Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time-delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non-linear p...

When faced with making a decision, it is only natural that one would aim to select the course of action which results in the “best" possible outcome. However, the ability to arrive at a decision necessarily depends upon two things: a well-defined notion of what qualities make an outcome desirable, and a previous decision1 defining to what extent it is necessary to characterize the quality of in...

In this paper we present a framework for realtime, full state feedback, nonlinear model predictive motion control of autonomous robots. The proposed approach uses an iterative optimization algorithm, namely iterative Linear Quadratic Gaussian (iLQG) to solve the underlying nonlinear optimal control problem, simultaneously deriving feedforward and feedback terms. The resulting motion controller ...

A true adaptive nonlinear model predictive control (MPC) algorithm must address the issue of robustness to model uncertainty while the estimator is evolving. Unfortunately, this may not be achieved without introducing extra degree of conservativeness and/or computational complexity in the controller calculations. To attenuate this problem, we employ a finite time identifier and propose an adapt...

An adaptive radial basis function (RBF) neural network model is developed in this paper for nonlinear systems using the recursive orthogonal least squares (ROLS) algorithm. The model is used in a nonlinear model predictive control (NMPC). The developed adaptive NMPC is applied to a chemical reactor rig. On-line control performance is presented and it demonstrates superiority over the fixed para...

Firstly, a method is introduced which uses Volterra series deploying technique to construct a nonlinear model based on OFS model. Then an improved novel incremental mode multiple steps adaptive predictive control strategy is brought forward, which can import more information about the system’s dynamical characteristics. Experiments of constant water pressure equipment’s control prove that this ...

Adaptive Model Predictive Transmission Control Protocol (AMP-TCP) as a new TCP delay-based congestion control algorithm is introduced. Both aspects of design and implementation of the algorithm are described using simulations on the ns-2 network simulator. The design stage is composed of two steps. First, a recursive system identification approach is proposed to capture the network delay dynami...

Recently, suboptimality estimates for model predictive controllers (MPC) have been derived for the case without additional stabilizing endpoint constraints or a Lyapunov function type endpoint weight. The proposed methods yield a posteriori and a priori estimates of the degree of suboptimality with respect to the infinite horizon optimal control and can be evaluated at runtime of the MPC algori...