Information about the vehicle states (e.g. the sideslip angle and the longitudinal velocity), tire forces, and tire-road friction coefficients is crucial for advanced vehicular active safety systems. In particular, th...
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Information about the vehicle states (e.g. the sideslip angle and the longitudinal velocity), tire forces, and tire-road friction coefficients is crucial for advanced vehicular active safety systems. In particular, the latest high-performance control system based on optimally distributing and controlling all tire forces requires feedback of the tire forces and the tire-road friction coefficient of each individual tire. Therefore, estimating all or parts of the vehicle/tire/road states from available sensor measurements in production vehicles has long been an active research topic in both academia and industry. Despite recent advances in automotive estimation technologies, it remains an open question on identifying the tire-road friction coefficient of each individual tire. This paper proposes an integrated estimation system that provides accurate estimates of the vehicle/tire/road states from available sensor measurements. More importantly, the tire-road friction coefficient of each tire can be separately estimated. The performance of the proposed estimation system is verified by simulations based on a complex nonlinear vehicle/ tire model.
Performance of constrained movements in multiple directions of a workspace simultaneously and in presence of uncertainty is a great challenge for robots. Achieving such tasks by employing control policies which are fu...
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ISBN:
(纸本)9781479947287
Performance of constrained movements in multiple directions of a workspace simultaneously and in presence of uncertainty is a great challenge for robots. Achieving such tasks by employing control policies which are fully determined a priori and do not take into account the system uncertainty can cause undesired stress on the robot end-effector or the environment and result in poor performance. Instead, a sophisticated control policy is required, which can adjust to the varying conditions of a task while taking into account the coupling of motion dynamics between different directions of movement. To this aim, in this paper, we propose a MIMO Extremum Seeking control (ESC)-Model Reference Adaptive control (MRAC) approach with the view of executing fine motion tasks in presence of uncertain task dynamics. ESC enhances robustness of the system to non-parametric uncertainties compared to single MRAC. The proposed approach ensures state tracking as well as optimization of a global state-dependent cost criterion in all directions of movement. We evaluate our approach in simulations and in a real-world robotic engraving task.
Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of ...
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ISBN:
(纸本)9781479938414
Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of Learning Automata to select only the optimal action out of a set of actions, this paper considers a multiple-action selection problem and proposes a novel class of Learning Automata for selecting an optimal subset of actions. Their objective is to identify the optimal subset: the top k out of r actions. Based on conventional continuous pursuit and discretized pursuit learning schemes, this paper introduces four pursuit learning schemes for selecting the optimal subset, called continuous equal pursuit, discretized equal pursuit, continuous unequal pursuit and discretized unequal pursuit learning schemes, respectively. In conjunction with a reward-inaction learning paradigm, the above four schemes lead to four versions of pursuit Learning Automata for selecting the optimal subset. The simulation results present a quantitative comparison between them.
In this paper, we study a transmit null-steering beamforming problem for wireless sensor networks in uncertain communication environment. Given a desired receiver direction,the system requires to avoid the unknown eav...
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In this paper, we study a transmit null-steering beamforming problem for wireless sensor networks in uncertain communication environment. Given a desired receiver direction,the system requires to avoid the unknown eavesdroppers as *** this case, we adjust both the sensors distribution and phase offsets such that beamforming is achieved at the desired direction,and meanwhile the communication of all the other directions is suppressed, which substantially reduces the risk of information theft by eavesdroppers. The Particle Swarm Optimization（PSO）algorithm is used to solve this constraint problem.
This paper proposes a new algorithm to eliminate the wiper interference in a vehicle's onboard video to improve the detection rate of vision-based Advanced Driver Assistance Systems (ADAS), such as Forward Collisi...
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This paper proposes a new algorithm to eliminate the wiper interference in a vehicle's onboard video to improve the detection rate of vision-based Advanced Driver Assistance Systems (ADAS), such as Forward Collision Warning (FCW) Systems. During raining days, the windshield wipers periodically and partially block the appearance of obstacles on the road that are to be detected in these early warning systems, and hence, impair their performance. The wiper pixels could be in-painted via (1) localizing the pixels belonging to the wipers and (2) replacing the wiper pixels with non-wiper pixels extracted from an adjacent video frame with no such blockage. Finally, since it is impossible to obtain the images captured in the same scenario with and without wiper interference, a quantitatively analyzing framework which blends wipers into non-wiper images is also proposed to quantitatively assess the detection rate of data with wipers, without wipers and with wipers but eliminated by our algorithm. The experimental results show that the wiper pixels being segmented and in-painted blend in unobtrusively with the surrounding pixels and the FCW detection rate is indeed improved.
In this paper, we investigate fundamental limits for physical implementations of the Kalman-Bucy filter for state estimation of a class of linear port-Hamiltonian systems. In particular, for the studied class of syste...
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In wireless sensor networks （WSNs）, as the shared nature of the wireless medium, jam- ming attacks can be easily launched and result in a great damage to the network. How to deal with jamming attacks has become a gr...
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In wireless sensor networks （WSNs）, as the shared nature of the wireless medium, jam- ming attacks can be easily launched and result in a great damage to the network. How to deal with jamming attacks has become a great concern recently. Finding the location of a jammer is important to take security actions against the jammer, and thus to restore the network communication. After a comprehensive study on the jammer localization problem, a lightweight easy-operated algorithm called triple circles localization （TCL） is proposed. The evaluation results have demonstrated that, compared with other approaches, TCL achieves the best jammer localization accuracy under variable conditions.
Application servers (AS) of virtualized platform may suffer from software aging problem. In this paper, we first formulate the system model including three virtual machines. Two of them act as the main servers, and th...
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Application servers (AS) of virtualized platform may suffer from software aging problem. In this paper, we first formulate the system model including three virtual machines. Two of them act as the main servers, and the third machine acts as the backup node. The motivation of our formulated model is that the relationship between the service provider and the service maintainer is collaborative as well as having different goals between them, the service provider as a leader wants to maximize his system availability, while the service maintainer wants to minimize his maintenance cost. Thus, the problem of maximizing availability and minimizing cost between the service provider and service maintainer is Stackelberg game based. Next, we assume that the AS degradation is caused by resource consumption due to memory leaks for the AS on the active VMs, and we present the system degradation states based on Markov renewal processes. We give the analytical definitions of threshold levels for R alert at each VM, which are used to determine the optimal rejuvenation schedules. In addition, we obtain the steady-state availability expressions for the system and the mean maintenance cost. Finally, we give the Stackelberg strategy with the open-loop information and the solutions for the game theory by a numerical illustration.
This paper deals with the fault detection problem for nonlinear uncertain non-affine systems. The variable-structure output-feedback stabilization based on observer is required. Depending on the type of uncertainties,...
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This paper deals with the fault detection problem for nonlinear uncertain non-affine systems. The variable-structure output-feedback stabilization based on observer is required. Depending on the type of uncertainties, conditions are given under which convergence to the unique solution of both the system and the observer, and fault detection are achieved. Simulation results illustrate the feasibility of the proposed approach.
As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intellige...
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As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.
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