In this article, we propose an event‐triggered output‐feedback controller that guarantees the simultaneous stabilization of traffic flow on two connected roads. The density and velocity traffic ...dynamics are described with the linearized Aw‐Rascle‐Zhang macroscopic traffic partial differential equation model, which results in a coupled hyperbolic system. The control objective is to simultaneously stabilize the upstream and downstream traffic to a given spatially uniform constant steady‐state that is in the congested regime. To suppress stop‐and‐go traffic oscillations on the cascaded roads, we consider a ramp metering strategy that regulates the traffic flow rate entering from the on‐ramp to the mainline freeway. The ramp metering is located at the outlet with only boundary measurements of flow rate and velocity. Under the event‐triggered scheme, the control signal is only updated when an event triggering condition is satisfied. Compared with the continuous input signal, the event‐triggered boundary output control presents a more realistic setting to implement by ramp metering on a digital platform. The event‐triggered control design relies on the emulation of the backstepping boundary output feedback and on a dynamic event‐triggered strategy to determine the time instants at which the control value must be updated. We prove that there is a uniform minimal dwell‐time (independent of initial conditions), thus avoiding the Zeno phenomenon. We guarantee the exponential convergence of the closed‐loop system under the proposed event‐triggered control. A numerical example illustrates the results.
We consider the problem of constructing optimal decentralized controllers. We formulate this problem as one of minimizing the closed-loop norm of a feedback system subject to constraints on the ...controller structure. We define the notion of quadratic invariance of a constraint set with respect to a system, and show that if the constraint set has this property, then the constrained minimum-norm problem may be solved via convex programming. We also show that quadratic invariance is necessary and sufficient for the constraint set to be preserved under feedback. These results are developed in a very general framework, and are shown to hold in both continuous and discrete time, for both stable and unstable systems, and for any norm. This notion unifies many previous results identifying specific tractable decentralized control problems, and delineates the largest known class of convex problems in decentralized control. As an example, we show that optimal stabilizing controllers may be efficiently computed in the case where distributed controllers can communicate faster than their dynamics propagate. We also show that symmetric synthesis is included in this classification, and provide a test for sparsity constraints to be quadratically invariant, and thus amenable to convex synthesis.
This paper investigates platoon control of vehicles via the wireless communication network. An integrated longitudinal and lateral control approaches for vehicle platooning within a designated lane ...is proposed. Firstly, the longitudinal control aims to regulate the speed of the follower vehicle on the leading vehicle while maintaining the inter-distance to the desired value which may be chosen proportional to the vehicle speed. Thus, based on Lyapunov candidate function, sufficient stability conditions formulated in BMIs terms are proposed. For the general objective of string stability and robust platoon control to be achieved simultaneously, the obtained controller is complemented by additional conditions established for guaranteeing string stability. Furthermore, constraints such as actuator saturation, and controller constrained information are also considered in control design. Secondly, a multi-model fuzzy controller is developed to handle the vehicle lateral control. Its objective is to maintain the vehicle within the road through steering. The design conditions are strictly expressed in terms of LMIs which can be efficiently solved with available numerical solvers. The effectiveness of the proposed control method is validated under the CarSim software package.
To improve the underwater control effect of a Remotely Operated Vehicle (ROV) with residual buoyancy, current disturbance, and control dead zone, the depth and heading combined control of ROV is ...studied to improve the control accuracy of the control system. First, the heading control with fixed depth is divided into heading control and depth control. The tanh‐sigmoid‐surface control laws for designed degrees of freedom are designed by using tanh function. To suppress the influence of residual buoyancy and control law dead zone in depth control, and to offset the influence of control law dead zone of ROV thruster control, a reserved control quantity is introduced to map the depth deviation and control dead zone with residual buoyancy into a control deviation quantity. An adaptive amplification factor method is proposed for the amplification factors of depth control, speed control, and heading control. The proportional coefficient is adopted to make that the balance among rise time, convergence speed, and overshoot can be achieved by adjusting the proportional coefficient. Then the corresponding tanh‐sigmoid‐surface controller module is designed in MOOS‐IvP environment to track the desired heading and depth. The proposed controller refines fuzzy rules and reduces the complexity of parameter adjustment. Compared with the classical proportional, integral, and derivative control method, the experiment results show that the proposed method can resist the influence of residual buoyancy, current disturbance, and control dead zone and has a better control effect with less control error in depth and heading determination.
