Accepted Manuscripts

Guaraci Jr. Bastos
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041530
An integrated and general methodology is required to define an ideal relation between input controls and structural parameters of a system in trajectory tracking problems. For underactuated manipulators, a synergistic optimal design should be to reduce elastic deformations, mass of structure and actuation forces. The key advantage of such integrated approach is the capability to search in a design space, to account for many dynamic couplings in an early design stage and to avoid simplifying assumptions which would induce to suboptimal design. Particulary, some advances considering underactuated manipulators are the possibility to treat non-minimum phase systems, then lighter structures could be selected, since bounded and smoother solution could be generated. A synergistic consideration in view to find the desired requirements and realize the specified task thought an optimal control problem is considered, where a generalization of an inverse dynamics problem is defined. A planar underactuated manipulator is considered for the methodology application.
TOPICS: Trajectories (Physics), Design, Manipulators, Dynamics (Mechanics), Deformation, Optimal control, Couplings
Imen Hbiri, Houssem Karkri, Fathi H. Ghorbel and Slim Choura
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041506
In this paper, we develop dynamic equations of motion of an in-tank swimming robot moving with low speed and performing tank floor inspection while the tank is filled with liquid. The robot's inspection maneuvers consist of a vertical up/down swimming motion and a floor two-dimensional motion of the robot swim- ming while in touch with the floor on wheels. The proposed dynamic model includes in particular drag and added mass coefficients that prove to be quite important for low speed maneuvering. The identified drag and added mass coefficients were obtained with CFD simulations. For the floor motion, we modeled wheel friction using LuGre friction model. The complete dynamic model was validated experimentally using a swimming robot in a circular water pool. The dynamic model developed in this paper will particularly be useful to devise model-based advanced control laws required for accurate maneuverability of floor inspec- tion swimming robots.
TOPICS: Inspection, Robots, Modeling, Dynamic models, Friction, Wheels, Drag (Fluid dynamics), Simulation, Equations of motion, Computational fluid dynamics, Engineering simulation, Water
Tobias Miunske, Justin Pradipta and Oliver Sawodny
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041504
To make motion perception more realistic, a current implemented classical washout motion cueing algorithm is extended to a model predictive motion cueing algorithm for a seven-cylinder pneumatically-actuated Stewart platform. Through this enhancement, not only are potential predictive signals taken into account, but also comprehensive information and data sets relating to the mechanical limitations of the simulator platform. The significantly increased information content enables the calculation of far more specific targeted requirements for the platform. First, the platform kinematics are derived and its physical platform constraints, are examined. Furthermore, the classical washout motion cueing algorithm is extended and transformed into a state-space based motion cueing algorithm for the purpose of setting up a linear quadratic model predictive motion cueing algorithm. Finally, the model predictive motion cueing algorithm is simulated and evaluated with respect to its degree of realism.
TOPICS: Algorithms, Cylinders, Signals, Kinematics
Yuhang Liu, Shiyu Zhou, Yong Chen and Jiong Tang
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041505
Linearization of the eigenvalue problem has been widely used in vibration-based damage detection utilizing the change of natural frequencies. However, the linearization method introduces bias in the estimation of damage parameters. Moreover, the commonly employed regularization method may render the estimation different from the true underlying solution. These issues may cause wrong estimation in the damage severities and even wrong damage locations. Limited work has been done to address these issues. We find that particular combinations of natural frequencies will result in less biased estimation using linearization approach. In this paper, we propose a measurement selection algorithm to select an optimal set of natural frequencies for vibration-based damage identification. The proposed algorithm adopts L1- norm regularization with iterative matrix randomization for estimation of damage parameters. The selection is based on the estimated bias using the least square method. Comprehensive case analyses are conducted to validate the effectiveness of the method.
TOPICS: Damage, Vibration, Eigenvalues, Selection algorithm, Algorithms
Matthew Bender, Aishwarya George, Nathan Powell, Andrew Kurdila and Rolf Müller
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041446
Bioinspired design of robotic systems can offer many potential advantages in comparison to traditional architectures including improved adaptability, maneuverability, or efficiency. Substantial progress has been made in the design and fabrication of bioinspired systems. While many of these systems are bioinspired at a system architecture level, the design of linkage connections often assumes that motion is well approximated by ideal joints subject to designer-specified box constraints. However, such constraints can allow a robot to achieve unnatural and potentially unstable configurations. In contrast, this paper develops a methodology which identifies the set of admissible configurations from experimental observations and optimizes a compliant structure around the joint such that motions evolve on or close to the observed configuration set. This approach formulates an analytical-empirical potential energy field which "pushes" system trajectories towards the set of observations. Then, the strain energy of a compliant structure is optimized to approximate this energy field. While our approach requires that kinematics of a joint be specified by a designer, the optimized compliant structure enforces constraints on joint motion without requiring an explicit definition of box-constraints. To validate our approach we construct a 1-DOF elbow joint which closely matches the analytical-empirical and optimal potential energy functions and admissible motions remain within the observation set.
