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This paper describes the implementation of a model predictive controller novel in an underwater robot vehicle. This work also shows the development of an underwater vehicle model that accounts for physical, hydrodynamic and restorative effects, while the damping coefficients are neglected in the prediction of the vehicle position and orientation. The vehicle kinematic and dynamic models are linearized...
Model predictive control (MPC) applications habitually focus on large systems with slow dynamics. In addition, traditional constrained optimization techniques make use of algorithms not suited for fast MPC execution. This work suggests the use of conditional penalties in the optimization cost function to account for constraints. Such penalty functions resemble the barrier functions, where the penalty...
This paper presents the programming features that are desirable in Process Simulation and Control Education Software. These programming features facilitate the understanding of the control subject by showing the effect of physical parameters in dynamic systems. These software features also deal with data acquisition through different hardware systems in an effective and simple way. Data acquisition...
Input and output time delays in continuous-time state-space systems are treated separately as their effects are encountered before and after the state dynamics. Existing discretization techniques for such systems usually consider the delays to be integer multiples of the sampling time. This work develops a discretization procedure for multi-variable state-space systems with nonuniform input and/or...
The design of nonlinear predictive controllers based on linear time-varying prediction models is discussed. The linear time-varying models can be obtained by applying a local linearization along the nominal input and state trajectory or by describing the nonlinear state equations by state dependent state space equations. A graphical predictive control framework that provides practical methods for...
The design of nonlinear predictive controllers based on linear time-varying prediction models is discussed. The linear time-varying models can be obtained by applying a local linearization along the nominal input and state trajectory or by describing the nonlinear state equations by state dependent state space equations. A graphical predictive control framework that provides practical methods for...
Graphical programming provides a suitable way to design and configure advanced control applications. This paper illustrates the configuration of graphical model predictive control applications. The system in study is controlled with linear as well as nonlinear predictive control methods, and it demonstrates the convenience of a graphical interface for the development of these popular control design...
A large number of applications of generic model control (GMC) have been published in the literature. However, an overview of the potential difficulties in implementation has not been provided. This paper evaluates the basic GMC algorithm when applied to single input single output linear processes and provides insight regarding its limitation to ensure robust stability. The effect of sampling time...
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