Predictive Controller Design to Control Angle and Position of DIPOAC

2018 ◽  
pp. 453-460 ◽  
Author(s):  
Abhaya Pal Singh ◽  
Siddharth Joshi ◽  
Pallavi Srivastava
Keyword(s):  
Controller Design ◽  
Predictive Controller

Multi-objective adaptive cruise controller design using nonlinear predictive controller with the objective function with variable weights determined by fuzzy logic controller

2021 ◽  
pp. 095440702110147
Author(s):  
Behzad Samani ◽  
Amir H. Shamekhi
Keyword(s):  
Objective Function ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Hierarchical Control ◽  
Control Input ◽  
Cruise Control ◽  
Model Predictive Controller ◽  
Control Step ◽  
Predictive Controller

In this paper, an adaptive cruise control system with a hierarchical control structure is designed. The upper-level controller is a model predictive controller (MPC) that by minimizing an objective function in the presence of the constraints, calculates the desired acceleration as control input and sends it to the lower-level controller. So the lower-level controller, which is a fuzzy controller, determines the amount of throttle valve opening or brake pressure to get the car to this desired acceleration. The model predictive controller performs optimization at each control step to minimize the objective function and achieve the reference values. Usually, the objective function has predetermined and constant weights to meet objectives such as maintain the driver’s desired speed and increase safety and in some cases increase comfort and reduce fuel consumption. In this paper, it is suggested that instead of using constant weights in the objective function, these weights should be determined by a fuzzy controller, depending on the different conditions in which the car is placed. The simulation results show that the variability of the weights of the objective function achieves control objectives much better than the optimization of the objective function with constant weights.

FEEDBACK PREDICTIVE CONTROL OF NONHOMOGENEOUS MARKOV JUMP SYSTEMS WITH NONSYMMETRIC CONSTRAINTS

2014 ◽  
Vol 56 (2) ◽  
pp. 138-149
Author(s):  
YANQING LIU ◽  
FEI LIU
Keyword(s):  
Predictive Control ◽  
Controller Design ◽  
Invariant Set ◽  
Markov Jump ◽  
Markov Jump Systems ◽  
Markov Jump System ◽  
Predictive Controller ◽  
Feasibility Region ◽  
Nonhomogeneous Markov Jump System ◽  
Jump Systems

AbstractWe consider feedback predictive control of a discrete nonhomogeneous Markov jump system with nonsymmetric constraints. The probability transition of the Markov chain is modelled as a time-varying polytope. An ellipsoid set is utilized to construct an invariant set in the predictive controller design. However, when the constraints are nonsymmetric, this method leads to results which are over conserved due to the geometric characteristics of the ellipsoid set. Thus, a polyhedral invariant set is applied to enlarge the initial feasible area. The results obtained are for a more general class of dynamical systems, and the feasibility region is significantly enlarged. A numerical example is presented to illustrate the advantage of the proposed method.

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