TOPICS: Design, Biomimetics, Potential energy, Linkages, Kinematics, Robots, Manufacturing, System architecture, Robotics, Architecture
Patrick Sammons, Douglas Bristow and Robert Landers
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041444
Additive Manufacturing (AM) processes fabricate parts by adding material in a layer-by-layer fashion. In order to enable closed-loop process control - a major hurdle in the adoption of most AM processes - compact models suitable for control design and for describing the layer-by-layer material addition process are needed. This paper proposes a two-dimensional modeling framework whereby the deposition of the current layer is affected by both in-layer and layer-to-layer dynamics, both of which are driven by the state of the previous layer. The proposed framework can be used to describe phenomena observed in AM processes such as layer rippling and large defects in Laser Metal Deposition (LMD) processes. Further, the proposed framework can be used to create two-dimensional dynamic models for the analysis of layer-to-layer stability and as a foundation for the design of layer-to-layer controllers for AM processes. In the application to LMD, a two-dimensional Linear-Nonlinear-Linear (LNL) repetitive process model is proposed that contains a linear dynamic component, which describes the dynamic evolution of the process from layer to layer, cascaded with a static nonlinear component cascaded with another linear dynamic component, which describes the dynamic evolution of the process within a given layer. A methodology, which leverages the two-dimensional LNL structure, for identifying the model process parameters is presented and validated with quantitative and qualitative experimental results.
TOPICS: Metals, Lasers, Modeling, Design, Dynamic models, Additive manufacturing, Dynamics (Mechanics), Stability, Process control, Control equipment
Haruhiko Harry Asada and Filippos Sotiropoulos
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041448
A new approach to modeling and linearization of nonlinear lumped-parameter systems based on physical modeling theory and a data-driven statistical method is presented. A nonlinear dynamical system is represented with two sets of differential equations in an augmented space consisting of independent state variables and auxiliary variables that are nonlinearly related to the state variables. It is shown that the state equation of a nonlinear dynamical system having a Bond Graph model of integral causality is linear, if the space is augmented by using the output variables of all the nonlinear elements as auxiliary variables. The dynamic transition of the auxiliary variables is investigated as the second set of differential equations, which are linearized by using statistical linearization. It is shown that the linear differential equations of the auxiliary variables inform behaviors of the original nonlinear system that the first set of state equations alone cannot represent. The linearization based on the two sets of linear state equations, termed Dual Faceted Linearization (DFL), can capture diverse facets of the nonlinear dynamics and, thereby, provide a richer representation of the nonlinear system. The two state equations are also integrated into a single latent model consisting of all significant modes with no collinearity. Finally, numerical examples verify and demonstrate the effectiveness of the new methodology.
TOPICS: Modeling, Nonlinear dynamical systems, Differential equations, Nonlinear systems, Nonlinear dynamics
David Bou Saba, Paolo Massioni, eric bideaux and Xavier BRUN
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041445
Pneumatic artificial muscles are an interesting type of actuators as they provide high power-to-weight and powerto-volume ratio. However, their efficient use requires very accurate control methods taking into account their complex and nonlinear dynamics. This paper considers a two-degree-of-freedom platform whose attitude is determined by three pneumatic muscles controlled by servovalves. An overactuation is present as three muscles are controlled for only two degrees of freedom. The contribution of this work is twofold. First, whereas most of the literature appraches the control of systems of similar nature with sliding mode control, we show that the platform can be controled with the flatness-based approach. This method is a nonlinear open-loop controller. In addition, this approach is model-based, and it can be applied thanks to the accurate models of the muscles, the platform and the servovalves, experimentally developed. In addition to the flatness-based controller, which is mainly a feedforward control, a proportional-integral controller is added in order to overcome the modeling errors and to improve the control robustness. Second, we solve the overactuation of the platform, by an adequate choice for the range of the efforts applied by the muscles. In this paper, we recall the basics of this control technique and then show how it is applied to the proposed experimental platform. At the end of the paper, the proposed approach is compared to the most commonly used control method, and its effectiveness is shown by means of experimental results.
