Dynamic Parameter Identification Research Articles

Simultaneous hybrid modeling of a nosiheptide fermentation process using particle swarm optimization

Hybrid modeling approaches have recently been investigated as an attractive alternative to model fermentation processes. Normally, these approaches require estimation data to train the empirical model part of a hybrid model. This may result in decreasing the generalization ability of the derived hybrid model. Therefore, a simultaneous hybrid modeling approach is presented in this paper. It transforms the training of the empirical model part into a dynamic system parameter identification problem, and thus allows training the empirical model part with only measured data. An adaptive escaping particle swarm optimization (AEPSO) algorithm with escaping and adaptive inertia weight adjustment strategies is constructed to solve the resulting parameter identification problem, and thereby accomplish the training of the empirical model part. The uniform design method is used to determine the empirical model structure. The proposed simultaneous hybrid modeling approach has been used in a lab-scale nosiheptide batch fermentation process. The results show that it is effective and leads to a more consistent model with better generalization ability when compared to existing ones. The performance of AEPSO is also demonstrated.

Numerical modelling of anaerobic digestion reactor dynamics with a delay

Anaerobic digestion of municipal and animal wastes provides a potentially important means of producing energy sustainably. The reliable production of methane from anaerobic digestion requires that bacteria metabolise municipal and agricultural wastes to produce mainly carbon dioxide and methane. Our model uses Monod based kinetics and is complex since the biomass concentration growth is inhibited with the increase in substrate. The production of methane depends on the number of methanogenic bacteria; there is evidence from previous chemostats experiments that there is a time delay in population number of these cells to respond to changes in substrate concentrations. In this article we focus on determining the dynamical response of the methane production rate under different dynamics of feed conditions and temperatures. Since there is a delay in the methane bacteria mass response, we include the effects of the delay on the dynamics of the system based on modification of kinetics in a simple fermentation anaerobic model. We compare the dynamics of the system with and without delay to show the contribution of delay to the overall stability of the system. References O. Bernard, Z. Hadj-Sadok, D. Dochain, A. Genovesi, J. P. Steyer. Dynamical model development and parameter identification for an anaerobic wastewater treament process. Biotechnol. Bioeng. 75:424–438, 2001. doi:10.1002/bit.10036 T. F. Thingstad and T. I. Langeland. Dynamics of chemostat culture: The effect of a delay in cell response. J. Theor. Biol. , 48:149–159, 1974. doi:10.1016/0022-5193(74)90186-6 J. R. Beddington and R. M. May. Time delays are not nessarily destabilizing. Math. Biosci. 27:109–119, 1975. doi:10.1016/0025-5564(75)90028-0 K. Y. San and G. Stephanopoulos. The effect of growth rate delays in substrate-inhibited kinetics on the optimal profile of fed-batch reactors. J. Theor. Biol. 28:356–361, 1986. doi:10.1002/bit.260280308 G. Stephanopoulos and K. Y. San. Studies on-line bioreactor identification. I. Theory. Biotechnol. Bioeng. 26:1176–1188, 1984. doi:10.1002/bit.260261006 A. A. Khan, A. J. Stacey and J. J. Shepherd. Optimization of methane output for an anaerobic waste digester. ANZIAM J. 54:C523–C539, 2013. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/6322 J. F. Andrews. A mathematical model for the continuous culture of microorganisms utilizing inhibitory substrates. Biotechnol. Bioeng. 10:707–723, 1968. doi:10.1002/bit.260100602 D. J. Batstone, J. Keller, I. Angelidaki, S. V. Kalyuzzhni, S. G. Pavlostathis, A. Rozzi, W. T. M. Sanders, H. Siegrist, and V. A. Vavilin. Anaerobic digestion model No. 1 (ADM1). Water Sci. Technol. 45(10):65–73, 2002 http://wst.iwaponline.com/content/45/10/65 K. J. Beers. Numerical methods for chemical engineering: Applications in Matlab . Cambridge, New York, USA, 2007. http://www.cambridge.org/us/academic/subjects/engineering/chemical-engineering/numerical-methods-chemical-engineering-applications-matlab J. F. Andrews. The development of a dynamic model and control strategies for the anaerobic digestion process. In Mathematical Models in Water Pollution Control , A. James (ed). Wiley, 1978. A. W. Bush and A. E. Cook. The effect of time delay and growth rate inhibition in the bacterial treatment of wastewater J. Theor. Biol. 63:385–395, 1976. doi:10.1016/0022-5193(76)90041-2 L. F. Shampine, I. Gladwell and S. Thompson. Solving ODEs with Matlab . Cambridge, New York, USA, 2003. http://www.cambridge.org/us/academic/subjects/mathematics/numerical-analysis/solving-odes-matlab?format=PB

