This paper introduces the concept of Receding Horizon Control (RHC) to Genetic Algorithm (GA) for real-time implementations in dynamic environments. The methodology of the new GA is presented with the emphases on how to effectively integrate the RHC strategy by following some RHC practices in control engineering, particularly, how to choose the length of receding horizon and how to design termi...

This paper presents a receding-horizon leader-follower (RH-LF) controller for addressing the formation control problem of multiple nonholonomic mobile robots. The issues to be investigated include separation, bearing, and orientation deviation control between the leader and the followers, where the orientation deviation control is especially important to control precision. After the leader-foll...

In this paper, a real-time distributed economic model predictive control approach for complete vehicle energy management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving several smaller optimization problems. The receding horizon control problem is formulated with va...

In this paper, we propose a new receding horizon disturbance attenuator (RHDA) for Takagi-Sugeno (T-S) fuzzy switched Hopfield neural networks with external disturbance. First, a new set of linear matrix inequality (LMI) conditions is proposed for the finite terminal weighting matrix of the receding horizon cost function with a cross term. Second, under this condition, we show that the proposed...

In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets. Feasibility and stability guarantees for the approximate control law are given using reachability analysis, where interval methods are used...

We introduce ARES, an efficient approximation algorithm for generating optimal plans (action sequences) that take an initial state of a Markov Decision Process (MDP) to a state whose cost is below a specified (convergence) threshold. ARES uses Particle Swarm Optimization, with adaptive sizing for both the receding horizon and the particle swarm. Inspired by Importance Splitting, the length of t...

Abstract: The paper deals with design and realization problems of collision avoidance systems (CAS) of cars (ground vehicles). CAS emergency path design is based on the principle of elastic band with improved reaction forces for road borders and static obstacles allowing quick computation of the force equilibrium. The CAS path (reference signal) is smoothed and realized using receding horizon c...

Multiagent systems arise in several domains of engineering. Examples include arrays of mobile sensor networks for aggregate imagery, autonomous highways, and formations of unmanned aerial vehicles. In these contexts, agents are governed by vehicle dynamics and often constraints, and the control objective is achieved by cooperation. Cooperation refers to the agreement of the agents to 1) have a ...