TOPICS: Muscle, Control equipment, Sliding mode control, Degrees of freedom, Actuators, Modeling, Errors, Feedforward control, Robustness, Nonlinear dynamics, Weight (Mass)
Kenan Isik, Gray Thomas and Luis Sentis
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041449
Series Elastic Actuators are widely used for impact protection and compliant behavior, but they typically fall short in tasks calling for accurate position control. In this paper, we propose a simple and effective heuristic for tuning series elastic actuator controllers to a high impedance position control behavior which compares favorably with previous publications. Our approach considers two models, an ideal model and a non-ideal model with time delays and filtering lag. The ideal model is used to design cascaded PD-type outer impedance and inner force loops as a function of critically-damped closed-loop poles for the force and impedance loops. The non-ideal model provides an estimate of the phase margin of the position controller for each candidate controller design. A simple optimization algorithm finds the best high-impedance behavior for which the non-ideal model meets a desired phase margin requirement. In this way, the approach automates the tradeoff between force and impedance bandwidth. The effect of important system parameters on the impedance bandwidth is also analyzed and the proposed method verified with a physical actuator.
TOPICS: Actuators, Control equipment, Position control, Design, Delays, Optimization algorithms, Tradeoffs, Poles (Building), Filtration
Taeyoung Lee, Dong Eui Chang and Yongsoon Eun
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041447
This paper presents tracking strategies for the attitude dynamics of a rigid body that are global on the configuration space $\SO$ and semi-global over the phase space $\SO \times \mathbb R^3$. It is well known that global attractivity is prohibited for continuous attitude control systems on the special orthogonal group. Such topological restriction has been dealt with either by constructing smooth attitude control systems that exclude a set of zero measure in the region of attraction, or by introducing discontinuities in the control input. This paper proposes non-memoryless attitude control systems that are continuous in time, where the region of attraction guaranteeing exponential convergence completely covers the special orthogonal group. This provides a new framework to address the topological restriction in attitude controls. The efficacy of the proposed methods is illustrated by numerical simulations and an experiment.
TOPICS: Dynamics (Mechanics), Control systems, Computer simulation, Phase space
Gustavo Koury Costa and Nariman Sepehri
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041382
In this paper, we present a novel design for single-rod hydrostatic actuators that produces a stable response in all operation quadrants. The new design, which can have different embodiments, is built upon compensating for the differential flows coming in and out of single-rod actuators, by alternately connecting cap and rod sides of the cylinder to a flow source in accordance with the energy flow direction between the circuit and the load. We show that previous quadrant division definitions result in either geometric quadrants that do not coincide with motoring and pumping operation, or misrepresentations of the actual energy exchange between the load and the cylinder. The proposed quadrant representation gives the exact information about the right operation of compensating flow valves. The efficacy of the new design has been tested on an instrumented John Deere JD-48 backhoe. Precise redirection of the compensation flow allowed for non-oscillatory motions in all quadrants of operation and various loading conditions.
TOPICS: Actuators, Design, Hydrostatics, Flow (Dynamics), Cylinders, Stress, Valves, Circuits
Saeed Salavati, Karolos Grigoriadis, Matthew Franchek and Reza Tafreshi
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041383
The full and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H8 problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full and reduced-order filters are designed for sensor fault detection and isolation. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.
TOPICS: Flow (Dynamics), Design, Filters, Flaw detection, Transmission lines, Noise (Sound), Fault diagnosis, Instrumentation, Sensors, Simulation, Fluids, Modeling, Pipeline systems, Engineering simulation, Unsteady flow, Linear matrix inequalities, Shapes
Milad Karimshoushtari and Carlo Novara
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041354
Lean NOx Trap (LNT) is one of the most effective after-treatment technologies used to reduce NOx emissions of diesel engines. One relevant problem in this context is LNT regeneration timing control. This problem is indeed difficult due to the fact that LNTs are highly nonlinear systems, involving complex physical/chemical processes, that are hard to model. In this paper, a novel approach for regeneration timing of LNTs is proposed, allowing us to overcome these issues. This approach, named data-driven model predictive control (D2-MPC), does not require a physical model of the engine/trap system but is based on low-complexity polynomial prediction models, directly identified from data. The regeneration timing is computed through an optimization algorithm, which uses the identified models to predict the LNT behavior. Two D2-MPC strategies are proposed, and tested in a co-simulation study, where the plant is represented by a detailed LNT model, built using the well-known commercial tool AMEsim, and the controller is implemented in Matlab/Simulink.
