Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance

This paper proposes a zero-moment control torque compensation technique.After compensating the gravity and friction of the robot,it must overcome a small inertial force to move in compliance with the external force.The principle of torque balance was used to realise the zero-moment dragging and teaching function of the lightweight collaborative robot.The robot parameter identification based on the least square method was used to accurately identify the robot torque sensitivity and friction parameters.When the robot joint rotates at a low speed,it can approximately satisfy the torque balance equation.The experiment uses the joint position and the current motor value collected during the whole moving process under the low-speed dynamic balance as the excitation signal to realise the parameter identification.After the robot was compensated for gravity and static friction,more precise torque control was realised.The zero-moment dragging and teaching function of the robot was more flexible,and the drag process was smoother.

PARAMETER IDENTIFICATION OF DYNAMIC MODELS USING A BAYES APPROACH

The Bayesian method of statistical analysis has been applied to the parameter identification problem. A method is presented to identify parameters of dynamic models with the Bayes estimators of measurement frequencies. This is based on the solution of an inverse generalized evaluate problem. The stochastic nature of test data is considered and a normal distribution is used for the measurement frequencies. An additional feature is that the engineer's confidence in the measurement frequencies is quantified and incorporated into the identification procedure. A numerical example demonstrates the efficiency of the method.

Dynamic modeling and parameter identification of a gun saddle ring

In this study,a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory.The ADAMS software was used to build a parameterized dynamic model of the saddle ring.A parameter identification method for the ring was proposed based on the particle swarm optimization algorithm.A loading test was designed and performed several times at different elevation angles.The response histories of the saddle ring with different loads were then obtained.The parameters of the saddle ring dynamic model were identified from statistics generated at a 500 elevation angle to verify the feasibility and accuracy of the proposed method.The actual loading history of the ring at a 70°elevation angle was taken as the model input.The response histories of the ring under these working conditions were obtained through a simulation.The simulation results agreed with the actual response.Thus,the effectiveness and applicability of the proposed dynamic model were verified,and it provides an effective method for modeling saddle rings.

Modeling and parameter identification of amplitude- and frequency-dependent rubber isolator

A model to describe the hysteresis damping characteristic of rubber material was presented.It consists of a parallel spring and damper,whose coefficients change with the vibration amplitude and frequency.In order to acquire these relations,force decomposition was carried out according to some sine vibration measurement data of nonlinear forces changing with the deformation of the rubber material.The nonlinear force is decomposed into a spring force and a damper force,which are represented by the amplitude-and frequency-dependent spring and damper coefficients,respectively.Repeating this step for different measurements gives different coefficients corresponding to different amplitudes and frequencies.Then,the application of a parameter identification method provides the requested approximation functions over amplitude and frequency.Using those formulae,as an example,the dynamic characteristic of a hollow shaft system supported by rubber rings was analyzed and the acceleration response curve in the centroid position was calculated.Comparisons with the sine vibration experiments of the real system show a maximal inaccuracy of 8.5%.Application of this model and procedure can simplify the modeling and analysis of mechanical systems including rubber materials.

Parameter Identification of Rubber Isolators Using Frequency-Dependent Spring and Damper Coefficients

A model to describe the hysteresis damper character of rubber material is presented in this paper. It consists of a parallel spring and damper, whose coefficients change with vibration frequencies. In order to acquire these relations, the force decomposition is carried out according to some sine vibration measurement data about nonlinear forces changing with deformations of the rubber material. The nonlinear force is decomposed into a spring force and a damper force, which are represented by a frequency-dependent spring and damper coefficient, respectively. Repeating this step for different measurements will give different coefficients corresponding to different frequencies. Then, application of a parameter identification method will provide the requested functions over frequency. Using those formulae, as an example, the dynamic character of a hollow shaft system supported by rubber rings is analyzed and the acceleration response curve in the centroid position is calculated. Comparisons with sine vibration experiments of the real system show a maximal inaccuracy of 8.8%. Application of this model and procedure can simplify the modeling and analysis of mechanical systems including rubber materials.

Parameters Identification for Extended Debye Model of XLPE Cables Based on Sparsity-Promoting Dynamic Mode Decomposition Method

To identify the parameters of the extended Debye model of XLPE cables,and therefore evaluate the insulation performance of the samples,the sparsity-promoting dynamicmode decomposition(SPDMD)methodwas introduced,aswell the basics and processes of its applicationwere explained.The amplitude vector based on polarization current was first calculated.Based on the non-zero elements of the vector,the number of branches and parameters including the coefficients and time constants of each branch of the extended Debye model were derived.Further research on parameter identification of XLPE cables at different aging stages based on the SPDMD method was carried out to verify the practicability of the method.Compared with the traditional differential method,the simulation and experiment indicated that the SPDMD method can effectively avoid problems such as the relaxation peak being unobvious,and possessing more accuracy during the parameter identification.And due to the polarization current being less affected by the measurement noise than the depolarization current,the SPDMD identification results based on the polarization current spectral line proved to be better at reflecting the response characteristics of the dielectric.In addition,the time domain polarization current test results can be converted into the frequency domain,and then used to obtain the dielectric loss factor spectrum of the insulation.The integral of the dielectric loss factor on a frequency domain can effectively evaluate the insulation condition of the XLPE cable.

