In this paper, robust RHC (Receding Horizon Control) method with adaptive DA converter for robotic wheelchair using EEG (Electroencephalogram) based BMI (Brain Machine Interface) is discussed. The method is developed to apply to the obstacle avoidance system of the robotic wheelchair. Some numerical examples are also included to demonstrate the effectiveness of the proposed method. Key–Words: R...

This paper presents a receding horizon planning algorithm for vision-based navigation using bearings-only SLAM that adapts the planning horizon to the velocity of the information gained about the environment. Bearings-only SLAM has an inherent dynamic observability property such that specific motion is needed in order to determine the relative positions between the camera and obstacles. Thus, t...

We consider a finite-horizon linear-quadratic optimal control problem where only a limited number of control messages are allowed for sending from the controller to the actuator. To restrict the number of control actions computed and transmitted by the controller, we employ a threshold-based event-triggering mechanism that decides whether or not a control message needs to be calculated and deli...

This paper proposes the optimal feedback control method using magnetic force for crystal growth dynamics of semiconductor materials. The system model considered here is described by the continuity, momentum, energy, mass transport, and magnetic induction equations. Receding horizon control is a kind of optimal feedback control in which the control performance over a finite future is optimized w...

We consider an approximation scheme for solving Markov Decision Processes (MDPs) with countable state space, finite action space, and bounded rewards that uses an approximate solution of a fixed finite-horizon sub-MDP of a given infinite-horizon MDP to create a stationary policy, which we call “approximate receding horizon control”. We first analyze the performance of the approximate receding h...

A framework for robustness analysis of input constrained nite receding horizon control is presented. Under the assumption of quadratic upper bounds on the nite horizon costs, we derive suucient conditions for robust stability of the standard discrete-time linear-quadratic receding horizon control formulation. This is achieved by recasting conditions for nominal and robust stability as an implic...

A hierarchical control architecture for the integration of scheduling decisions, dynamic real-time optimization and tracking control is proposed. It is shown how the discretecontinuous problem of simultaneous scheduling and trajectory optimization on a receding horizon can be integrated within the upper control layer of a two-layer architecture. On the upper layer, the optimal plant strategy de...

Model Predictive Control is analyzed as a strategy for coping with the unknown, variable and non-deterministic action and measurement delays which can occur in congestion control of available-bit-rate teletraffic control for highspeed data networks. It is shown that the state-feedbackplus-estimator certainty equivalence nature of this control law is particularly amenable to coping with these de...

In this paper, a new distributed receding horizon formation control scheme is introduced using relative dynamical model instead of absolute dynamical model of each member robot in most existing formation control algorithms. Convergence of the proposed distributed receding horizon formation control (DRHFC) is implemented using some additional control input constraints, and the relative dynamical...

In this survey, receding horizon control is presented as a method for obtaining approximately optimal solutions to infinite horizon optimal control problems by iteratively solving a sequence of finite horizon optimal control problems. We investigate conditions under which we can obtain mathematically rigorous approximation results for this approach. A key ingredient of our analysis is the so-ca...