Heat Pipe Radiator for Satellites

Satellite＇s thermal control subsystem （TCS） has to maintain components and structure within their specified temperature limits during satellite service life. TCS designers have to face the challenge of reducing both the weight of the system and required heater power while keeping components temperature within their design range. For a space based heat pipe radiator system, several researchers have published different approaches to reach such goal. This paper presents a thermal design and optimization of a heat pipe radiator applied to a practical engineering design application. For this study, a prospective communication satellite payload panel with applied passive thermal control techniques was considered. The thermal passive techniques used in this design mainly include multilayer insulation （MLI） blankets, optical solar reflectors （OSR）, selected thermal coatings, interface fillers and constant conductance heat pipes. The heat pipe network is comprised of some heat pipes embedded in the panel and some mounted on inner surface of the panel. Embedded heat pipes are placed under high heat dissipation equipments and their size is fixed; minimum weight of the radiator is achieved by a minimum weight of the mounted heat pipes. Hence, size of the mounted heat pipes is optimized. A thermal model was built and parameterized for transient thermal analysis and optimization. Temperature requirements of components in both worst case conditions （Hot case and cold case） were satisfied under optimal sizing of mounted heat pipes.

On the Design of Optimal Feedback Control for Systems of Second Order

A difficult but important problem in optimal control theory is the design of an optimal feedback control, i.e., the design of an optimal control as function of the phase (state) coordinates [1,2]. This problem can be solved not often. We study here the autonomous nonlinear system of second order in general form. The constraints imposed on the control input can depend on the phase (state) coordinates of the system. The goal of the control is to maximize or minimize one phase coordinate of the considered system while other takes a prescribed in advance value. In the literature, optimal control problems for the systems of second order are most frequently associated with driving both phase coordinates to a prescribed in advance state. In this statement of the problem, the optimal control feedback can be designed only for special kind of systems. In our statement of the problem, an optimal control can be designed as function of the state coordinates for more general kind of the systems. The problem of maximization or minimization of the swing amplitude is considered explicitly as an example. Simulation results are presented.

Policy Iteration for Optimal Control of Discrete-Time Time-Varying Nonlinear Systems

Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.

Series-parallel Hybrid Vehicle Control Strategy Design and Optimization Using Real-valued Genetic Algorithm

Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of hybrid electric vehicles.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Adaptive optimization of agile organization of command and control resource

Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net （CPN） model of AOC2R and then searches for the result by ant colony optimization （ACO） algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.

Adaptive Sliding-Mode Control of an Automotive Electronic Throttle in the Presence of Input Saturation Constraint

In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and input saturation constraints,an adaptive sliding-mode tracking control strategy for an ET is presented. Compared with the existing control strategies for an ET, input saturation constraints and parameter uncertainties are adequately considered in the proposed control strategy. At first, the nonlinear dynamic model for control of an ET is described. According to the dynamical model, the nonlinear adaptive sliding-mode tracking control method is presented,where parameter adaptive laws and auxiliary design system are employed. Parameter adaptive law is given to estimate the unknown parameter with an ET. An auxiliary system is designed,and its state is utilized in the tracking control method to handle the input saturation. Stability proof and analysis of the adaptive sliding-mode control method is performed by using Lyapunov stability theory. Finally, the reliability and feasibility of the proposed control strategy are evaluated by computer simulation.Simulation research shows that the proposed sliding-mode control strategy can provide good control performance for an ET.

Research on Mechanisms of Steam Breakthrough and Profile Control Design for Steam Soaking Well

Scaled physical model tests for steam breakthrough were conducted based on the analysis of mechanisms and influence factors of steam breakthrough. Physical simulation results showed that at the initial steam breakthrough, preferential flow channels were formed in narrow sand packs and most residual oil left in these channels was immobile. This shortened the steam breakthrough time of follow-up steam flooding and decreased the increment of oil recovery efficiency. Steam breakthrough occurred easily for a smaller producer-injector spacing, and a bigger difference in physical properties between fluids and rock. Steam breakthrough is more likely to occur at a larger formation permeability （k）, greater steam displacement velocity （u） and smaller producer-injector spacing （L）. Steam breakthrough time is a function of the parameter group （uk/L）, i.e. tb=3.2151 （uk/L）^-0.5142. A non piston-like displacement model was built based on steam breakthrough observation for a steam stimulated well in the Jinglou Oilfield, Henan Oilfield Company. The steam volume swept in different directions could be obtained from inter-well permeability capacity and breakthrough angle, and the steam swept pore volume （SSPV） was also determined. Numerical simulation showed that steam sweep efficiency reached its peak value when a slug of profile control agent （slug size 10%-15% SSPV） was set at one half of the inter-well spacing. Field test with 12.5% SSPV of profile control agents in the Jinglou Oilfield achieved success in sealing breakthrough channels and good production performance of adjacent producers.

