Accepted Manuscripts

Ruzhou Yang and Marcio de Queiroz
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039366
In this paper, we introduce two robust adaptive controllers for the human shank motion tracking problem that is inherent to neuromuscular electrical stimulation systems. The control laws adaptively compensate for the unknown parameters that appear nonlinearly in the musculoskeletal dynamics while providing robustness to additive disturbance torques. The adaptive schemes exploit the Lipschitzian and/or the concave/convex parameterizations of the model functions. The resulting control laws are continuous and guarantee practical tracking for the shank angular position. The performance of the two robust adaptive controllers are demonstrated via simulations.
TOPICS: Adaptive control, Dynamics (Mechanics), Control equipment, Simulation, Engineering simulation, Neuromuscular stimulation, Robustness, Musculoskeletal system
Technical Brief  
Yoon-Gyung Sung, W. S. Jang and Jae-Yeol Kim
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039367
A negative input shaped command is presented for flexible systems to reduce the residual oscillation under unequal acceleration and braking delays of actuators that are common issues in industrial applications. Against this nonlinearity, a compensated unit magnitude zero vibration shaper is analytically developed with a phasor vector diagram and a ramp-step function to approximate the dynamic response of the unequal acceleration and braking delays of actuators. A closed-form solution is presented with a benchmark system without sacrificing the generality and simplicity for industrial applications. The robustness and control performance of the exact solution are numerically evaluated and compared with those of an existing negative input shaper in terms of the switch-on time, command interference, and effects of the shaper parameters. The proposed negative input shaped commands are experimentally validated with a mini-bridge crane.
TOPICS: Actuators, Braking, Delays, Dynamic response, Robustness, Switches, Flexible systems, Vibration, Oscillations, Bridges (Structures), Cranes
Tingting Jiang, Jin kun Liu and Wei He
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039364
In this paper, the problem of state constraints control is investigated for a class of output constrained flexible manipulator system with varying payload. The dynamic behavior of the flexible manipulator is represented by partial differential equations. To prevent states of the flexible manipulator system from violating the constraints, a Barrier Lyapunov Function which grows to infinity whenever its arguments approach to some limits is employed. Then based on the Barrier Lyapunov Function, boundary control laws are given. To solve the problem of varying payload, an adaptive boundary controller is developed. Furthermore, based on the theory of Barrier Lyapunov Function and the adaptive algorithm, state constraints and output control under vibration condition can be achieved. The stability of the closed-loop system is carried out by the Lyapunov stability theory. Numerical simulations are given to illustrate the performance of the closed-loop system.
TOPICS: Flexible manipulators, Closed loop systems, Stability, Control equipment, Computer simulation, Algorithms, Vibration, Partial differential equations
Masood Ghasemi and Xingyong Song
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039365
This paper investigates a nonlinear control design for trajectory tracking and rate of penetration (ROP) control of the vertical downhole drilling process. The drilling system dynamics are first built incorporating the coupled axial and torsional dynamics together with a velocity independent drill bitrock interaction model. Given the under-actuated and nonlinear feature of the drilling dynamics with sharp transients, we propose a control design that can prevent significant downhole vibrations, enable accurate tracking and achieve desired rate of penetration. It can also ensure robustness against modeling uncertainties and external disturbances. The controller is designed using a sequence of hyperplanes given in a cascade structure. The tracking control is achieved in two phases, where in the first phase the drilling system states converge to a high-speed drilling regime free of stick-slip behaviour and in the second phase the error dynamics can asymptotically converge. Finally, we provide simulation results considering different case studies to evaluate the efficacy and the robustness of the proposed control approach.
TOPICS: Drilling, Trajectories (Physics), Dynamics (Mechanics), Robustness, Design, Modeling, Vibration, Errors, System dynamics, Cascades (Fluid dynamics), Transients (Dynamics), Simulation results, Stick-slip, Tracking control, Uncertainty, Control equipment, Drills (Tools)
Jie Huang and Xinsheng Zhao
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039278
Rectangular containers are used for numerous liquid transports in many industrial applications. However, unwanted slosh in the container degrades safe and reliable operations. A three-dimensional nonlinear slosh model in a more clear way is presented, which benefits simulations of the nonlinear slosh dynamics. In addition, a new method is designed for suppressing the nonlinear slosh by filtering the driving commands. Comparison between the new method and a previously present method is also explored. Many simulations are conducted to analyze the sloshing dynamics and the effectiveness of the new method. Experimental results obtained from a moving rectangular container validate the dynamic effects and the effectiveness of the method.