TOPICS: Nitrogen oxides, Emissions, Chemical processes, Control equipment, Engines, Simulation, Nonlinear systems, Diesel engines, Matlab, Optimization algorithms, Polynomials, Predictive control
Yongxiang Jiang, Shijie Guo and Sanpeng Deng
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041355
This paper proposes a detection method of driver fatigue by use of electrocardial signals. Firstly, LWT (Lifting Wavelet Transform) was used to reduce signal noise and its effect was confirmed by applying it to the denoising of a white-noise-mixed Lorenz signal. Secondly, phase space reconstruction was conducted for extracting chaotic features of the measured electrocardial signals. The phase diagrams show fractal geometry features even under a strong noise background. Finally, Kolmogorov entropy, which is a factor reflecting the uncertainty in and the chaotic level of a nonlinear dynamic system, was used as an indicator of driver fatigue. The effectiveness of Kolmogorov entropy in the judgement of driver fatigue was confirmed by comparison with an SD (Semantic Differential) subjective evaluation experiment. It was demonstrated that Kolmogorov entropy has a strong relationship with driver fatigue. It decreases when fatigue occurs. Furthermore, the influences of delay time and sampling points on Kolmogorov entropy were investigated since the two factors are important to the actual use of the proposed detection method. Delay time may have significant influence on fatigue determination, but sampling points are relatively inconsequential. This result indicates that real time detection can be realized by selecting a reasonably small number of sampling points.
TOPICS: Fatigue, Entropy, Feature extraction, Signals, Noise (Sound), Delays, Wavelet transforms, Uncertainty, Fractals, Geometry, Nonlinear dynamical systems, Phase diagrams, Phase space
Prem Kumar, B. Bhavya Anoohya and Radhakant Padhi
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041356
Inspired by fast model predictive control (MPC), a new nonlinear optimal command tracking technique is presented in this paper, which is named as 'Tracking-oriented Model Predictive Static Programming (T-MPSP)'. Like MPC, a model-based prediction-correction approach is adopted. However, the entire problem is converted to a very low-dimensional 'static programming' problem, from which the control history update is computed in closed-form. Moreover, the necessary sensitivity matrices (which are the backbone of the algorithm) are computed recursively. These two salient features make the computational process highly efficient, thereby making it suitable for implementation in real time. A trajectory tracking problem of a two-wheel differential drive mobile robot is presented to validate and demonstrate the proposed philosophy. The simulation studies is very close to realistic scenario by incorporating disturbance input, parameter uncertainty, feedback sensor noise, time delays, state constraints and control constraints. The algorithm has been implemented on a real hardware and experimental validation corroborates the simulation results.
TOPICS: Computer programming, Algorithms, Delays, Feedback, Mobile robots, Predictive control, Simulation results, Wheels, Sensors, Simulation, Hardware, Noise (Sound), Trajectories (Physics), Uncertainty
Sofiane Khadraoui, Raouf Fareh, Hazem Nounou and Mohamed Nounou
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041357
This paper deals with the design of fixed-structure controllers for TITO (two-input two-output) systems using frequency-domain data. In standard control approaches, a plant model is first derived, then a suitable controller is designed to meet some user-specified performance specifications. Basically, there are two common ways for obtaining mathematical models: white-box modeling and black-box modeling. In both approaches, it is difficult to obtain a simple and accurate model that completely describes the system dynamics. As a result, errors associated with the plant modeling may result in degradation of the desired closed-loop performance. Moreover, the intermediate step of plant modeling introduced for the controller design is a time consuming task. Hence, the concept of data-based control design is introduced as a possible alternative to model-based approaches. This promising methodology allows us to avoid the under-modeling problem and to significantly reduce the time and workload for the user. Most existing data-based control approaches are developed for SISO (single-input single-output) systems. Nevertheless, a large class of real systems involve several manipulated and output variables. To this end, we attempt here to develop an approach to design controllers for TITO systems using frequency-domain data. In such a method, a set of frequency-domain data is utilized to find an adequate decoupler and to tune a diagonal controller that meets some desired closed-loop performance measures. Two simulation examples are presented to illustrate and demonstrate the efficacy of the proposed method.
TOPICS: Design, Modeling, Control equipment, System dynamics, Simulation, Errors
Tassadit Chekari, Rachid Mansouri and Maamar Bettayeb
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041353
This paper is aimed to propose a multiloop control scheme for Fractional Order Multi-Input Multi-Output (FO-MIMO) systems. It is an extension of the FO-multiloop controller design method developed for integer order multivariable systems to FO-MIMO ones. The interactions among the control loops are considered as disturbances and a 2DOF paradigm is used to deal with the process outputs performance and the interactions reduction effect, separately. The proposed controller design method is simple, in relation with the desired closed loop specifications and a tuning parameter. It presents an interest in controlling complex MIMO systems since Fractional Order models (FO-models) represent some real processes better than integer order ones and high order systems can be approximated by FO-models. Two examples are considered and compared with other existing methods to evaluate the proposed controller.