Modeling and Analysis for Practical CT Based on Transient Test and Parameter Identification

In the transient process of power grid faults,the transferring distortion of current transformer(CT)can seriously affect relay protection performance.Under these conditions,it is difficult to analyze the ferromagnetic characteristic of the magnetizing branch in the transient equivalent circuit of CT.The Jiles-Atherton hysteresis model(J-A model),which is widely used in digital simulations,can accurately describe the hysteresis and saturation process of the core characteristics;however,to acquire the parameters of the J-A model of current transformers in practical use is still a challenging problem.In this paper,physical tests based on a practical CT and parameter identification are presented to solve the problem.The basic hysteresis loops of P,PR,and TPY class of practical current transformers are obtained through physical tests.Thus,the J-A model parameters are identified using a hybrid genetic/simulated annealing algorithm,based on which transient simulation models of different class CTs are constructed.The effectiveness of the proposed method is verified via dynamic physical simulation tests.A typical accident is analyzed based on these models.

Parameter identification of nonlinear system via a dynamic frequency approach and its energy harvester application

A dynamic frequency-based parameter identification approach is applied for the nonlinear system with periodic responses.Starting from the energy equation,the presented method uses a dynamic frequency to precisely obtain the analytical limit cycle expression of nonlinear system and utilizes it as the mathematic foundation for parameter identification.Distinguished from the time-domain approaches,the strategy of using limit cycle to describe the system response is unaffected by the influence of phase change.The analytical expression is fitted with the value sets from phase coordinates measured in periodic oscillation of the nonlinear systems,and the unknown parameters are identified with the interior-reflective Newton method.Then the performance of this identification methodology is verified by an oscillator with nonlinear stiffness and damping.Besides,numerical simulations under noisy environment also verify the efficiency and robustness of the identification procedure.Finally,we apply this parameter identification method to the modeling of a large-amplitude energy harvester,to improve the accuracy of mechanical modeling.Not surprisingly,good agreement is achieved between the experimental data and identified parameters.It also verifies that the proposed approach is less time-consuming and more accuracy in identification procedure.

PARAMETER IDENTIFICATION METHOD OF NONLINEAR JOINTS

Joints are widely used in many kinds of engineering structures, which often leads to the structures to exhibit local nonlinearities, and moreover, they are difficult to model because the complexity of configuration and operating mode. Therefore, parameter identification technique is usually used to model the joints and estimate the model parameters. A novel parameter identification method of nonlinear joints inside a structure is introduced in this paper, by expressing the force transmitted by the joint as a function of its mechanical state and assuming that the other part of the structure is known. In general, the force transmitted by the joints inside a structure and their mechanical state are difficult to measure. To overcome this difficulty, the algorithm of stochastic optimal control is used to identify the force transmitted by the joints and their mechanical state. After that, parameters of the joints can be identified by least squares parameter estimation method. Numerical simulation examples are also given to validate the effectiveness of the proposed method.

PROPER APPLICATION OF A KIND OF MATRIX CON-STRUCTION METHOD IN PHYSICAL PARAMETER IDENTIFICATION OF DYNAMIC MODEL

The expressions of matrix construction by using the singular value decomposition (SVD) are applied to the physics parameter identification of dynamic model. Then, based upon to the characteristics of a kind of matrix construction method, the orders of the parameter identification model can be reduced. After reducing, the mathematics and physics correspondence relations between the subsystem and the original system are distinct. the condensation errors can be avoided. The numerical example shows the benefit of the presented methodology.

Identification Schemes for Unmanned Excavator Arm Parameters

Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters （mass, inertia, and length） and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.

