Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming

Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots. The performance indexes used in optimal trajectory planning are classified into two main categories: optimum traveling time and optimum mechanical energy of the actuators. The current trajectory planning algorithms are designed based on one of the above two performance indexes. So far, there have been few planning algorithms designed to satisfy two performance indexes simultaneously. On the other hand, some deficiencies arise in the existing integrated optimi2ation algorithms of trajectory planning. In order to overcome those deficiencies, the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators. In the algorithm, two object functions are designed based on the specific weight coefficient method and ' ideal point strategy. Moreover, based on the features of optimization problem, the intensified evolutionary programming is proposed to solve the corresponding optimization model. Especially, for the Stanford Robot,the high-quality solutions are found at a lower cost.

Integrated Optimization of Structure and Control Parameters for the Height Control System of a Vertical Spindle Cotton Picker

Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how to realize a precise height control of the cotton picker is a crucial issue to be solved.The objective of this study is to design a height control system to avoid the collision.To design it,the mathematical models are established first.Then a multi-objective optimization model represented by structure parameters and control parameters is proposed to take the pressure of chamber without piston,response time and displacement error of the height control system as the opti-mization objectives.An integrated optimization approach that combines optimization via simulation,particle swarm optimization and simulated annealing is proposed to solve the model.Simulation and experimental test results show that the proposed integrated optimization approach can not only reduce the pressure of chamber without piston,but also decrease the response time and displacement error of the height control system.

Three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants

In order to explore the potential of profit margin improvement,a novel three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants is proposed and evaluated.A decoupling strategy is proposed for the solution of the three-scale model,which uses our previously proposed reactor scale model for operation optimization and then transfers the obtained results as a parameter table in the joint MILP optimization of plant-supply chain scale for cyclic scheduling.This optimization framework simplifies the fundamental mixed-integer nonlinear programming(MINLP)into several sub-models,and improves the interpretability and extendibility.In the evaluation of an industrial case,a profit increase at a percentage of 3.25%is attained in optimization compared to the practical operations.Further sensitivity analysis is carried out for strategy evolving study when price policy,supply chain,and production requirement parameters are varied.These results could provide useful suggestions for petrochemical enterprises on thermal cracking production.

Integrated Electrode-Electrolyte Optimization to Manufacture a Real-Life Applicable Aqueous Supercapacitor with Record-Breaking Lifespan

Aqueous supercapacitors(SCs)have been regarded as a promising candidate for commercial energy storage device due to their superior safety,low cost,and environmental benignity.Unfortunately,an age-old challenge of achieving both long electrode lifespan and qualified energy-storage property blocks their practical application.Herein,we develop an electrode-electrolyte integrated optimization strategy to fulfill the real-life device requirements.Electrode optimization simultaneously regulates the nanomorphology and surface chemistry of the tungsten oxide anode,resulting in superior electrochemical performance given by an ideal“bird-nest”structure with optimal oxygen vacancy status;the anodes interact with and are protected from dissolution and structural collapse by the rationally designed hybrid electrolyte with optimized pH and facilitated cation desorption behavior.Collaboratively,a record-breaking durability of no capacitive decay after 250000 cycles is achieved.On the basis of this integrated optimization,the first aqueous pouch SCs with real-life practicability were manufactured by a soft-package encapsulation technique,which can steadily power commercial 3 C products such as tablets and smartphones and maintain safely working against extreme conditions.This work demonstrates the possibility of using aqueous energy storage devices with enhanced safety and lower cost to replace the commercial organic counterparts for wide range of daily applications.

Integrated optimization on aerodynamics-structure coupling and flight stability of a large airplane in preliminary design

The preliminary phase is significant during the whole design process of a large airplane because of its enormous potential in enhancing the overall performance. However, classical sequential designs can hardly adapt to modern airplanes, due to their repeated iterations, long periods, and massive computational burdens. Multidisciplinary analysis and optimization demonstrates the capability to tackle such complex design issues. In this paper, an integrated optimization method for the preliminary design of a large airplane is proposed, accounting for aerodynamics, structure, and stability. Aeroelastic responses are computed by a rapid three-dimensional flight load analysis method combining the high-order panel method and the structural elasticity correction. The flow field is determined by the viscous/inviscid iteration method, and the cruise stability is evaluated by the linear small-disturbance theory. Parametric optimization is carried out using genetic algorithm to seek the minimal weight of a simplified plate-beam wing structure in the cruise trim condition subject to aeroelastic, aerodynamic, and stability constraints, and the optimal wing geometry shape, front/rear spar positions, and structural sizes are obtained simultaneously. To reduce the computational burden of the static aeroelasticity analysis in the optimization process, the Kriging method is employed to predict aerodynamic influence coefficient matrices of different aerodynamic shapes. The multidisciplinary analyses guarantee computational accuracy and efficiency, and the integrated optimization considers the coupling effect sufficiently between different disciplines to improve the overall performance, avoiding the limitations of sequential approaches utilized currently.

