In this paper, a model predictive control (MPC) approach for controlling an active front steering system in autonomous vehicle is presented. At each time step, trajectory assumed to be known over finite horizon, and MPC controller computes the angle order follow on slippery roads at highest possible entry speed. We present two approaches with different computational complexities. first approach, we formulate problem by using nonlinear model. The second based successive online linearization...

We study model predictive control (MPC) schemes for discrete-time linear time-invariant systems with constraints on inputs and states, that can be formulated using a program (LP). In particular, we focus our attention performance criteria based mixed 1 -norm, namely, 1-norm respect to time -norm space. First provide method compute the terminal weight so closed-loop stability is achieved. then show optimal profile piecewise affine continuous function of initial state briefly describe...

We study the use of kinematic and dynamic vehicle models for model-based control design used in autonomous driving. In particular, we analyze statistics forecast error these two by using experimental data. addition, effect discretization on error. results first part to motivate a controller an model predictive (MPC) simple bicycle model. The proposed approach is less computationally expensive than existing methods which tire models. Moreover it can be implemented at low speeds where become...

This brief presents a model-based predictive control (MPC) approach to building cooling systems with thermal energy storage. We focus on buildings equipped water tank used for actively storing cold produced by series of chillers. First, simplified models chillers, towers, storage tanks, and are developed validated the purpose design. Then an MPC chilling system operation is proposed optimally store in using knowledge loads weather conditions. addresses real-time implementation feasibility...

This paper presents a distributed model predictive control (DMPC) algorithm for heterogeneous vehicle platoons with unidirectional topologies and priori unknown desired set point. The vehicles (or nodes) in platoon are dynamically decoupled but constrained by spatial geometry. Each node is assigned local open-loop optimal problem only relying on the information of neighboring nodes, which cost function designed penalizing errors between predicted assumed trajectories. Together this...

For discrete-time uncertain linear systems with constraints on inputs and states, we develop an approach to determine state feedback controllers based a min-max control formulation. Robustness is achieved against additive norm-bounded input disturbances and/or polyhedral parametric uncertainties in the state-space matrices. We show that finite-horizon robust optimal law continuous piecewise affine function of vector can be calculated by solving sequence multiparametric programs. When...

In this paper a novel approach to autonomous steering systems is presented. A model predictive control (MPC) scheme designed in order stabilize vehicle along desired path while fulfilling its physical constraints. Simulation results show the benefits of systematic methodology used. particular we how very effective manoeuvres are obtained as result MPC feedback policy. Moreover, highlight trade off between speed and required preview on vehicle. The concludes with highlights future research...

In this paper, we propose a path following Model Predictive Control-based (MPC) scheme utilising steering and braking. The control objective is to track desired for obstacle avoidance manoeuvre, by combined use of braking steering. proposed relies on the Nonlinear MPC (NMPC) formulation used in [F. Borrelli, et al., MPC-based approach active autonomous vehicle systems, Int. J. Veh. Autonomous Syst. 3(2/3/4) (2005), pp. 265–291.] [P. Falcone, IEEE Trans. Control Technol. 15(3) (2007),...

The building sector is the largest energy consumer in world. Therefore, it economically, socially, and environmentally significant to reduce consumption of buildings. Achieving substantial reduction buildings may require rethinking whole processes design, construction, operation a building. This article focuses on specific issue advanced control system design for efficient

We consider a set of identical decoupled dynamical systems and control problem where the performance index couples behavior systems. The coupling is described through communication graph each system node action at only function its state states neighbors. A distributed design method presented which requires solution single linear quadratic regulator (LQR) problem. size LQR equal to maximum vertex degree plus one. procedure proposed in this paper illustrates how stability large-scale related...

A learning model predictive controller for iterative tasks is presented. The reference-free and able to improve its performance by from previous iterations. safe set a terminal cost function are used in order guarantee recursive feasibility nondecreasing at each iteration. This paper presents the control design approach, shows how recursively construct state input trajectories of Simulation results show effectiveness proposed logic.

This article presents a novel method for exactly reformulating nondifferentiable collision avoidance constraints into smooth, differentiable using strong duality of convex optimization. We focus on controlled object whose goal is to avoid obstacles while moving in an n-dimensional space. The proposed reformulation exact, does not introduce any approximations, and applies general objects that can be represented as the union sets. connect our results with notion signed distance, which widely...

This paper presents a stochastic model predictive control (SMPC) approach to building heating, ventilation, and air conditioning (HVAC) systems. The HVAC system is modeled as network of thermal zones controlled by central handling unit local variable volume boxes. In the first part this paper, simplified nonlinear models are presented for components. uncertain load forecast in each zone finitely supported probability density functions (pdfs). These pdfs initialized using historical data...

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents systematic way enforcing robustness during the MPC design stage. A nonlinear model predictive controller (RNMPC) is used to help driver navigating vehicle in order avoid obstacles track road centre line. force-input bicycle developed RNMPC design. invariant set guarantee that state input constraints are satisfied presence disturbances error. Simulations...

We present a framework for autonomous driving which can learn from human demonstrations, and we apply it to the longitudinal control of an car. Offline, model car-following strategies set example sequences. Online, is used compute accelerations replicate what driver would do in same situation. This reference acceleration tracked by predictive controller enforces comfort safety constraints before applying final acceleration. The designed be robust uncertainty predicted motion preceding...

This paper presents a novel approach in train control systems based on the concept called virtual coupling or convoys. follows recent developments field of safe platooning autonomous vehicles. We use decentralized model predictive (MPC) framework for each participating convoy formation. Control designs leading and following trains are presented. An optimal formulation both controllers is used its design relies numeric solution finite horizon problem. compares proposed method with alternative...

This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of signal timing signalized intersections road is considered. eco-driving formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) defined random variable, describes feasible passing time through intersections. Usually, true probability distribution ERD unknown. Consequently, approach adopted...

This paper describes a hybrid model and predictive control (MPC) strategy for solving traction problem. The problem is tackled in systematic way from modeling to synthesis implementation. described first the Hybrid Systems Description Language obtain mixed-logical dynamical (MLD) of open-loop system. For resulting MLD model, we design receding horizon finite-time optimal controller. controller converted its equivalent piecewise affine form by employing multiparametric programming techniques,...

Abstract A model predictive control (MPC) approach for controlling an active front steering (AFS) system in autonomous vehicle is presented. At each time step a trajectory assumed to be known over finite horizon, and MPC controller computes the angle order best follow desired on slippery roads at highest possible entry speed. We start from results presented ( Int. J. Veh. Auton. Syst. 2005; 3 (2–4):265–291; IEEE Trans. Contr. Technol. 2007; 15 (3)) formulate problem based successive online...