Robust Control Techniques for State Tracking in the Presence of Variable Time Delays

Goodell, Jarrett; Compere, Marc; Simon, Miguel; Smith, Wilford; Wright, Ronnie L.; Brudnak, Mark

doi:10.4271/2006-01-1163

Cited by 15 publications

(10 citation statements)

References 3 publications

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“…In the simulation study documented previously [11], both H-infinity and Sliding mode control methodologies were evaluated along with two input vector topologies. The first input topology associated with Sliding mode used three fictitious skyhook inputs to achieve mobility state convergence.…”

Section: Control System Design Considerationsmentioning

confidence: 99%

Robust Control Techniques Enabling Duty Cycle Experiments Utilizing a 6-DOF Crewstation Motion Base, a Full Scale Combat Hybrid Electric Power System, and Long Distance Internet Communications

Compere

Goodell

Simon

et al. 2006

SAE Technical Paper Series

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The RemoteLink effort supports the U.S. Army's objective for developing and fielding next generation hybrid-electric combat vehicles. It is a distributed soldierin-the-Ioop and hardware-in-the-Ioop environment with a 6-DOF motion base for operator realism, a full-scale combat hybrid electric power system, and an operational context provided by OneSAF. The driver/gunner crewstations rest on one of two 6-DOF motion bases at the U.S. Army TARDEC Simulation Laboratory (TSL). The hybrid power system is located 2,450 miles away at the TARDEC Power and Energy System Integration Laboratory (P&E SIL). The primary technical challenge in the RemoteLink is to operate both laboratories together in real time, coupled over the Internet, to generate a realistic power system duty cycle. A topology has been chosen such that the laboratories have real hardware interacting with simulated components at both locations to guarantee local closed loop stability. This layout is robust to Internet communication failures and ensures the long distance network delay does not enter the local feedback loops. The TSL states and P&E SIL states will diverge due to (1) significant communications delays and (2) unavoidable differences between the TSL's powersystem simulation and the P&E SIL's real hardware-inthe-loop power system. Tightly coupled, bi-directional interactions exist among the various distributed simulations and software-and hardware-in-the-Ioop components representing the driver, gunner, vehicle, and power system. These interactions necessitate additional adjustment to ensure that the respective states at the TSL and P&E SIL sites converge. This is called state convergence and ensures the dominant energetic states of both laboratories remain closely matched in real time. State convergence must be performed at both locations to achieve bi-directional, real-time interaction like that found on a real vehicle. The result is a distributed control system architecture with Internet communications in the state convergence feedback loop. The Internet communication channel is a primary source of uncertainty that impacts the overall state convergence performance and stability. Multiple control schemes were developed and tested in simulation. This paper presents robust control techniques that compensate for asynchronous Internet communication delays during closed loop operation of the TSL and P&E SIL sites. The subsequent soldier-and hardware-in-the-Ioop experiments were performed using a combination of nonlinear Sliding-mode and linear PID control laws to achieve state convergence at both locations. The control system development, performance, and duty cycle results are presented in this paper.

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Section: Control System Design Considerationsmentioning

confidence: 99%

Robust Control Techniques Enabling Duty Cycle Experiments Utilizing a 6-DOF Crewstation Motion Base, a Full Scale Combat Hybrid Electric Power System, and Long Distance Internet Communications

Compere

Goodell

Simon

et al. 2006

SAE Technical Paper Series

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“…As mentioned above, the only application of ID-HILS to automotive powertrains is the work by TARDEC researchers [25,43,44]. To overcome the abovementioned challenges, they proposed an observer-based method.…”

Section: Introductionmentioning

confidence: 98%

“…Within the telerobotics literature, the possibility of achieving stable forcereflecting teleoperation over the Internet was first explored by Niemeyer and Slotine, also in 1998 [24], and attracted the attention of many other researchers [33][34][35][36][37][38][39][40][41][42]. The notion of ID-HILS did not appear in the automotive powertrain systems engineering area until 2006, when US Tank-Automotive Research, Development, and Engineering Center (TARDEC) researchers successfully integrated a ride motion simulator in Warren, MI, USA, with a hybridpower-system simulator in Santa Clara, CA, USA [25,43,44].…”

Section: Introductionmentioning

confidence: 99%

“…The integration ensured, through feedback control, that the states of the observers remained close to the actual states of the corresponding components. Different feedback control strategies were employed and analyzed, including PI [25], sliding mode, and H 1 control [43]. Duty cycle experiments have been performed successfully with this setup [44].…”

Section: Introductionmentioning

confidence: 99%

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Development and model-based transparency analysis of an Internet-distributed hardware-in-the-loop simulation platform

et al. 2011

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“…A negative aspect of distributed simulation is that delays are introduced which is an undesired property. The combination of distributed systems with real-time requirements present a particular challenge and techniques have been developed to deal with such set-ups in (Goodell et al 2006) and (Ersal et al 2011).…”

Section: Distributed Simulationmentioning

confidence: 99%

Extensions for Distributed Moving Base Driving Simulators

Andersson¹

2017

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Modern vehicles are complex systems. Different design stages for such a complex system include evaluation using models and submodels, hardwarein-the-loop systems and complete vehicles. Once a vehicle is delivered to the market evaluation continues by the public. One kind of tool that can be used during many stages of a vehicle lifecycle is driving simulators.The use of driving simulators with a human driver is commonly focused on driver behavior. In a high fidelity moving base driving simulator it is possible to provide realistic and repetitive driving situations using distinctive features such as: physical modelling of driven vehicle, a moving base, a physical cabin interface and an audio and visual representation of the driving environment. A desired but difficult goal to achieve using a moving base driving simulator is to have behavioral validity. In other words, "A driver in a moving base driving simulator should have the same driving behavior as he or she would have during the same driving task in a real vehicle.".In this thesis the focus is on high fidelity moving base driving simulators. The main target is to improve the behavior validity or to maintain behavior validity while adding complexity to the simulator. One main assumption in this thesis is that systems closer to the final product provide better accuracy and are perceived better if properly integrated. Thus, the approach in this thesis is to try to ease incorporation of such systems using combinations of the methods hardware-in-the-loop and distributed simulation. Hardware-inthe-loop is a method where hardware is interfaced into a software controlled environment/simulation. Distributed simulation is a method where parts of a simulation at physically different locations are connected together. For some simulator laboratories distributed simulation is the only feasible option since some hardware cannot be moved in an easy way.Results presented in this thesis show that a complete vehicle or hardwarein-the-loop test laboratory can successfully be connected to a moving base driving simulator. Further, it is demonstrated that using a framework for distributed simulation eases communication and integration due to standardized interfaces. One identified potential problem is complexity in interface wrappers when integrating hardware-in-the-loop in a distributed simulation framework. From this aspect, it is important to consider the model design and the intersections between software and hardware models. Another important issue discussed is the increased delay in overhead time when using a framework for distributed simulation.

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Robust Control Techniques for State Tracking in the Presence of Variable Time Delays

Cited by 15 publications

References 3 publications

Robust Control Techniques Enabling Duty Cycle Experiments Utilizing a 6-DOF Crewstation Motion Base, a Full Scale Combat Hybrid Electric Power System, and Long Distance Internet Communications

Robust Control Techniques Enabling Duty Cycle Experiments Utilizing a 6-DOF Crewstation Motion Base, a Full Scale Combat Hybrid Electric Power System, and Long Distance Internet Communications

Development and model-based transparency analysis of an Internet-distributed hardware-in-the-loop simulation platform

Extensions for Distributed Moving Base Driving Simulators

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