TOPICS: Containers, Sloshing, Simulation, Engineering simulation, Dynamics (Mechanics), Filtration
Arash Sheikhlar and Ahmad Fakharian
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039287
In this paper, online policy iteration reinforcement learning algorithm is proposed for motion control of four wheeled omni-directional robots. The algorithm solves the linear quadratic tracking (LQT) problem in an online manner using real-time measurement data of the robot. This property enables the tracking controller to compensate the alterations of dynamics of the robot's model and environment. The online policy iteration based tracking method is employed as low level controller. On the other side, a proportional derivative (PD) scheme is performed as supervisory planning system (high level controller). In this study, the followed paths of online and offline policy iteration algorithms are compared in a rectangular trajectory in presence of slippage drawback and motor heat. Simulation and implementation results of the methods demonstrate the effectiveness of the online algorithm compared to offline one in reducing the command trajectory tracking error and robot's path deviations. The novelty of this paper is proposition of a simple-structure learning based adaptive optimal scheme that tracks the desired path, optimizes the energy consumption and solves the uncertainty problem in omni-directional wheeled robots.
TOPICS: Robots, Tracking control, Algorithms, Control equipment, Trajectories (Physics), Energy consumption, Errors, Uncertainty, Engines, Dynamics (Mechanics), Heat, Motors, Simulation, Motion control
Huan Do, Jongeun Choi, Chae Young Lim and Tapabrata Maiti
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039286
Appearance-based localization is a type of robot self-navigation technique, in which the environment map describes a visual features map instead of a geometrical features map. Since images are high dimensional, commonly learning schemes are developed based on features space instead of image space. Therefore, the localization performance essentially depends on the set of chosen visual features. For a high dimensional feature space, choosing the optimal set of features by handcrafting is impractical. Thus, we build a regression model based on extracted visual features from raw images as predictors to estimate the robot's location in 2-D coordinates. We define our supervised learning problem as: given the training data, our model finds the optimal subset of the features that maximizes the localization performance. To tackle the problem, we propose an integrated localization model that consists of two main components: the Least Absolute Shrinkage and Selection Operator (LASSO) regression followed by a filtering estimator. In this study, we examine two candidates for the filtering estimator: the extended Kalman filter (EKF) and Particle Filter (PF). From a raw image, we extract a number of visual features, viz. Fast Fourier Transform, color histogram, and the Speeded-Up Robust Features (SURF). Our method is implemented in both indoor mobile robot and outdoor vehicle equipped with an omni-directional camera. The results validate the effectiveness of our proposed approach.
TOPICS: Mobile robots, Filtration, Particulate matter, Robots, Shrinkage (Materials), Vehicles, Fast Fourier transforms, Filters, Kalman filters, Navigation, Regression models
Tao Zeng, Devesh Upadhyay and Guoming George Zhu
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039285
Control-oriented models for automotive turbocharger compressors typically describe the compressor power assuming an isentropic thermodynamic process with fixed isentropic and mechanical efficiencies for power transmission between the turbine and compressor. Although these simplifications make the control-oriented model tractable, they also introduce additional errors due to un-modeled dynamics. This is especially true for map-based approaches since the manufacture-provided maps tend to be sparse and often incomplete at the operational boundaries, especially at operational conditions with low mass flow rate and low speed. Extrapolation scheme is often used when the compressor is operated outside the mapped regions, which introduces additional errors. Furthermore, the manufacture-provided compressor maps, based on steady-flow bench tests, could be quite different from these under pulsating engine flow. In this paper, a physics-based model of compressor power is developed using Euler equations for turbo-machinery, where the mass flow rate and compressor rotational speed are used as model inputs. Two new coefficients, speed and power coefficients, are defined. As a result, this makes it possible to directly estimate the compressor power over the entire compressor operational range based on a single analytic relationship. The proposed modeling approach is validated against test data from standard turbocharger flow bench tests, standard supercharger tests, steady-state and certain transient engine dynamometer tests. Model validation results show that the proposed model has acceptable accuracy for model-based control design and also reduces the dimension of the parameter space typically needed to model compressor dynamics.