Design of Retarded Fractional Delay Differential Systems Using the Method of Inequalities

Methods based on numerical optimization are useful and effective in the design of control systems. This paper describes the design of retarded fractional delay differential systems （RFDDSs） by the method of inequalities, in which the design problem is formulated so that it is suitable for solution by numerical methods. Zakian＇s original formulation, which was first proposed in connection with rational systems, is extended to the case of RFDDSs. In making the use of this formulation possible for RFDDSs, the associated stability problems are resolved by using the stability test and the numerical algorithm for computing the abscissa of stability recently developed by the authors. During the design process, the time responses are obtained by a known method for the numerical inversion of Laplace transforms. Two numerical examples are given, where fractional controllers are designed for a time-delay and a heat-conduction plants.

Optimizing Designed Variable Speed Control Moment Gyroscopes with Variable Skew Angle

Large torque can be output by the single gimbal control momentum gyroscope (SGCMG) based on the principle of the gyroscopic precession. However, the singularity is a major obstacle to successfully implement the task of the attitude control. The singularity can be avoided by the additional variable flywheel speed of variable speed control moment gyroscopes (VSCMG). Unfortunately, some kind of singularity cannot be effectively avoided. Consequently, the output toque can be only supported by the reaction torque of the flywheel when the singularity is encountered, and the consume power that is determined by the flywheel speed and reaction torque can be greatly increased when the flywheel spin rate over one thousand revolutions per minute. In this paper, the pyramid configuration with variable skew angle of the VSCMG is considered. A new steering law for the VSCMG with variable skew angle is proposed. The singularity that cannot be avoided by the varying flywheel speed can be effectively avoided with assisting of varying the skew angle. Consequently, the requirement of flywheel torque can be reduced. At last, the optimizing VSCMG with variable skew angle can be cast as a multi-objective function with multi-constraints. The particle swarm optimization method is used to solve the optimizing problem. In summary, the VSCMG with variable skew angle can be redesigned with considering of the singularity avoidance and minimizing system power.

Optimal design of dynamic and control performance for planar manipulator

A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which made it possible to obtain good dynamic and control performances just through mechanism optimization.Based on the idea of design for control(DFC),a novel kind of multi-objective optimization model was proposed.There were three optimization objectives:the index of inertia,the index describing the dynamic coupling effects and the global condition number.Other indexes to characterize the designing requirements such as the velocity of end-effector,the workspace size,and the first mode natural frequency were regarded as the constraints.The cross-section area and length of the linkages were chosen as the design variables.NSGA-II algorithm was introduced to solve this complex multi-objective optimization problem.Additional criteria from engineering experience were incorporated into the selecting of final parameters among the obtained Pareto solution sets.Finally,experiments were performed to validate the linear dynamic structure and control performances of the optimized mechanisms.A new expression for measuring the dynamic coupling degree with clear physical meaning was proposed.The results show that the optimized mechanism has an approximate decoupled dynamics structure,and each active joint can be regarded as a linear SISO system.The control performances of the linear and nonlinear controllers were also compared.It can be concluded that the optimized mechanism can achieve good control performance only using a linear controller.

Data Driven Vibration Control:A

With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic communities.Input shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC methods.It convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration separately.Based on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of DDVC.By doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.

Design of Guided Air Ammunition's Optimal Guidance Law

Some long distance air ammunition can be used to attack large still target. According to this character and according to the mathematical description of target-missile relative motion built by the message supplied by the strapdown inertial navigation system/global position system （SINS/GPS） of air ammunition, optimal guidance law is designed by applying optimal control theory. The simulation is provided to indicate that when the air ammunition reaches the target, its line-of-sight （LOS） and LOS angular rate can nearly equal zero. So the air ammunition can get good terminal attitude, and the air ammunition reaches the target at the expected velocity and heading.

Method of Designing Missile Controller Based on Multi-Objective Opti mization

A method of designing robust controller based on genetic algorithm is presented in order to overcome the drawback of manual modification and trial in designing the control system of missile. Specification functions which reflect the dynamic performance in time domain and robustness in frequency domain are presented, then dynamic/static performance, control cost and robust stability are incorporated into a multi-objective optimization problem. Genetic algorithm is used to solve the problem and achieve the optimal controller directly. Simulation results show that the controller provides a good stability and offers a good dynamic performance in a large flight envelope. The results also validate the effectiveness of the method.