Showing 6 results for Chehardoli
H. Chehardoli, M.r. Homainezhad,
Volume 7, Issue 3 (9-2017)
Abstract
This paper studies the longitudinal control of a group of vehicles following a lead vehicle. A
neighbor based upper level controller is proposed by considering communication delay and
actuator lag. Constant spacing policy is used between successive vehicles. Two different
approaches based on Lyapunov-Razumikhin and Lyapuniv-Krassovski theorems are presented to
stability analysis of closed loop dynamic. By simulation studies, it will be shown that the second
approach is less conservatism than the first one. We consider the bidirectional leader following
(BDLF) topology for inter-vehicle communication. Based on this structure, some sufficient
conditions assuring string stability of platoon is derived. At the end of paper, four different
scenarios are presented to study the robustness of algorithm against communication delay,
actuator lag, disturbance, heterogeny and communication losses.
Dr Hossein Chehardoli, Dr Ali Ghasemi, Mr Mohammad Daneshyian,
Volume 10, Issue 4 (12-2020)
Abstract
A new safe optimal consensus procedure is presented to guarantee the asymptotic and string stability as well as crash avoidance of large-scale non-identical traffic flow. Since time delay is an inherent characteristic of physical actuators and sensors, measurement delay and lags are involved in the upper level control structure. A third-order linear model is employed to define the 1-D motion of each automated vehicle (AV) and the constant time headway plan is employed to regulate the inter-AV distance. It is assumed that the network structure is decentralized look ahead (DLA) and each AV has access to relative position and velocity regarding with the front AV. A linear control law is introduced for each AV and by performing the stability analysis in frequency domain, the necessary conditions guaranteeing string stability and crash avoidance for large-scale traffic flow are derived. Afterwards, to calculate the optimal control parameters guaranteeing the best performance, an objective function combining all mentioned conditions as well as maximum overshoot, settling time and stability margin is introduced. The genetic algorithm (GA) technique is employed to optimize the presented objective function and obtain the optimal control parameters. Various numerical results are proposed to demonstrate the efficiency of this method.
Dr Hossein Chehardoli,
Volume 11, Issue 3 (9-2021)
Abstract
This paper considers the asymptotic zero tracking error as well as string stability of large-scale automated vehicle convoys (LAVC). Both centralized and decentralized bi-directional network topologies are investigated. A double integrator dynamical equation is defined to describe the 1-D dynamics of automated vehicles (AV). A centralized / decentralized controller which employs the relative displacement and velocity compared with the backward and forward AVs is defined for all following AVs. Since the dynamical equation of LAVC is hard to be analyzed for internal stability, a PDE-based approach is introduced to decouple and reduce the closed-loop dynamical equation. According to this approach, we will be able to decouple the dynamical equation of all AVs individually based on the error dynamics. After simplifying the dynamical equation of LAVC, the conditions satisfying the internal stability of centralized and decentralized networks are obtained. After that, algebraic analyses in frequency domain will able us to find the constraints on control gains guaranteeing the string stability. Simulation and experimental results are available to describe the merits of this algorithm.
Hossein Chehardoli,
Volume 12, Issue 2 (6-2022)
Abstract
The adaptive size-independent consensus problem of uni-directional (UD) and bi-directional (BD) decentralized large-scale vehicle convoys with uncertain dynamics has been investigated in this research work. The constant distance plan (CDP) is employed to adjust the distances between successive vehicles. We assume that only relative displacement information between adjacent vehicles is accessible (partial measurement) and other information such as relative velocity and acceleration are not provided. The stability of the convoy can be performed by the analysis of each couple of consecutive vehicles. The main objective is to design an adaptive size-independent control protocol maintaining internal and string stability based on CDP with only partial measurement. Appropriate adaptive rules are derived to estimate the uncertain dynamics by utilizing only relative displacement. It will be proved that the presented adaptive protocol assures both internal stability (asymptotic stability of closed-loop convoy) and string stability (tracking error attenuation) of large-scale decentralized UD and BD convoys under the CDP. Simulations demonstrate the efficiency of the presented control framework.
Dr Hossein Chehardoli,
Volume 13, Issue 1 (3-2023)
Abstract
In this paper, the consensus of second-order nonlinear self-driving vehicle convoys (SDVCs) is studied. We assume that each self-driving vehicle (SDV) communicates only with one front and one rear SDVs. Each SDV’s nonlinear dynamics consisting of the rolling resistance and the air drag force is a function of SDV’s speed and is investigated in SDVC’s modeling and consensus design. Since the speed is bounded, all vehicles’ nonlinearities are also bounded. Due to engine saturation of each SDV, the control input is limited. We involve this limitation by introducing the arctan(.) function to control protocol. The inter-SDV’s distances are assumed to be constant during motion. The distance tracking error associated with each SDV is defined as distance between it and the leading SDV. The error dynamics of the proposed SDVC is derived after applying the consensus law to each SDV. To prove the internal stability, the Lyapunov theorem is employed. We will prove that under this consensus algorithm, the SDVC will be internal stable. To validate the effectiveness of this method, a SDVC comprising a leading and 6 following SDVs will be studied. It will be verified that under the proposed consensus law, all the SDVs reach a unique consensus.
Dr Hossein Chehardoli,
Volume 13, Issue 3 (9-2023)
Abstract
In this article, the optimal robust H2 / H∞ control of self-driving car platoons (SDCPs) under external disturbance is investigated. By considering the engine dynamics and the effects of external disturbance, a linear dynamical model is presented to define the motion of each self-driving car (SDC). Each following SDC is in direct communication with the leader. By utilizing the relative position of following SDCs and the leader, the error dynamics of each SDC is calculated. The particle swarm optimization (PSO) method is utilized to find the optimal control gains. To this aim, a cost function which is a linear combination of H2 and H∞ norms of the transfer function between disturbance and target variables is constructed. By employing the PSO method, the cost function will be minimized and therefore, the robustness of the controller against external disturbance is guaranteed. It will be proved that under the presented robust control method, the negative effects of disturbance on system performance will significantly reduce. Therefore, the SDCP is internally stable and subsequently, each SDC tracks the motion of the leader. In order to validate the proposed method, simulation examples will be presented and analyzed.