A Parametric Study on Friction Instabilities in Mechanical Face Seals

ABSTRACTThe present article aims to analyze and evaluate how dynamic parameter design influences the behavior of mechanical face seals and improves their performance by detecting undesirable phenomena like stick–slip and ringing. Those phenomena occur in situations of boundary lubrication.A new lumped parameter model is proposed to study mechanical face seals used in automotive cooling water pumps in order to examine how dynamic parameters such as mass, moment of inertia, and stiffness are involved in stick–slip phenomena. The aim of this work is to provide a practical design tool to predict stick–slip conditions and to choose the optimal mechanical specifications. Numerical simulations demonstrate how the critical service conditions vary with design parameters and permit tabulation of the results.

Dynamic parametric design and feasibility assessment for a high resistance measuring system

Abstract A high resistance measuring system (HRMS) is used to measure the surface insulation resistance (SIR) values of the printed circuit board (PCB), and monitor whether a momentary circuit short and/or the case of current slow leakage occur, which will affect the electrical properties of electronic components. This study constructs a dynamic parameter design for optimization of the test parameters of the HRMS in order to obtain robust test results. The optimal test parameters for SIR testing are: 390 ms test time, 100 V test voltage, 100 V, 15 s charge time, and 100 s pause interval. Further investigation is conducted on the impact of the test parameters on the measurement performance.

A new data-driven modeling method for fermentation processes

An accurate model is the premise for successfully implementing fermentation process optimization. Most data-driven models that are widely applied to fermentation processes are unfit for optimization or provide low precision. This paper presents a new data-driven modeling method for directly developing an ANN-based differential model that is fit for optimization. Moreover, this model can provide high precision because it can be discretized using the sampling period of the control variables as the step length. The lack of data pairs is addressed by transforming the model-training problem into a dynamic system parameter identification problem. Further, a particle swarm optimization algorithm with a time-varying escape mechanism (PSOE) is constructed to determine the model parameters. Finally, the uniform design method is used to select the model structure. The results of experiments conducted using practical data for a lab-scale nosiheptide batch fermentation process confirm the effectiveness of the proposed modeling method and PSOE algorithm.

A hybrid method for dynamic stiffness identification of bearing joint of high speed spindles

Bearing joint dynamic parameter identification is crucial in modeling the high speed spindles for machining centers used to predict the stability and natural frequencies of high speed spindles. In this paper, a hybrid method is proposed to identify the dynamic stiffness of bearing joint for the high speed spindles. The hybrid method refers to the analytical approach and experimental method. The support stiffness of spindle shaft can be obtained by adopting receptance coupling substructure analysis method, which consists of series connected bearing and joint stiffness. The bearing stiffness is calculated based on the Hertz contact theory. According to the proposed series stiffness equation, the stiffness of bearing joint can be separated from the composite stiffness. Then, one can obtain the bearing joint stiffness fitting formulas and its variation law under different preload. An experimental set-up with variable preload spindle is developed and the experiment is provided for the validation of presented bearing joint stiffness identification method. The results show that the bearing joint significantly cuts down the support stiffness of the spindles, which can seriously affects the dynamic characteristic of the high speed spindles.