Studies on ecological characteristics variation and population dynamics of four lizardfishes in the southern Taiwan Straits

The ecological characteristics of four lizardfishes, Trachinocephalus myops, Saurida undosquamis, Saurida tumbil and Saurida elongata, were studied from specimens （910 T. myops, 454 S. un-dosquamis, 686 S. tumbil and 744 S. elongata） collected monthly in the southern Taiwan Straits from April 2005 to March 2006. The population dynamics of the four lizardfishes was also discussed by the comparison with the previous studies. All being composed of 7 a classes; the dominant group of T. myops and S. tumbil was 1–2 a, while S. undosquamis and S. elongate were 2–3 a. The total mortality coefficient Z and the fishing mortality F were at high as indicated by the exploitation ratio E（0.5）, and a large number of by-caught juvenile and young fishes showing that the stock of lizardfishes in this area was overexploited and the fishing gear was irrational. Compared with the previous studies, the maximum and mean fork length, body mass and age of the four lizard- fishes declined gradually, the lizardfishes populations were younger in age and smaller in size. The asymptotic fork length L ∞ decreased while increasing growth coefficient k, and age at the inflexion point of mass t r was younger compared with the previous studies. The declining of older ones has moderated the feeding competition and the younger ones grew faster. The larger mortality param-eters Z, M and F have revealed higher fishing pressure. The smaller change of the first mature fork length of female T . myops and the change from K selection pattern to r selection pattern of S. tumbil have indicated a more vulnerable fishery ecosystem in this area. The changes of ecological characteristics and population dynamics may be caused by over-exploitation of demersal fishes such as the lizardfishes, especially a large number of juvenile and young fishes by-catch by the current fishing gears and methods. Therefore, in addition to the traditional fishery management approach such as the minimum length-limit, ecosystem approach to fisheries management （EAF） should be taken to improve the practical marine ecosystem management, including increased fishing intensity of the non-economic species especially the feeding competitors of the lizardfishes and the conservation of the pelagic fishery population in the fisheries ecosystem, in order to restore the fishery population and achieve the sustainable use of the fishery stocks.

Population parameters and dynamic pool models of commercial fishes in the Beibu Gulf, northern South China Sea

Length-frequency data of eight commercial fish species in the Beibu Gulf (Golf of Tonkin), northern South China Sea, were collected during 2006-2007. Length-weight relationships and growth and mortality parameters were analyzed using FiSAT II software. Five species had isometric growth, two species had negative allometric growth, and one species had positive allometric growth. Overall, the exploitation rates of the eight species were lower in 2006-2007 than in 1997-1999: for four species (Saurida tumbil, Saurida undosquamis, Argyrosomus macrocephalus, and Nemipterus virgatus) it was lower in 2006-2007 than in 1997-1999, for two species (Parargyrops edita and Trichiurus haumela) it remained the same, and for the other two species (Trachurus japonicus and Decapterus maruadsi) it was higher in 2006-2007 than in 1997-1999. The exploitation rates might have declined because of the decline in fishing intensity caused by high crude oil prices. The optimum exploitation rate, estimated using Beverton-Holt dynamic pool models, indicated that although fishes in the Beibu Gulf could sustain high exploitation rates, the under-size fishes at first capture resulted in low yields. To increase the yield per recruitment, it is more effective to increase the size at first capture than to control fishing effort.

Identification of nucleation parameter for cellular automaton model of dynamic recrystallization

The accuracy of nucleation parameter is a critical factor in the simulation of microstructural evolution during dynamic recrystallization(DRX).Based on the flow stress curve under hot deformation conditions,a new approach is proposed to identify the nucleation parameter during DRX.In this approach,a cellular automaton(CA) model is applied to quantitatively simulate the microstructural evolution and flow stress during hot deformation;and adaptive response surface method(ARSM) is applied as optimization model to provide input parameters to CA model and evaluate the outputs of the latter.By taking an oxygen-free high-conductivity(OFHC) copper as an example,the good agreement between the simulation results and the experimental observations demonstrates the availability of the proposed method.

THEORY AND METHOD OF OPTIMAL CONTROL SOLUTION TODYNAMIC SYSTEM PARAMETERS IDENTIFICATION (Ⅰ)──FUNDAMENTAL CONCEPT AND DETERMINISTIC SYSTEM PARAMETERS IDENTIFICATION

Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into correspondence with optimal control problem. Then the theory and algorithm of optimal control are introduced into the study of dynamic system parameters identification. According to the theory of Hamilton-Jacobi-Bellman (HJB) equations solution, the existence and uniqueness of optimal control solution to dynamic system parameters identification are resolved in this paper. At last, the parameters identification algorithm of determi-nistic dynamic system is presented also based on above mentioned theory and concept.

THEORY AND ALGORITHM OF OPTIMAL CONTROL SOLUTION TO DYNAMIC SYSTEM PARAMETERS IDENTIFICATION(Ⅱ)──STOCHASTIC SYSTEM PARAMETERS IDENTIFICATION AND APPLICATION EXAMPLE

Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (Ⅰ), then the procedure of establishing HamiltonJacobi-Bellman (HJB) equations of parameters identification problem is presented.And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.