Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics
Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847
Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce
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Článekpeer-reviewedpostprint Otevřený přístup Desired Terminal State Concept in Model Predictive Control: A Case Study(Hindawi limited, 2019) Dušek, František; Honc, DanielThe paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for the case of short horizons and large control error penalization. Terminal state is one way to ensure stability or at least increase the controller robustness. In the paper, deviation of the predicted terminal state from the desired terminal state is considered as one term of the cost function. Effect of the stability and control quality is demonstrated in the simulated experiments. The application area for online optimization methods is very broad including various logistics and transport problems. If the dynamics of the controlled processes cannot be neglected, the optimization problem must be solved not only for steady state but also for transient behaviour, e.g., by MPC.Konferenční objektpeer-reviewedpostprint Otevřený přístup Comparitive study of predictive controllers for trajectory tracking of non-holonomic mobile robot(IEEE (Institute of Electrical and Electronics Engineers), 2017) Kizhakke Illom, Rahul Sharma; Dušek, František; Honc, DanielThe paper deals with predictive control of non-holonomic mobile robot. The basic nonlinear kinematic equation is linearized into two different linear time varying models based on frame of reference-world coordinates and local coordinate of mobile robot. The non-linear model predictive control is applied to the trajectory tracking problem of a non-holonomic mobile robot with these models. The control law is derived from a cost function which penalizes the state tracking error, control effort and terminal state deviation error. Various simulation experiments are conducted and a comparative analysis has been made with respect to state-of-the-art approaches.Konferenční objektpeer-reviewedpostprint Otevřený přístup Optimal control with disturbance estimation(Nottingham Trent University, 2017) Dušek, František; Honc, Daniel; Kizhakke Illom, Rahul SharmaThe paper deals with a very common situation in many control systems and this is the fact that, for zero control action, the controlled variable is nonzero. This is often caused by the existence of another process input which is uncontrolled. Classic controllers do not take into account the second input, so deviation variables are considered or some feedforward controller is used to compensate the variable. The authors propose a solution, that the process is considered as a system with two inputs and single output (TISO). Here, the uncontrolled input is estimated with the state observer and the controller is designed as the multivariable controller. A Linear-quadratic (LQ) state-feedback control and model predictive control (MPC) of simple thermal process simulations are provided to demonstrate the proposed control strategy.Konferenční objektpeer-reviewedpostprint Omezený přístup PREDICTIVE CONTROL OF DIFFERENTIAL DRIVE MOBILE ROBOT CONSIDERING DYNAMICS AND KINEMATICS(EUROPEAN COUNCIL MODELLING & SIMULATION, 2016) Sharma K., Rahul; Honc, Daniel; Dušek, FrantišekThe paper deals with trajectory tracking of the differential drive robot with a mathematical model governing dynamics and kinematics. Motor dynamics and chassis dynamics are considered for deriving a linear state-space dynamic model. Basic nonlinear kinematic equations are linearized into a successively linearized state-space model. The dynamic and kinematic models are augmented to derive a single state-space linear model. The deviation variables are reference variables which are variables of an ideal robot following a reference trajectory which can be pre-calculated. Reference tracking is achieved by model predictive control of supply voltage of both the drive motors by considering constraints on controlled variables and manipulated variables. Simulation results are provided to demonstrate the performance of proposed control strategy in the MATLAB simulation environment.