Energy saving design of the machining unit of hobbing machine tool with integrated optimization

The machining unit of hobbing machine tool accounts for a large portion of the energy consumption during the operating phase.The optimization design is a practical means of energy saving and can reduce energy consumption essentially.However,this issue has rarely been discussed in depth in previous research.A comprehensive function of energy consumption of the machining unit is built to address this problem.Surrogate models are established by using effective fitting methods.An integrated optimization model for reducing tool displacement and energy consumption is developed on the basis of the energy consumption function and surrogate models,and the parameters of the motor and structure are considered simultaneously.Results show that the energy consumption and tool displacement of the machining unit are reduced,indicating that energy saving is achieved and the machining accuracy is guaranteed.The influence of optimization variables on the objectives is analyzed to inform the design.

Integrated optimization of multiproduct multiperiod transportation and inventory under a carbon cap constraint for online retailers

This study aims to solve the problem of multiproduct multiperiod integrated transportation and inventory optimization for online retailers.A carbon cap constraint and multitype of capacitated trucks are simultaneously incorporated into the proposed mixed-integer program.A simulated annealing(SA)algorithm is designed.CPLEX 12.9.0 is used to solve the submodel obtained from the neighbourhood search and is also used to get the optimal solutions for instances.Experimental results show that the simulated annealing algorithm can find satisfactory solutions within a reasonable time.When the problem size increases,the growth of the computational time of the SA algorithm is significantly smaller than that of the CPLEX.A sensitivity analysis for the carbon cap is also conducted.The results indicate that if the carbon cap is gradually tightened,the total cost increases first with a gentle slope,and then with a remarkable slope,same as for the total number of trucks used;the total carbon emissions first decrease with a gentle slope,and then decline with a significant slope.When the carbon cap is strict,only a few different types of trucks will be considered.The percentage changes of the total cost increase and the total carbon emission reduction are also compared.When the allowed carbon emissions are gradually reduced,situation of a higher amount of carbon emission reduction and a lower amount of cost increase can be achieved.Additionally,using multiple types of trucks in the integrated optimization of transportation and inventory decisions can achieve greater cost savings with lower increments of carbon emission.

Multidisciplinary Design Optimization of A Human Occupied Vehicle Based on Bi-Level Integrated System Collaborative Optimization

The design of Human Occupied Vehicle （HOV） is a typical multidisciplinary problem, but heavily dependent on the experience of naval architects at present engineering design. In order to relieve the experience dependence and improve the design, a new Multidisciplinary Design Optimization （MDO） method ＂Bi-Level Integrated System Collaborative Optimization （BLISCO）＂ is applied to the conceptual design of an HOV, which consists of hull module, resistance module, energy module, structure module, weight module, and the stability module. This design problem is defined by 21 design variables and 23 constraints, and its objective is to maximize the ratio of payload to weight. The results show that the general performance of the HOV can be greatly improved by BLISCO.

Scheduling optimization of task allocation in integrated manufacturing system based on task decomposition

How to deal with the collaboration between task decomposition and task scheduling is the key problem of the integrated manufacturing system for complex products. With the development of manufacturing technology, we can probe a new way to solve this problem. Firstly, a new method for task granularity quantitative analysis is put forward, which can precisely evaluate the task granularity of complex product cooperation workflow in the integrated manufacturing system, on the above basis; this method is used to guide the coarse-grained task decomposition and recombine the subtasks with low cohesion coefficient. Then, a multi-objective optimieation model and an algorithm are set up for the scheduling optimization of task scheduling. Finally, the application feasibility of the model and algorithm is ultimately validated through an application case study.