TOPICS: Turbochargers, Compressors, Flow (Dynamics), Dynamics (Mechanics), Errors, Model validation, Steady state, Turbomachinery, Mechanical efficiency, Dynamometers, Superchargers, Physics, Engines, Dimensions, Transients (Dynamics), Thermodynamic processes, Design, Engine flow, Modeling, Turbines
William Scott and Naomi Leonard
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039283
We present time-optimal trajectories for a steered agent with constraints on speed, lateral acceleration, and turning rate for the problem of reaching a point on the plane in minimum time with free terminal heading angle. Both open-loop and state-feedback forms of optimal controls are derived through application of Pontryagin's minimum principle. We apply our results for the single agent to solve a multi-agent coverage problem in which each agent has constraints on speed, lateral acceleration, and turning rate.
TOPICS: State feedback
Chih-Lyang Hwang and Yunta Lee
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039277
Owing to the hierarchical architecture of the derived model of the omni-direction autonomous ground vehicle (OD-AGV), the virtual desired trajectory (VDT) is first designed by the 1st switching surface, which is set as the linear dynamic pose error of the OD-AGV. In sequence, the trajectory tracking control (TTC) is designed by the 2nd switching surface, which is the linear dynamic tracking error of the VDT. To deal with nonlinear time-varying uncertainties including system disturbance and different ground conditions, enhanced fuzzy 2nd order variable structure control (EF2VSC) is designed into both VDT and TTC. Finally, the experiments for tracking the circular trajectories with different curvatures, traveling velocities, and poses of the OD-AGV are presented to validate the effectiveness and robustness of the proposed hierarchical enhancement using fuzzy 2nd order variable structure control (HEF2VSC).
TOPICS: Design, Vehicles, Automated guided vehicles, Trajectories (Physics), Errors, Robustness, Tracking control, Uncertainty
Noah Manring and Muslim Ali
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039282
The objectives of this research are to explore the inertial-torque characteristics of an inline, internal combustion engine with connecting-rod joints that are evenly spaced about the centerline of the crankshaft, and to evaluate the goodness of a mass approximation that is customarily used in machine design textbooks. In this research the number of pistons within the internal combustion engine is varied from 1 to 8. In order to generalize the results, the inertial-torque equations are nondimensionalized and shown to depend upon only four nondimensional groups, all related to the mass and geometry properties of the connecting rod. As shown in this research, the inertial-torque imbalance is greatest for an engine with 2 pistons, and that a dramatic reduction in the torque imbalance may be obtained for engine designs that use 4 or more pistons. It is also shown in this paper that the customary mass approximations for the connecting rod may be used to simplify the analysis for all engine designs without a significant loss of modeling accuracy.
TOPICS: Internal combustion engines, Modeling, Approximation, Torque, Pistons, Engine design, Geometry, Machine design, Engines
Chun-Feng Huang, Bang-Hao Dai and T.-J. Yeh
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039280
This paper proposes a sensor fusion algorithm to determine the motor torque for power-assist electric bicycles. Instead of using torque sensors to directly measure the pedaling torque, outputs from a wheel encoder and a 6-axis inertial measurement unit are processed by the fusion algorithm to estimate the slope angle of the road and the longitudinal acceleration of the bicycle for conducting mass compensation, gravity compensation and friction compensation. The compensations allow the ride of the electric bicycle on hills to be as effortless as the ride of a plain bicycle on the level ground regardless the weight increase by the battery and the motor. The sensor fusion algorithm is basically an observer constructed on the kinematic model which describes the time-varying characteristics of the gravity vector observed from a frame moving with the bicycle. By exploiting the structure of the observer model, convergence of the estimation errors can be easily achieved by selecting two constant, sub-gain matrices in spite of the time-varying characteristics of the model. The validity of the sensor fusion is verified by both numerical simulations and experiments on a prototype bicycle.
TOPICS: Torque, Sensors, Bicycles, Engines, Motors, Algorithms, Gravity (Force), Friction, Measurement units and standards, Computer simulation, Weight (Mass), Kinematics, Engineering prototypes, Errors, Roads, Wheels, Batteries
Technical Brief  
Oscar S. Salas and Jesus DeLeon
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039279
In this work, the synchronization of a group of heterogeneous uncertain nonlinear systems is addressed. A strategy based on Adaptive Super Twisting Algorithm (ASTA) is proposed, in order to synchronize the outputs of the heterogeneous systems. With the aim of implementing the proposed control strategy, unmeasurable states are estimated by means of High-Order Sliding Modes Differentiators. This control scheme increases robustness against unknown dynamics and disturbances, whose bounds are not required to be known. Finally, experimental results for synchronizing a heterogeneous system platform, constituted by an Inertial Stabilization Platform and a Helicopter of 2-DOF, are used to illustrate the performance of the proposed control scheme.
