Juraj Oravec

Robust model predictive control of a laboratory two-tank system

Robust model predictive control was applied for the laboratory two-tank system. The controlled process is modeled as the uncertain polytopic system for the controller design. Two robust model predictive control design strategies were used. The first strategy uses the single Lyapunov function and the second one assumes the parameter-dependent Lyapunov functions. The design problem is converted to the solution of the system of linear matrix inequalities and a simple algorithm is also presented. The controllers designed using both strategies were tested on the laboratory process. The results confirmed that using the parameter-dependent Lyapunov function in the robust model predictive controller design improved the control performance in comparison with the single Lyapunov function based strategy.

Robust and optimal control approach for exothermic reactor stabilization

In this paper, the possibility to stabilise open-loop unstable exothermic reactors with temperature measurements is studied. Moreover, the reactors are considered to be multi-input multi-output systems with parametric uncertainties. Robust static output feedback and optimal controllers are designed for stabilization of the exothermic reactors into their open-loop unstable steady states. Stabilization of reactors is simulated using designed controllers. The possibility of using both types of controllers for energy savings is studied and measured by coolant consumption. The approach is tested with a representative example. Obtained simulations results confirm that the robust static output feedback controllers outperform optimal controllers when systems with parametric uncertainties are controlled.

Model predictive control-based robust stabilization of a chemical reactor

The paper addresses an approach to robust stabilization of chemical continuous stirred tank reactors. State feedback was used for the stabilization and the feedback controller was designed using the robust model-based predictive control algorithm in which the symmetric constraints on input and output variables are taken into account. The known strategy was modified by adding integral action to the controller. Parameters of robust feedback controllers with and without integral action were found as solutions of a constrained optimization problem solved on the infinite prediction horizon. The possibility to stabilize chemical reactors with uncertainty using the robust model-based predictive control has been verified by simulations and compared with the optimal linear quadratic control and the model-based predictive control. The obtained results confirm that the robust model-based predictive control provides better results than other approaches.

Software for efficient LMI-based robust MPC design

Robust MPC is an advanced control strategy to optimize control performance subject to the constraints of the system inputs/outputs and in the presence of bounded disturbance. The paper presents novel MATLAB/Simulink MUP toolbox for on-line robust MPC design using LMIs. Software MUP represents an efficient and user-friendly tool. Therefore it is recommended to use this toolbox especially for educational purposes oriented on advanced process control. An illustrative case study of robust MPC design of the open-loop unstable system was investigated to demonstrate the basic features of the presented software.

Robust constrained MPC stabilization of a CSTR

Abstract The paper addresses a case study of robust stabilization of a continuous stirred tank reactor using robust model-based predictive control with constrained input variables. One exothermic reaction runs in the reaction mixture and the reactor is modelled in the form of an uncertain polytopic system. The control approach is based on solution of a set of linear matrix inequalities. This formulation enables to use convex optimization methods to design a gain matrix of a state feedback controller in each control step. The task of stabilization is solved in assumed control conditions with respect to symmetric constraints on control inputs. The control performance achieved by robust constrained model-based predictive control is studied via simulations. Obtained results confirm that the robust constrained model-based predictive control ensures the stability demands and the quality requirements represented by chosen quadratic cost function.

MPC-based reference governor control of a continuous stirred-tank reactor

Abstract Optimal control of a CSTR represents a challenging task. The proposed paper discusses two issues. The first one addresses control of pH in a chemical vessel, where the reaction between sodium hydroxide and acetic acid occurs. The objective here is to improve control performance of a well tuned PI controller. It will be shown that this can be achieved by introducing a reference governor scheme. The second problem, elaborated in this paper, is the implementation of the reference governor paradigm. Concretely, we aim to design a fast and cheap MPC-based feedback controller. To achieve these goals, we exploit the region-less explicit technique, which efficiently reduces memory footprint issues of standard explicit MPC schemes. Such MPC-based reference governor was employed to control pH in the chemical vessel. Its control performance is compared with conventional PI controller. Finally, comparison of implementation requirements of region-less and region-based explicit techniques is investigated.

Computationally Tractable Formulations for Optimal Path Planning with Interception of Targets’ Neighborhoods

Devising the planar routes of minimal length that are required to pass through predefined neighborhoods of target points plays an important role in reducing the mission’s operating cost. Two versions of the problem are considered. The first one assumes that the ordering of the targets is fixed a priori. In such a case, the optimal route is devised by solving a convex optimization problem formulated either as a second-order cone program or as a sum-of-squares optimization problem. Additional route properties, such as continuity and minimal curvature, are considered as well. The second version allows the ordering of the targets to be optimized to further reduce the route length. We show that such a problem can be solved by introducing additional binary variables, which allows the route to be designed using off-the-shelf mixed-integer solvers. A case study that shows that the proposed strategy is computationally tractable is presented.

WebPIDDESIGN for robust PID controller design

The paper presents the novel online tool for robust PID controller design RobCont that enables to design robust PID controllers and to analyze the stability of the closed-loop control performance in an advanced way. This tool is an extension of modular system WebPIDDESIGN, a complex framework that provides features of system identification, PID controller design, and evaluation of control quality. RobCont extends the possibilities of framework by control design tasks focused on systems with interval uncertainties. The tool allows user to perform the step-by-step procedure from system definition, through open loop analysis, to selection of robust controller, closed loop simulation, and evaluation of control quality. The controller selection is based on Neimarks D-partition method and Kharitonovs 16 plant theorem. The RobCont extends also other features of the WebPIDDESIGN, i.e. enables to perform the polynomial approximation of the time-delay systems. The paper also contains a case study on a real laboratory process, where common RobCont usage procedure is illustrated. The presented tool is mainly intended for the education purposes in the field of automatic control.

Fuzzy controller design for a heat exchanger

The paper presents an advanced control strategy that uses fuzzy controllers in the complex control structure with an auxiliary control input. The controlled tubular counter-current heat exchanger is used for pre-heating petroleum by hot water. The heat exchanger is modelled as a nonlinear system with the interval parametric uncertainty. The set-point tracking and the disturbance rejection using intelligent control strategies are investigated. The control objective is to keep the outlet temperature of the pre-heated petroleum at a reference value. Simulations of control of the tubular heat exchanger are done in the Matlab/Simulink environment. The complex control structure with fuzzy controllers is compared with conventional PID control, fuzzy control and complex control structure with conventional controllers. Simulation results confirm the effectiveness and superiority of the advanced control approach combining two fuzzy controllers.

WebPIDDESIGN - software for PID controller design management

The goal of this paper is to present the software tool WebPIDDESIGN for complex management of PID controller design. This tool is suitable for those who need to design the PID controller for the simple closed-loop feedback in an effective and user-friendly way. As the WebPIDDESIGN interface has been currently placed on the Internet, the users may benefit from the simple utilization without the need of complex software and hardware requirements. The features of this tool determine its usability especially for educational purpose. Users of WebPIDDESIGN can reap the benefits of its online form, especially interactivity, information value, ease of use, and accessibility 24/7. This software includes system analysis and identification features, various PID controller design methods, closed loop simulations and evaluation of control quality. As a tool for education, it also provides appropriate theoretical background to specific control design and identification tasks, in such an extent that user is able to understand all performed tasks without an exhaustive effort.