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Multiple Model Approaches to Modelling and Control
1. Basic Principles: The Operating Regime Approach 2. Modelling: Fuzzy Set Methods for Local Modelling Identification 3. Modelling of Electrically Stimulated Muscle 4. Process Modelling Using a
An algorithm for multi-parametric quadratic programming and explicit MPC solutions
TLDR
The properties of the polyhedral partition of the state space induced by the multi-parametric piecewise affine solution are studied, and a new mp-QP solver is proposed that adopts a different exploration strategy for subdividing the parameter space, avoiding unnecessary partitioning and QP problem solving.
Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment
TLDR
Simulations show that the model predictive control method for a collision avoidance system for ships is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.
On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models
TLDR
There exists a close relationship between dynamic Takagi-Sugeno fuzzy models and dynamic linearization when using affine local model structures, which suggests that a solution to the multiobjective identification problem exists, but it is also shown that the affineLocal model structure is a highly sensitive parametrization when applied in transient operating regimes.
Constructing NARMAX models using ARMAX models
TLDR
It is shown that a large class of non-linear systems can be modelled in this way, and indicated how to decompose the systems range of operation into operating regimes.
A Survey of Control Allocation Methods for Ships and Underwater Vehicles
Control allocation problems for marine vessels can be formulated as optimization problems, where the objective typically is to minimize the use of control effort (or power) subject to actuator rate
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