The Dynamic FEM Models Results Comparison of the New Bridge Over Danube River in Bratislava

In general, the actual approach to achieve the dynamic parameters of bridge structures is supported to use standard FEM software. The final element model can be created by many different ways. The best way to obtain the objective results is to create at least two variants of FEM model. Currently, standard software of the FEM type is enabled to use variable types of elements. This paper shows the two basic models types of real slender road bridge. This bridge is named as: “The New Bridge over Danube”. This bridge is one of the Slovak capital dominants. For both models creation the historical documentation and the real dimension's measurements were applied. Both FEM models were created in the software of Scia Engineer v. 2013.Many existing slender long – span bridges are structurally adequate with respect to the maximum design axle loads, they may suffer from fatigue related to the cyclic application of modern freight equipment axle loads. Only the relevant FEM model can consider the real dynamic behaviour of the bridge. This is the idea for the best identification of dynamic parameters and FEM model tuning.

Dynamic Friction Parameter Identification Method with LuGre Model for Direct-Drive Rotary Torque Motor

Attainment of high-performance motion/velocity control objectives for the Direct-Drive Rotary (DDR) torque motor should fully consider practical nonlinearities in controller design, such as dynamic friction. The LuGre model has been widely utilized to describe nonlinear friction behavior; however, parameter identification for the LuGre model remains a challenge. A new dynamic friction parameter identification method for LuGre model is proposed in this study. Static parameters are identified through a series of constant velocity experiments, while dynamic parameters are obtained through a presliding process. Novel evolutionary algorithm (NEA) is utilized to increase identification accuracy. Experimental results gathered from the identification experiments conducted in the study for a practical DDR torque motor control system validate the effectiveness of the proposed method.

Nonlinear Modeling and Identification of an Aluminum Honeycomb Panel with Multiple Bolts

This paper focuses on the nonlinear dynamics modeling and parameter identification of an Aluminum Honeycomb Panel (AHP) with multiple bolted joints. Finite element method using eight-node solid elements is exploited to model the panel and the bolted connection interface as a homogeneous, isotropic plate and as a thin layer of nonlinear elastic-plastic material, respectively. The material properties of a thin layer are defined by a bilinear elastic plastic model, which can describe the energy dissipation and softening phenomena in the bolted joints under nonlinear states. Experimental tests at low and high excitation levels are performed to reveal the dynamic characteristics of the bolted structure. In particular, the linear material parameters of the panel are identified via experimental tests at low excitation levels, whereas the nonlinear material parameters of the thin layer are updated by using the genetic algorithm to minimize the residual error between the measured and the simulation data at a high excitation level. It is demonstrated by comparing the frequency responses of the updated FEM and the experimental system that the thin layer of bilinear elastic-plastic material is very effective for modeling the nonlinear joint interface of the assembled structure with multiple bolts.

Performance Analysis Based on Parameter Identification

A next generation of models is needed to guarantee energy performances of buildings and systems in practice. Current energy performance models use assumptions on climate, user behavior, characteristics of building and systems that may deviate from reality. Improvement of the accuracy of these models and assumptions is necessary to better predict the real energy performance of buildings and systems. Joining calculation models with data, using dynamic parameter identification (DPI), is a promising way for a better prediction of energy use in practice. Three example cases for identifying deviating building and system properties are discussed.

Dynamic Parameter Identification of Overactuated Parallel Robots

Offline robot dynamic identification methods are based on the use of the inverse dynamic identification model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal (the input reference of the motor current loop) with the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of the linear least squares technique to calculate the parameters (IDIM-LS technique). However, as actuation-redundant parallel robots are overactuated, their IDIM has an infinity of solution for the force/torque prediction, depending on the value of the desired overconstraint that is a priori unknown in the identification process. As a result, the IDIM cannot be used as it is for such a class of parallel robots. This paper proposes a procedure for the dynamic parameter identification of actuation-redundant parallel robots. The procedure takes advantage of two possible modified formulations for the IDIM of actuation-redundant robots that can be used for identification purpose. The modified IDIM formulations project some or all input torques/forces onto the robot bodies, thus leading to a unique solution of the model that can then be used in the identification process. A systematic and straightforward way to compute these modified IDIM is presented. The identification of the inertial parameters of a planar parallel robot with actuation redundancy, the DualV, is then carried out using these modified IDIM. Experimental results show the validity of the methods.