Summary
In a real‐time hybrid simulation, a transfer system is used to enforce the interface interaction between computational and physical substructures. A model‐based, multilayer nonlinear control ...system is developed to accommodate extensive performance variations and uncertainties in a physical substructure. The aim of this work is to extend the application of real‐time hybrid simulation to investigating failure, nonlinearity, and nonstationary behavior. This Self‐tuning Robust Control System (SRCSys) consists of two layers: robustness and adaptation. The robustness layer synthesizes a nonlinear control law such that the closed‐loop dynamics perform as intended under a broad range of parametric and nonparametric uncertainties. Sliding mode control is employed as the control scheme in this layer. Then, the adaptation layer reduces uncertainties at run time through slow and controlled learning of the control plant. The tracking performance of the SRCSys is evaluated in two experiments that have highly uncertain physical specimens.
This paper examines the practical design issues of sliding-mode (SM) controllers as applied to the control of dc-dc converters. A comprehensive review of the relevant literature is first provided. ...Major problems that prevent the use of SM control in dc-dc converters for industrial and commercial applications are investigated. Possible solutions are derived, and practical design procedures are outlined. The performance of SM control is compared with that of conventional linear control in terms of transient characteristics. It has been shown that the use of SM control can lead to an improved robustness in providing consistent transient responses over a wide range of operating conditions.
A novel active disturbance rejection based repetitive learning control scheme, including three channels, namely, feedforward, feedback, and disturbance rejection channels, is investigated. The goal ...of this work is to achieve a high-quality output voltage and robustness to disturbances and uncertainties in the inverter system. The mathematics model of the inverter is replaced by a chain of two integrators to avoid model identification and time-varying parameter estimation when designing the controller. The ignored system dynamics, the uncertainties, and the nonrepetitive factors caused by nonrepetitive disturbances are all defined as part of the total disturbance to be estimated and compensated for, which decreases the controller sensitivity for the system parameters and operating environment. The stability conditions of the control system scheme along the periods are analyzed, and the mitigation of different frequency-band disturbances using the combination control scheme is demonstrated on the frequency spectrum. Finally, the algorithm is validated on a hardware platform, and the tolerability of varying parameters is tested.
We describe a framework for the design of collective behaviors for groups of identical mobile agents. The approach is based on decentralized simultaneous estimation and control, where each agent ...communicates with neighbors and estimates the global performance properties of the swarm needed to make a local control decision. Challenges of the approach include designing a control law with desired convergence properties, assuming each agent has perfect global knowledge; designing an estimator that allows each agent to make correct estimates of the global properties needed to implement the controller; and possibly modifying the controller to recover desired convergence properties when using the estimates of global performance. We apply this framework to the problem of controlling the moment statistics describing the location and shape of a swarm. We derive conditions which guarantee that the formation statistics are driven to desired values, even in the presence of a changing network topology.
This paper presents a traction control (TC) system for electric vehicles with in-wheel motors, based on explicit nonlinear model predictive control. The feedback law, available beforehand, is ...described in detail, together with its variation for different plant conditions. The explicit controller is implemented on a rapid control prototyping unit, which proves the real-time capability of the strategy, with computing times on the order of microseconds. These are significantly lower than the required time step for a TC application. Hence, the explicit model predictive controller can run at the same frequency as a simple TC system based on proportional integral (PI) technology. High-fidelity model simulations provide: 1) a performance comparison of the proposed explicit nonlinear model predictive controller (NMPC) with a benchmark PI-based traction controller with gain scheduling and anti-windup features, and 2) a performance comparison among two explicit and one implicit NMPCs based on different internal models, with and without consideration of transient tire behavior and load transfers. Experimental test results on an electric vehicle demonstrator are shown for one of the explicit NMPC formulations.
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