Novak Nedic

Robust identification of OE model with constrained output using optimal input design

Abstract This paper considers the robust algorithm for identification of OE (output error) model with constrained output in presence of non-Gaussian noises. In practical conditions, in measurements there are rare, inconsistent observations with the largest part of population of observations (outliers). The synthesis of robust algorithms is based on Huber׳s theory of robust statistics. Also, it is known fact that constraints play a very important role in many practical cases. If constraints are not taken into consideration, the control performance can corrupt and safety of a process may be at risk. The practical value of proposed robust algorithm for estimation of OE model parameters with constrained output variance is further increased by using an optimal input design. It is shown that the optimal input can be obtained by a minimum variance controller whose reference is a white noise sequence with known variance. A key problem is that the optimal input depends on system parameters to be identified. In order to be able to implement the proposed optimal input, the adaptive two-stage procedure for generating the input signal is proposed. Theoretical results are illustrated by simulations which show significant increasing of accuracy in parameter estimates of the OE model by using the robust identification procedure in relation to the linear identification algorithm for OE models. Also, it can be seen that the convergence rate of the robust algorithm is further increased by using the optimal input design, which increases the practical value of proposed robust procedure.

Simulation, animation and program support for a high performance pneumatic force actuator system

Program support, simulation and the animation of dual action pneumatic actuators controlled with proportional spool valves are developed. Various factors are involved, such as time delay in the pneumatic lines, leakage between chambers, air compressibility in cylinder chambers as well as non-linear flow through the valve. Taking into account the complexity of the model, and the fact that it is described by partial different equations, it is important to develop the program support based on numerical methods for solving this kind of problems. Simulation and program support in Maple and Matlab programming languages are conducted, and the efficiency of the results is shown from the engineering point of view.

A Nature Inspired Parameter Tuning Approach to Cascade Control for Hydraulically Driven Parallel Robot Platform

This paper presents the optimal tuning of cascade load force controllers for a parallel robot platform. A parameter search for the proposed cascade controller is difficult because there is no methodology to set the parameters and the search space is broad. The proposed parameter search scheme is based on a bat algorithm, which attracts a lot of attention in the evolutionary computation area due to the empirical evidence of its superiority in solving various nonconvex problems. The control design problem is formulated as an optimization problem under constraints. Typical constraints, such as mechanical limits on positions and maximal velocities of hydraulic actuators as well as on servo-valve positions, are included in the proposed algorithm. The simulation results indicate that the proposed optimal tuned cascade control is effective and efficient. These results clearly demonstrate that applied techniques exhibit a significant performance improvement over classical tuning methods.

A nature inspired optimal control of pneumatic-driven parallel robot platform

Woodworking industry is increasingly characterized by processing complex spatial forms with high accuracy and high speeds. The use of parallel robot platforms with six degrees of freedom gains more significance. Due to stricter requirements regarding energy consumption, easy maintenance and environmental safety, parallel platforms with pneumatic drives become more and more interesting. However, the high precision tracking control of such systems represents a serious challenge for designers. The reason is found in complex dynamics of the mechanical system and strong nonlinearity of the pneumatic system. This paper presents an optimal control design for a pneumatically driven parallel robot platform. The Proportional-Integral-Derivative (PID) algorithm with feedback linearization is used for control. The parameter search method is based on a firefly algorithm due to the empirical evidence of its superiority in solving various nonconvex problems. The simulation results show that the proposed optimal tuned cascade control is effective and efficient. These results clearly demonstrate that the proposed control techniques exhibit significant performance improvement over classical and widely used control techniques.

Design of PI Controllers for Hydraulic Control Systems

The paper proposes a procedure for design of PI controllers for hydraulic systems with long transmission lines which are described by models of high order. Design is based on the combination of the IE criterion and engineering specifications (settling time and relative stability) as well as on the application of D-decomposition. In comparison with some known results, the method is of graphical character, and it is very simple (solving nonlinear algebraic equations is eliminated). The paper presents the algorithm of software procedure for design of the controller. The method is compared with other methods at the level of simulation, and its superiority is shown. By applying the Nyquist criterion, it is shown that the method possesses robustness in relation to non modelled dynamics.

Simulation of hydraulic check valve for forestry equipment

Modelling and simulating complex systems, such as forestry equipment, are often the only way for their full analysis and design. This problem may lead to a stiff set of equations that are followed by numerical problems. In this paper two alternative approaches are investigated. The first one refers to the use of a variable step of integration by continuous models adjusted to the fastest processes. The second one refers to the approximation of fast transitions by ideal instantaneous mode-transitions and hybrid models. These two approaches are analysed in the framework of bond graph. The classical bond graph is adopted for description of the continuous models, and the switched bond graph is preferred for description of the hybrid models. The model of check valve is used as a working example for illustration of results. Matlab/Simulink tools are used for modelling and simulation.

Design of an H(lemniscate) PI controller with given relative stability and its application to the CSTR problem

H ¥ control theory has achieved a very high level, which is not followed by appropriate application in industry. Some reasons are: synthesis of H ¥ controllers is complex and based on the numerical Nevanlinna-Pick procedure, high order of controllers (higher than the order of the process) and sensitivity to deviation of controller coefficients (fragile controller). On the other hand, PI (PID) controllers are still dominant in industry, which places the problem of design of fixed structure controllers at the forefront. The mentioned problem is very difficult. This paper proposes a simple interactive procedure for design of H ¥ PI controllers with the presence of constraints (given relative stability) based on D-decomposition. The catalogue of responses to references, suppression of disturbances and minimum of H ¥ criteria of control is created. The selection of controllers, based on the catalogue, is left to the user. The application of H ¥ PI controllers to a CSTR (continuous stirred-tank reactor) is demonstrated.

Multilinear Model of Heat Exchanger with Hammerstein Structure

The multilinear model control design approach is based on the approximation of the nonlinear model of the system by a set of linear models. The paper presents the method of creation of a bank of linear models of the two-pass shell and tube heat exchanger. The nonlinear model is assumed to have a Hammerstein structure. The set of linear models is formed by decomposition of the nonlinear steady-state characteristic by using the modified Included Angle Dividing method. Two modifications of this method are proposed. The first one refers to the addition to the algorithm for decomposition, which reduces the number of linear segments. The second one refers to determination of the threshold value. The dependence between decomposition of the nonlinear characteristic and the linear dynamics of the closed-loop system is established. The decoupling process is more formal and it can be easily implemented by using software tools. Due to its simplicity, the method is particularly suitable in complex systems, such as heat exchanger networks.

Time Variable Speed Control of Pump Controlled Hydraulic Motor Using Natural Tracking Control

Abstract A pump controlled hydraulic motor meets problems with speed and accuracy. These problems become very significant with time varying motion. One way to overcome these problems is to develop some kind of control algorithm. Having in mind the task of these systems, a control algorithm based on the trackability concept seems logical. The special kind of control algorithm based on this concept has been investigated on time variable speed control of pump controlled hydraulic motor. Experimental and simulation results are shown.