Axial dynamic characteristic parameters identification of rolling joints in a ball screw feed drive system

The dynamic characteristic parameters of mechanical joints are difficult to determine in theoretical modeling, dynamic simulation, and servo controller design for the ball screw feed drive system. Therefore, this study proposes a novel method for identifying the axial stiffness and damping parameters of the rolling joints in an assembled ball screw feed drive system. First, the proposed method deduces the axial vibration equations of the feed drive system with a harmonic excitation force exerted on its worktable. Second, the identification model of the axial stiffness and damping parameters of the rolling joints is established on the basis of the equations. Third, the identification equations are built by measuring the distance between the screw supporting points, the frequency, and the amplitude of the harmonic excitation force, as well as the amplitude of the axial vibration velocity of the screw end section. The axial stiffness and damping parameters of the rolling joints are finally determined by solving the identification equations using the genetic algorithm. With a ball screw feed drive system as the research object, the proposed method is used to identify the rolling joints’ axial stiffness and damping parameters of the ball screw assembly, as well as the left and the right bearing groups. The experiments show that the proposed method is correct, effective, and achieves high identification accuracy.

Dynamic Model Parameter Identification and Simulation of SCR Based on Genetic Algorithm§

The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.

Bearing dynamic parameters identification of a flexible rotor-bearing system based on transfer matrix method

Bearing dynamic parameters are important factors governing the vibration characteristics of rotating machinery; however, they are difficult to determine due to limited experimentation, and inaccurate in modelling. In this paper, a parameter identification method is presented to identify the bearing dynamic parameters of a flexible rotor-bearing system. In this method, the parameter identification problem is formulated as an inverse problem. The bearing dynamic parameters have been characterized through minimizing the error squared of the rotor-bearing system unbalance response between the experiment results and the computational ones. The intergeneration projection genetic algorithm is used to minimize the error squared. As an efficient method for analysing the dynamic behaviour of a rotor-bearing system, an improved transfer matrix method has been employed to calculate the unbalance response. This approach has been applied to identify the bearing dynamic parameters of a test rig supported by two anisotropic bearings, according to the unbalance response experimental data. Results indicated that this method could identify the bearing dynamic parameters. It is also robust to the noise effects.

Observer-based dynamic parameter identification for wheeled mobile robots

This paper presents a novel method for online dynamic parameter identification in wheeled mobile robots with nonholonomic constraints. First, the direct dynamic model of a mobile robot is obtained and reformulated in the linear form of dynamic parameters. Then, an adaptive estimation routine is proposed in order to identify the robot dynamic parameters with high accuracy and in finite time without requiring the measurement of the acceleration state vector. Based on Solidworks/ SimMechanics, a virtual prototype with the structure of a real mobile robot system is established to implement in the simulation. The simulation results demonstrate the effectiveness of the proposed approach for identifying the mobile robot dynamic parameters.

Characterization and Control of a Strontium Ferrite Motor

Exploiting the flux concentration configuration is a good alternative for designing a relatively low cost synchronous motor based on ferrite magnets. This paper discusses the design of a motor drive system based on a three-phase permanent magnet motor in which both the use of low cost ferrite and minimization of cogging torque have been adopted as design criteria. The dynamic modeling, parameter identification, and experimental characterization of the motor as well as the overall control system design have been performed. Simulation and experimental results are presented to demonstrate the correctness of the methodology and the feasibility of proposed motor drive solution and its related feedback control laws.