The Integrated System of Aerial Photogrammetry and Tower Locations Optimization for Transmission Lines

This paper describes the functions and the features of the integrated system of aerial survey and tower locations optimization for transmission lines, which includes all stages from data acquisition, data transmission and data processing to automatic optimization of the tower locations and drawing. The paper also briefly describes the economic benefit gained from this system, and finally proposes the directions of the future development for this system.

A new approach for flow simulation in complex hydraulic fracture morphology and its application:Fracture connection element method

Efficient flow simulation and optimization methods of hydraulic fracture morphology in unconventional reservoirs are effective ways to enhance oil/gas recovery.Based on the connection element method(CEM)and distribution of stimulated reservoir volume,the complex hydraulic fracture morphology was accurately described using heterogeneous node connection system.Then a new fracture connection element method(FCEM)for fluid flow in stimulated unconventional reservoirs with complex hydraulic fracture morphology was proposed.In the proposed FCEM,the arrangement of dense nodes in the stimulated area and sparse nodes in the unstimulated area ensures the calculation accuracy and efficiency.The key parameter,transmissibility,was also modified according to the strong heterogeneity of stimulated reservoirs.The finite difference and semi-analytical tracking were used to accurately solve the pressure and saturation distribution between nodes.The FCEM is validated by comparing with traditional numerical simulation method,and the results show that the bottom hole pressure simulated by the FCEM is consistent with the results from traditional numerical simulation method,and the matching rate is larger than 95%.The proposed FCEM was also used in the optimization of fracturing parameters by coupling the hydraulic fracture propagation method and intelligent optimization algorithm.The integrated intelligent optimization approach for multi-parameters,such as perforation number,perforation location,and displacement in hydraulic fracturing is proposed.The proposed approach was applied in a shale gas reservoir,and the result shows that the optimized perforation location and morphology distribution are related to the distribution of porosity/permeability.When the perforation location and displacement are optimized with the same fracture number,NPV increases by 70.58%,which greatly improves the economic benefits of unconventional reservoirs.This work provides a new way for flow simulation and optimization of hydraulic fracture morphology of multi-fractured horizontal wells in unconventional reservoirs.

Novel Block Chain Technique for Data Privacy and Access Anonymity in Smart Healthcare

The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internetand computing resources. In recent years, many more IoT applications have beenextensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstaclesfaced by the extensive acceptance and usage of these emerging technologies aresecurity and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, theexisting system has issues with specific security issues, privacy-preserving rate,information loss, etc. Hence, the overall system performance is reduced significantly. A unique blockchain-based technique is proposed to improve anonymityin terms of data access and data privacy to overcome the above-mentioned issues.Initially, the registration phase is done for the device and the user. After that, theGeo-Location and IP Address values collected during registration are convertedinto Hash values using Adler 32 hashing algorithm, and the private and publickeys are generated using the key generation centre. Then the authentication is performed through login. The user then submits a request to the blockchain server,which redirects the request to the associated IoT device in order to obtain thesensed IoT data. The detected data is anonymized in the device and stored inthe cloud server using the Linear Scaling based Rider Optimization algorithmwith integrated KL Anonymity (LSR-KLA) approach. After that, the Time-stamp-based Public and Private Key Schnorr Signature (TSPP-SS) mechanismis used to permit the authorized user to access the data, and the blockchain servertracks the entire transaction. The experimental findings showed that the proposedLSR-KLA and TSPP-SS technique provides better performance in terms of higherprivacy-preserving rate, lower information loss, execution time, and Central Processing Unit (CPU) usage than the existing techniques. Thus, the proposed method allows for better data privacy in the smart healthcare network.

Integrated batteries layout and structural topology optimization for a solar-powered drone

The purpose of this paper is to demonstrate an integrated optimization scheme for a solar-powered drone structure.Consider a primary beam in the wing of large aspect ratio,where 100 lithium batteries are assembled.In the proposed integrated optimization,the batteries are considered here as parts of the load-carrying structure.The corresponding mechanical behaviors are simulated in the structural design and described with super-elements.The batteries layout and the structural topology are then introduced as mixed design variables and optimized simultaneously to achieve an accordant load-carrying path.Geometrical nonlinearity is considered due to the large deformation.Different periodic structural configurations are tested in the optimization in order to meet the structural manufacturing and assembly convenience.The optimized designs are rebuilt and tested in different load cases.Maintaining the same structural weight,the global mechanical performances are improved greatly compared with the initial design.

