Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...

A new formulation of a trajectory tracking controller for flexible joint robotic manipulator is proposed. The controller is based on the continuous time nonlinear predictive control approach wherein predicted errors in the actual response and the desired response and current control expenditure is minimized point-wise to obtain an optimal, nonlinear feedback control law. It is shown that the we...

the control of car following is essential due to its safety and its operational efficiency. for this purpose, this paper builds a model of car following behavior based on armax structure from a real traffic dataset and design a model predictive control (mpc) system. based on the relative distance and relative acceleration of each instant, the mpc predicts the future behavior of the leader vehic...

This thesis addresses two neural network based control systems. The first is a neural network based predictive controller. System identification and controller design are discussed. The second is a direct neural network controller. Parameter choice and training methods are discussed. Both controllers are tested on two different plants. Problems regarding implementations are discussed. First the...

Control engineers have been aware of non-minimum phase systems showing either undershoot or time-delay characteristics for some considerable time (Linoya & Altpeter, 1962; Mita & Yoshida, 1981; Vidyasagar, 1986; Waller & Nygardas, 1975). A number of researchers that addressed this problem from a predictive control point of view mainly followed one of two approaches: a classical (non-optimal) pr...

A new nonlinear predictive control law for a class of multivariable nonlinear systems is presented in this paper. It is shown that the closed-loop dynamics under this nonlinear predictive controller explicitly depend on design parameters (prediction time and control order). The main features of this result are that an explicitly analytical form of the optimal predictive controller is given, on-...

In this paper an algorithm of PID controller based on model predictive control is designed for a shell and tube heat exchanger. PID controllers and model predictive controls are two control algorithm mostly used these types of process applications. The three parameters of PID controller must be tuned to the process to obtain a satisfactory closed loop process performance. The model of the heat ...

igestion is a hot topic in pulp production at Skeena Cellulose in Prince Rupert, British Columbia, Canada. A new continuous digester control system uses a new predictive adaptive process controller to provide closed-loop control of Effective Alkali and reduced Kappa Number variability. The installation of this controller has resulted in production cost savings of $0.60 per ton of pulp and proje...

In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear model bank) and the parameters are identified for an experimental polymerization reactor. Then, a multiple model adaptive predictive controller ...