Design and analysis of control strategies for vehicle platooning
This paper presents a novel vehicle platoon control algorithm using Vehicle to Vehicle (V2V) and ... more This paper presents a novel vehicle platoon control algorithm using Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) wireless communications between platoon members. A platoon forms a chain of vehicles (e.g., trucks) for improved traffic and fuel efficiency. Platooning algorithms aim to maintain small inter-vehicular distance between vehicles under dynamic driving conditions like acceleration and deceleration. The random delay and dropped messages have a pronounced impact on the control algorithm especially in a congested communication network. In this work, a decentralized platooning control strategy is proposed such that each vehicle can independently switch between multiple controller strategies dependent on communication topologies or the pattern of information exchange from vehicles in-front. The control strategy takes into account V2V communication delay of up to 100ms. In order to overcome the impact of dropped messages a predictive control scheme is proposed. We show the existence of well-known Common Quadratic Lyapunov Function (CQLF), to prove the stability of this switched system. Simulation results show that the proposed control algorithm maintains stability and can keep the inter-vehicle gap deviation less than ±6.3% under imperfect communication conditions for a sinusoidal acceleration input between ±2m/s2.
In this work, a prognostics framework to predict the evolution of damage in fiber-reinforced comp... more In this work, a prognostics framework to predict the evolution of damage in fiber-reinforced composites materials under fatigue loads is proposed. The assessment of internal damage thresholds is a challenge for fatigue prognostics in composites due to inherent uncertainties, existence of multiple damage modes, and their complex interactions. Our framework, considers predicting the balance of release strain energies from competing damage modes to establish a reference threshold for prognostics. The approach is demonstrated on data collected from a run-to-failure tension-tension fatigue experiment measuring the evolution of fatigue damage in carbon-fiber-reinforced polymer (CFRP) cross-ply laminates. Results are presented for the prediction of expected degradation by micro-cracks for a given panel with the associated uncertainty estimates.
Induction motors are the workhorses of industries. Indirect vector control scheme has been prefer... more Induction motors are the workhorses of industries. Indirect vector control scheme has been preferred due to its superior dynamic performance. Since the conventional PI controller has bounded operating limits and poor transient response, a search for an alternative controller arises. Recently, Artificial Neural Network (ANN) is gaining momentum as a controller for non linear systems. Herein an artificial neural network controller has been designed for a vector controlled induction motor drive. The complete drive system is modeled in Matlab / Simulink. The drive results have been analyzed for both steady state and dynamic conditions. The results are presented with the traditional PI controller and the proposed ANN controller. It is evident from the results that the proposed ANN controller gives promising results.
Induction motors are the workhorses of industries. Indirect vector control scheme has been prefer... more Induction motors are the workhorses of industries. Indirect vector control scheme has been preferred due to its superior dynamic performance. Since the conventional PI controller has bounded operating limits and poor transient response, a search for an alternative controller arises. Recently, Artificial Neural Network (ANN) is gaining momentum as a controller for non linear systems. Herein an artificial neural network controller has been designed for a vector controlled induction motor drive. The complete drive system is modeled in Matlab / Simulink. The drive results have been analyzed for both steady state and dynamic conditions. The results are presented with the traditional PI controller and the proposed ANN controller. It is evident from the results that the proposed ANN controller gives promising results.
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Papers by Apoorv Saxena