Review:Research Progress for Electric Vehicle Hub Motor Driving Technology

Due to high efficiency,high controllability,high integration,lightweight,and other advantages,electric vehicle with hub motor driving technology has become an emerging trend of chassis technology.This paper concludes the current state⁃of⁃the⁃art of hub motor drive technologies.Firstly,it summarizes recent hub motor drive products and makes suggestions for hub motor drive schemes in different application scenarios.Then research on hub motor drive key technologies such as integrated design,thermal optimization,lightweight,and intensity optimization is investigated.Considering the high response accuracy and zero delay characteristic of hub motor driving system combined with advanced distributed dynamics control technology that can further improve vehicle performance,this paper also analyzes existing chassis dynamics control technologies of hub motor driving system.Considering the development trend of vehicle electrification,intelligentization,network connection,and current research,this paper makes some forecasts for hub motor drive technologies development in the conclusion.

An Innovative Bias-Correction Approach to CMA-GD Hourly Quantitative Precipitation Forecasts

This paper proposes a simple and powerful optimal integration(OPI)method for improving hourly quantitative precipitation forecasts(QPFs,0-24 h)of a single-model by integrating the benefits of different biascorrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration(CMA).Three techniques are used to generate multi-method calibrated members for OPI:deep neural network(DNN),frequency-matching(FM),and optimal threat score(OTS).The results are as follows:(1)The QPF using DNN follows the basic physical patterns of CMA-GD.Despite providing superior improvements for clear-rainy and weak precipitation,DNN cannot improve the predictions for severe precipitation,while OTS can significantly strengthen these predictions.As a result,DNN and OTS are the optimal members to be incorporated into OPI.(2)Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation.Compared with the CMA-GD,OPI improves the TS by 2.5%,5.4%,7.8%,8.3%,and 6.1%for QPFs from clear-rainy to rainstorms in the verification dataset.Moreover,OPI shows good stability in the test dataset.(3)It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation.Therefore,improvements in predicting severe precipitation using this method should be further realized by improving the numerical model's forecasting capability.

Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

Finite element（FE） is a powerful tool and has been applied by investigators to real-time hybrid simulations（RTHSs）. This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time（TET） decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method（CDM）, the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ（λ = 4） method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

DISOPE distributed model predictive control of cascade systems with network communication

A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.

Ice-Class Propeller Strength and Integrity Evaluation Using Unified Polar ClassURI3 Rules

A systematic method was developed for ice-class propeller modeling,performance estimation,strength and integrity evaluation and optimization.To estimate the impact of sea ice on the propeller structure,URI3 rules,established by the International Association of Classification Societies in 2007,were applied for ice loading calculations.An R-class propeller(a type of ice-class propeller)was utilized for subsequent investigations.The propeller modeling was simplified based on a conventional method,which expedited the model building process.The propeller performance was simulated using the computational fluid dynamics(CFD)method.The simulation results were validated by comparison with experimental data.Furthermore,the hydrodynamic pressure was transferred into a finite element analysis(FEA)module for strength assessment of ice-class propellers.According to URI3 rules,the ice loading was estimated based on different polar classes and working cases.Then,the FEA method was utilized to evaluate the propeller strength.The validation showed that the simulation results accorded with recent research results.Finally,an improved optimization method was developed to save the propeller constituent materials.The optimized propeller example had a minimum safety factor of 1.55,satisfying the safety factor requirement of≥1.5,and reduced the design volume to 88.2%of the original.

New smooth gap function for box constrained variational inequalities

A new smooth gap function for the box constrained variational inequality problem （VIP） is proposed based on an integral global optimality condition. The smooth gap function is simple and has some good differentiable properties. The box constrained VIP can be reformulated as a differentiable optimization problem by the proposed smooth gap function. The conditions, under which any stationary point of the optimization problem is the solution to the box constrained VIP, are discussed. A simple frictional contact problem is analyzed to show the applications of the smooth gap function. Finally, the numerical experiments confirm the good theoretical properties of the method.

PENALTY FUNCTION METHOD OF CONTINUUM SHAPE OPTIMIZAION

The penalty function method of continuum shape optimization and its sensitivity analysis technique are presented. A relatively simple integrated shape optimization system is developed and used to optimize the design of the inner frame shape of a three-axis test table. The result shows that the method converges well, and the system is stable and reliable.