This paper provides a comprehensive tutorial on a family of Model Predictive control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision ...
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Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem ...
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This paper develops a physics-informed neural network (PINN) for learning the parameters of commercially implemented adaptive cruise control (ACC) systems. The constant time-headway policy (CTHP) is adopted to emulate...
This paper develops a physics-informed neural network (PINN) for learning the parameters of commercially implemented adaptive cruise control (ACC) systems. The constant time-headway policy (CTHP) is adopted to emulate the core functionality of stock ACC systems (proprietary control logic and its parameters) which is not publicly available. Multi-layer artificial neural networks is a class of universal approximators, and thus the developed PINN can serve as a surrogate approximator to capture the longitudinal dynamics of ACC-engaged vehicles and efficiently learn the unknown parameters of the CTHP. The ability of the PINN to infer the unknown ACC parameters is tested on both synthetic and empirical data of space-gap and relative velocity involved ACC-engaged vehicles in platoon formation. The results have demonstrated the superior predictive ability of the proposed PINN to learn the unknown design parameters of stock ACC systems of different vehicle makes. The set of ACC model parameters obtained from the PINN revealed that the stock ACC system of the considered vehicles in three experimental campaigns is neither $\mathcal{L}_{2}$ nor $\mathcal{L}_{\infty}$ string stable.
Automation of ship maneuvering in limited sailing conditions usually requires 100% redundancy of thrusters (THRs) of various modifications and their locations in accordance with the matrix. The hierarchy of the motion...
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The load on a power station varies from time to time due to uncertain demands of the consumers and is known as variable load on the station. Also it is known to have an effect on the performance of a power system stab...
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This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA...
This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA extension set designed for configuring and driving up to 32 PWM signals. The extension is integrated into RiscPwm, an updated version of our previous work, the RisCanFd SoC, for taking advantage of CAN-FD, a massively used protocol in the areas of automation and mobility. Being configured with the dedicated ISA extension or with parameters directly extracted from CAN-FD commands, the proposed solution manages to configure/reconfigure PWM channels between 4.79x and 9.18x times faster than an ARM Cortex-M7 processor, although our SoC operates with a 6x lower frequency.
This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as po...
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We consider distributionally robust optimal control of stochastic linear systems under signal temporal logic (STL) chance constraints when the disturbance distribution is unknown. By assuming that the underlying predi...
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This paper investigates the problem of maximizing social power for a group of agents, who participate in multiple meetings described by independent Friedkin-Johnsen models. A strategic game is obtained, in which the a...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
This paper investigates the problem of maximizing social power for a group of agents, who participate in multiple meetings described by independent Friedkin-Johnsen models. A strategic game is obtained, in which the action of each agent (or player) is her stubbornness over all the meetings, and the payoff is her social power on average. It is proved that, for all but some strategy profiles on the boundary of the feasible action set, each agent's best response is the solution of a convex optimization problem. Furthermore, even with the non-convexity on boundary profiles, if the underlying networks are given by a fixed complete graph, the game has a unique Nash equilibrium. For this case, the best response of each agent is analytically characterized, and is achieved in finite time by a proposed algorithm.
Integrating Automated Vehicles (AVs) into everyday traffic is an ongoing challenge. Ensuring the safety of all involved agents, even in the presence of system failures, is crucial, especially in urban environments. Th...
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