Inertia transfer concept based general method for the determination of the base inertial parameters

This paper presents a new algorithm to obtain the symbolic expressions of any of the possible base inertial parameter sets of a multibody system. Based on the “inertia transfer concept”, a procedure is proposed to write a system of equations from which the base parameters are obtained. This leads to an automatizable and general method to obtain these parameters symbolically. The method can also be used to determine base inertial parameters numerically, and it can be even more straightforward to implement and use than the standard numerical methods. An example is presented to illustrate in detail the application of the algorithm, and to compare its results with those of a standard numerical procedure. The symbolic base inertial parameters can be of interest in symbolic simplification of the dynamic equations for real-time applications, design optimization, dynamic parameter identification, model reduction, and in other fields.

Output Impedance Mismatch Effects on the Linearity Performance of Digitally Predistorted Power Amplifiers

This paper analyzes the effects of load impedance mismatch in power amplifiers which linearity has been enhanced using various digital predistortion (DPD) algorithms. Two different power amplifier architectures are considered: a class AB and a Doherty amplifier and three model structures for the DPD model are compared: memoryless polynomial (MLP), general memory polynomial (GMP) and Kautz-Volterra functions (KV). This paper provides a sensitivity analysis of the linearized amplifiers under load mismatch conditions and reports the performance when dynamic parameter identification for the DPD is used to compensate for the changes in the load impedance. In general, power amplifiers linearity is sensitive to load impedance mismatch. Linearity may degrade as much as 10 dB (in normalized mean square error) according to the magnitude and the phase of the reflection coefficient provided by the load impedance. However, depending on the amplifier design, the sensitivity to load impedance mismatch varies. While the Doherty amplifier studied show significant linearity degradations in the in-band and out-of-band distortions, the out-of-band distortions of the studied class AB were less sensitive to the load impedance mismatch. In adaptive DPD schemes, the performance obtained in the MLP model does not benefit from the updating scheme and the performance achieved is similar to a static case, where no updates are made. This stresses the memory requirements in the predistorter. When employing the GMP and the KV models in an adaptive DPD scheme, they tackle to a larger extent the linearity degradations due to load impedance mismatch.

Identification of Dynamic Parameters for Robots with Elastic Joints

This paper presents a novel method for identifying dynamic parameters of robot manipulators with elastic joints. A procedure based on the Lagrangianm formulation of the dynamic model is proposed. Each term is inspected to search for a linear relationship with the dynamic parameters, thus enabling the linearization of robot dynamic model. Hence, the torque vector is expressed as the product of a regressor matrix, suitably defined by the vector of dynamic parameters. A parametric identification based on a least-squares technique is applied to determine dynamic parameters of robots with elastic joints. The correctness of the proposed procedure has been tested in simulation on two robotic structures with elastic joints of different complexity, that is, a 2-degree-of-freedom (dof) and a 6-dof manipulator, controlled with a PD control in the joint space.

Dynamic characteristic parameters identification analysis of a parallel manipulator with flexible links

This paper presents dynamic parameters identification analysis of a 3-TPT parallel manipulator with flexible links by means of simulation and experiment. The 3-TPT mechanism is described in detail, and the dynamic equations of the regarded mechanism are derived analytically based on the Newton’s second law. The dynamic simulation model of parallel manipulator with flexible links is built by the integration method of virtual prototyping (VP) and finite element analysis (FEA), which forms the flexible multi-body system of parallel manipulator. Frequency response curves are obtained by applied force on the simulation model, and the stiffness and damping ratio are identified, respectively, from the simulation results. The strategy has been experimentally tested on an actual 3-TPT parallel manipulator. The compared results show that the errors are very small and reasonable scope, so it is feasible for the integration method used as reference and basis for dynamic characteristic. Therefore, the integration simulation method provides a theoretical foundation and reference for dynamic optimal design of parallel manipulator. These analyses and results provide valuable insight into the design and control of the parallel manipulator with flexible links.