Model-Free Adaptive Predictive Control for an Urban Road Traffic Network via Perimeter Control

Abstract

This paper proposes a novel model-free adaptive control (MFAC) strategy for urban road traffic network via perimeter control based on dynamic linearization technique and predictive control. The accurate traffic flow model of the urban road network is replaced by equivalent data model. Based on the idea of predictive control, the current control action is obtained by solving online, at each sampling coordinate, a finite horizon closed-loop optimal control problem. The robustness of the MFAC strategy to time-varying desired vehicle accumulation, random traffic demand and macroscopic fundamental diagram (MFD) model uncertainty is verified through simulation results. INDEX TERMS MFAC, model predictive control (MPC), MFD, perimeter control, urban road traffic network.

Computationally Simple Nonlinear MPC Algorithm for Vehicle Obstacle Avoidance With Minimization of Fuel Utilization

“…, N , where c x and c i are constraint slope and constraint intercept factors, respectively. Since the constraints (19) are concerned with the predicted state variables, we also use their soft versions…”

“…Hence, there are n u N u + 3 = 2N u + 3 decision variables. Since it is straightforward that we allow violation of the original hard state constraints (17) and (19) only to find a feasible solution, it is necessary to minimize the necessary degree of violation. Hence, in the cost-function of the optimization problem (22) there are 3 penalty terms the objective of which is to keep the values of the decision variables ε min (k), ε max (k) and ε x (k) as low as possible.…”

“…First of all, MPC algorithms provide very powerful and fast low-level control of engines [14]- [16]. Secondly, MPC methods are able to manage difficult problems such as: autonomous driving [17], autonomous racing [18], urban road traffic network control [19], and traction control [21]. The most advanced MPC applications in automotive systems have complex objectives.…”

A Novel Disturbance Estimator-Enhanced Predictive Control Approach for Landing Planar Movement Control of Amphibious Airplanes

“…A predictive controller suitable for linear cascade systems is developed to deal with the sudden changes, which in turn avoids rudder surging and too large output overshoot. The predictive control methods have been applied to degrade the influences from the sudden changes theoretically and experimentally [32][33][34][35].…”

Enhancing the performance of wind energy conversion systems using unified power flow controller

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