TOPICS: Nonlinear systems, Synchronization, Robustness, Dynamics (Mechanics), Algorithms
Technical Brief  
Michael Hauser, Yiwei Fu, Shashi Phoha and Dr. Asok Ray
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039281
This paper makes use of long short-term memory (LSTM) neural networks for forecasting probability distributions of time series in terms of discrete symbols that are quantized from real-valued data. The developed framework formulates the forecasting problem into a probabilistic paradigm. The proposed method is different from standard formulations (e.g. autoregressive moving average) of time series modeling. The main advantage of formulating the problem in the symbolic setting is that density predictions are obtained without any significantly restrictive assumptions (e.g. second order statistics). The efficacy of the proposed method has been demonstrated by forecasting probability distributions on chaotic time series data collected from a laboratory-scale experimental apparatus. Three neural architectures are compared, each with 100 different combinations of symbol-alphabet size and forecast length, resulting in a comprehensive evaluation of their relative performances.
TOPICS: Density, Modeling, Architecture, Artificial neural networks, Statistical distributions, Time series, Statistics as topic
Youngsun Nam, Inyoung Jang, Cheongyo Bahk, Dongjun Lee, Jaehyun Kim and Han Ho Song
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039210
We propose a novel modeling, estimation and control framework for homogeneous charge compression ignition (HCCI) engines, which, by utilizing direct in-cylinder pressure sensing, can detect, and react to, the wide spectrum of combustion, thereby, allowing for the prevention, or even recovery from, partial burn or misfire, while significantly improving the stability of transition control. For this, we first develop a discrete-time cyclic control-oriented model of the HCCI process, for which we completely replace the Arrhenius integral by quantities based on the in-cylinder pressure sensing. We then propose a nonlinear state feedback control based on the exact feedback linearization and the switching linear quadratic regulators, and also present how the state and other quantities necessary for this control can be estimated by using the in-cylinder pressure sensing. We also provide a new modeling approach for heat transfer, which, through principal component analysis, can systematically allow us to choose most significant variables, thereby, substantially improving control and estimation precision. Simulation studies using a continuous-time detailed HCCI engine model built on MATLAB/Simulink and Cantera Toolbox are also performed to demonstrate the efficacy of our proposed framework for the scenarios of engine load transition and partial burn recovery with the enlarged regions-of-attraction with less stringent actuation limitation also shown.
TOPICS: Pressure, Modeling, Cylinders, Homogeneous charge compression ignition engines, Engines, Simulation, Stress, Feedback, Matlab, Principal component analysis, State feedback, Stability, Heat transfer, Combustion
Flah Aymen, Martin Novak and Sbita Lassaad
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039212
The paper presents an improved speed estimator for a permanent magnet synchronous motor (PMSM). It focuses on Hybrid Electric Vehicles (HEV). The speed estimator is based on reactive power Model Reference Adaptive System (Q-MRAS). The MRAS parameters are tuned using Particle Swarm Optimization (PSO) algorithms. The proposed method has been experimentally verified with a 100kW, 5000 RPM PMSM and a good agreement between the measured speed and the estimated speed is found. It is shown that the proposed method is able to handle the transition into the flux weakening mode without any problem.
TOPICS: Engines, Motors, Permanent magnets, Algorithms, Optimization, Hybrid electric vehicles, Particle swarm optimization
Yi Huo and Fengjun Yan
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039216
This paper proposes an energy management strategy for a Hybrid Electric Vehicle with a turbocharged diesel engine. By introducing turbocharger to the HEV powertrain, air path dynamics of engine becomes extremely complex and critical to engine torque response during transient processes. Traditional strategy that adopts steady-state-map based engine model may not work properly in this situation as a result of its incapability of accurately capturing torque response. Thus, in this paper a physical-law based air path model is utilized to simulate turbo lag phenomenon and predict air charge in cylinder. Meanwhile, engine torque boundaries are obtained on basis of predicted air charge. A receding horizon structure is then implemented in optimal supervisory controller to generate torque split strategy for the HEV. Simulations are conducted for three cases: the first one is rule-based torque-split energy management strategy without optimization; the second one is online optimal control strategy using map-based engine model; third one is online optimal control strategy combining air path loop model. The comparison of the results shows that the proposed third method has the best fuel economy of all and demonstrates considerable improvements of fuel saving on the other two methods.
