Wheel slip control with torque blending using linear and nonlinear model predictive control

Model predictive control of nonlinear systems using piecewise linear models

We consider the problem of controlling nonlinear systems which are modeled as a set of piecewise linear (PL) or affine systems using model predictive control (MPC). The paper reviews recent results on the analysis and control of PL systems, which can model a wide range of practically relevant nonlinear systems. Using techniques from the theory of linear matrix inequalities (LMIs), we develop a ...

An optimal wheel-torque control on a compliant modular robot for wheel-slip minimization

This paper discusses the development of an optimal wheel torque controller for a compliant modular robot. The wheel actuators are the only actively controllable elements in this robot. For this type of robots, wheel-slip could offer a lot of hindrance while traversing on uneven terrains. Therefore, an effective wheel-torque controller is desired that will also improve the wheel-odometry and min...

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Nonlinear Model Predictive Control

Linear and Nonlinear Model Predictive Control of Quadruple Tank Process

In a multi input and output (MIMO) process mathematical modeling of the physical systems has gained importance due to the complexity of interactions within the system. All the parameters used in a model cannot be determined accurately. The major problem in a multivariable process is that loop interaction can arise and cause difficulty in feedback control design. This problem can be solved using...