It is well known that exponentially unstable linear systems can not be globally stabilized in the presence of input constraints. In the case where the linear system is neutrally stable, one can achieve global asymptotic stability using a particular Control Lyapunov Function (CLF)based controller. Using this particular CLF as terminal cost in a receding horizon scheme, we obtain a receding horiz...

results that include the well-known matrix equality condition [1] as a special case, still allowing arbitrary state weighting matrices. Theorem 6 and Corollary 4 are also new results that weaken the condition on the state weighting matrix. It is known that the terminal weighting matrices presented in this paper can be represented as LMI forms and computed by using existing semi-definite program...

We consider the control of interacting subsystems whose dynamics and constraints are decoupled, but whose state vectors are coupled non-separably in a single cost function of a finite horizon optimal control problem. For a given cost structure, we generate distributed optimal control problems for each subsystem and establish that a distributed receding horizon control implementation is stabiliz...

The paper addresses the obstacle avoidance motion planning problem for ground vehicles operating in uncertain environments. By resorting to set-theoretic ideas, a receding horizon control algorithm is proposed for robots modelled by linear time-invariant (LTI) systems subject to input and state constraints and disturbance effects. Sequences of inner ellipsoidal approximations of the exact one-s...

This paper treats modeling and control for the burnthrough point in industrial sintering processes. First, a simple state-space model for event-time dynamics is derived for a complicated system by introducing events into a continuous variable system. For the control of the sintering process, a twostage control policy is used. First, optimal interevent time is obtained from an output-constrained...

We study the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and incomplete state information. Given a suitable choice of causal control policies, we first present a slight extension of the Kalman filter to estimate the state optimally in mean-square sense. We then show how to augment the underlying optimization problem with a negative drift-...

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...

We consider the control of interacting subsystems whose dynamics and constraints are decoupled, but whose state vectors are coupled non-separably in a single cost function of a finite horizon optimal control problem. For a given cost structure, we generate distributed optimal control problems for each subsystem and establish that a distributed receding horizon control implementation is stabiliz...