TOPICS: Diesel engines, Energy management, Torque, Engines, Turbochargers, Optimal control, Optimization, Cylinders, Transients (Dynamics), Engineering simulation, Corporate average fuel economy, Simulation, Control equipment, Fuels, Physical laws, Hybrid electric vehicles, Fuel efficiency, Dynamics (Mechanics)
Dawei Pi, Xianhui Wang, Hongliang Wang and Zhenxing Kong
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039185
In this paper, a hierarchical control logic for 2-channel hydraulic active roll control (ARC) system, which includes vehicle level control and actuator level control is proposed. Vehicle level control consists of anti-roll torque controller and anti-roll torque distributor. The anti-roll torque controller is designed with 'PID+feedforward' algorithm to calculate the total anti-roll moment. The anti-roll torque distributor is devised based on fuzzy control method to implement an anti-roll moment allocation between the front and rear stabilizer bar. Actuator level control is designed based on pressure and displacement respectively. The contrastive analysis of the two proposed actuator control method is presented. The hardware-in-the-loop (HIL) test platform is proposed to evaluate the performance of the devised control algorithm. The HIL simulation result illustrates that actuator displacement control could generate a relatively accurate anti-roll moment, and the vehicle roll stability, yaw stability can be enhanced by the proposed ARC control method.
TOPICS: Torque, Pressure, Stability, Control systems, Control equipment, Hardware, Fuzzy control, Actuators, Algorithms, Vehicles, Displacement, Simulation results, Yaw, Control algorithms
Agees Kumar C, Saranya Rajeshwaran and Kanthaswamy G
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039186
This paper compares the effectiveness of the proposed hybrid metaheuristic algorithms for a class of unstable systems with time delay to that of the existing ones. The local search and global methods of optimization are combined to yield more effective hybrid metaheuristic algorithms. These algorithms are used to tune the PID controllers, satisfying the robust stabilizing Vector Gain Margin (VGM). Six global heuristic algorithms namely Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Biogeography Based Optimization (BBO), Population Based Incremental Learning (PBIL), Evolution Strategy (ES) and Stud Genetic Algorithms (StudGA) are combined with the local search property of derivative free optimization methods such as Simplex Derivative Pattern Search (SDPS) and Implicit Filtering (IMF) to yield hybrid metaheuristic algorithms. The efficacy of the proposed control schemes in terms of various time domain specifications and stabilizing VGM are compared with some existing methods for Unstable Process with Time Delay (UPTD) systems. The performance of the proposed control schemes, particularly in the context of uncertainty in the plant is demonstrated using a case study. The efficacy of the proposed control scheme is illustrated with a non-transfer function based multi body vehicle auto steer control design problem.
TOPICS: Control equipment, Algorithms, Design, Optimization, Delays, Particle swarm optimization, Uncertainty, Genetic algorithms, Vehicles, Filtration
Fengchen Wang and Yan Chen
J. Dyn. Sys., Meas., Control   doi: 10.1115/1.4039187
In this paper, a novel active yaw stabilizer (AYS) system is proposed for improving vehicle lateral stability control. The introduced AYS, inspired by the recent in-wheel motor technology, has two degrees of freedom with independent self-rotating and orbiting movements. The dynamic model of the AYS is first developed. The capability of the AYS is then investigated to show its maximum generation of corrective lateral forces and yaw moments, given a limited vehicle space. Utilizing the high-level Lyapunov based control design and the low-level control allocation design, a hierarchical control architecture is established to integrate the AYS control with active front steering (AFS) and direct yaw moment control (DYC). To demonstrate the advantages of the AYS, generating corrective lateral force and yaw moment without relying on tire road interaction, double lane change maneuvers are studied on road with various tire road friction coefficients. Co-simulation results, integrating CarSimĀ® and MATLAB/SimulinkĀ®, successfully demonstrate that the vehicle with the assistance of the AYS system has better lateral dynamics stabilizing performance, compared with cases in which only AFS or DYC is applied.
TOPICS: Dynamics (Mechanics), Stability, Vehicles, Yaw, Roads, Tires, Design, Dynamic models, Wheels, Matlab, Friction, Engines, Motors, Simulation, Degrees of freedom

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