TOPICS: Control equipment, Design, Design methodology
Truong Sinh Nguyen, Jian Song, Liangyao Yu, Shengnan Fang, Yuzhuo Tai and Zhenghong Lu
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041358
An approach for building a real-time simulation and testing platform for a novel seamless two-speed automated manual transmission (AMT) for electric vehicles (EVs) is proposed and experimentally evaluated. First, the structure of the AMT and the dynamic model of an EV powertrain system equipped with the AMT are presented. Then, according to the testing requirements, a prototype of the AMT, hardware components and software system of the platform are designed. Unlike a real-time transmission test bench, of which the real-time simulation and control system (RSCS) is built based on a dedicated simulator, the RSCS of the platform is built based on a standard desktop PC by using a useful and low-cost solution from MATLAB/Simulink®. Additionally, a simulation model of EV, which is equipped with the AMT and is more suitable for hardware-in-the-loop (HIL) simulation, has been developed. In particular, for conducting various dynamic mechanical tests, the platform is combined with induction motors (IMs), which are adopted with direct torque control (DTC) technique to emulate the dynamic driving conditions of the transmission. The designed platform can be used for different test techniques, including rapid simulation, rapid control prototyping, hardware-in-the-loop simulation as well as dynamic mechanical tests. The work expands the capability of the platform and makes the test conditions become closer to reality. Simulation and experimental results indicate that the platform responds well to the real-time dynamic requirements and it is very useful for developing the proposed transmission.
TOPICS: Simulation, Design, Testing, Electric vehicles, Hardware, Mechanical testing, Simulation models, Torque control, Dynamic models, Manual transmissions, Engineering prototypes, Electromagnetic induction, Control systems, Motors, Matlab, Computer software
Yimin Chen and Junmin Wang
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041359
Thermal protection strategy is employed to protect in-wheel-motors in thermal fault conditions. Vehicle motion and stability maybe affected by motor thermal protection because the output torque is reduced to lower motor temperature and protect motor from thermal damage. This paper proposes a fault-tolerant control (FTC) method and a fault-prevention control (FPC) method for vehicle motion control considering motor thermal protection. The FTC method is developed to stabilize vehicle motions when motor thermal protection is triggered. A control allocation (CA) with motor temperature measurement algorithm is developed for the FTC method. The output torque constraints are changed with motor temperature to include thermal protection strategy in the controller design. When future trajectories are available, the FPC method is created to prevent motor thermal faults. A model predictive control (MPC) algorithm is used to regulate the control efforts in advance to avoid overheating in-wheel-motors and triggering the thermal protection strategy. The proposed methods are validated in CarSim® simulations. The results show that both the FTC and FPC methods can eliminate the yaw rate tracking errors when in-wheel-motors are subject to thermal protection strategy.
TOPICS: Motion control, Engines, Motors, Electric vehicles, Wheels, Vehicles, Algorithms, Torque, Temperature, Temperature measurement, Control equipment, Stability, Design, Engineering simulation, Yaw, Damage, Errors, Predictive control, Simulation
Ahmet Can Afatsun and Tuna Balkan
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4041300
In this paper, a mathematical model to simulate the pressure and flow rate characteristics of a spool valve is derived. To improve the simulation accuracy, the discharge coefficient through the spool valve ports is assumed to be a function of both the Reynolds number and the orifice geometry rather than treating it as a constant. Parameters of the model are determined using the data obtained by computational fluid dynamics (CFD) analyses conducted on 2D axisymmetric domains using ANSYS Fluent 15 commercial software. For turbulence modeling, SST k-w model is preferred after a comparison of performance with the other available turbulence model options. Resulting model provides consistent pressure and flow rate estimations with CFD analyses and a smooth transition between different geometrical conditions. The ultimate aim of this study is to fulfill the need for a model to precisely determine the geometrical tolerances of spool valve components for optimum performance. Estimations of the developed model is compared with the experimental data of a spool valve and the model is proved to be able to accurately estimate the maximum leakage flow rate, the pressure sensitivity and the shapes of leakage flow/load pressure curves.
TOPICS: Flow (Dynamics), Simulation, Valves, Pressure, Computational fluid dynamics, Leakage flows, Turbulence, Reynolds number, Stress, Gates (Closures), Computer software, Discharge coefficient, Geometry, Shapes, Modeling

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