Two-degree-of-freedom multi-input multi-output proportional–integral–derivative control design: Application to quadruple-tank system

Author(s):  
Jatin Kumar Pradhan ◽  
Arun Ghosh ◽  
Chandrashekhar Narayan Bhende

This article is concerned with designing a 2-degree-of-freedom multi-input multi-output proportional–integral–derivative controller to ensure linear quadratic regulator performance and H∞ performance using a non-iterative linear matrix inequality–based method. To design the controller, first, a relation between the state feedback gain and proportional–integral–derivative gain is obtained. As the gains of proportional–integral–derivative controller cannot, in general, be found out from this relation for arbitrary stabilizing state feedback gain, a suitable form of the matrices involved in linear matrix inequality–based state feedback design is then chosen to obtain the proportional–integral–derivative gains directly. The special structure of the above matrices allows one to design proportional–integral–derivative controller in non-iterative manner. As a result, multi-objective performances, such as linear quadratic regulator and H∞, can be achieved simultaneously without increasing the computational burden much. To enhance the reference-input-to-output characteristics, a feedforward gain is also introduced and designed to minimize certain closed-loop H∞ performance. The proposed control design method is applied for multi-input multi-output proportional–integral compensation of a laboratory-based quadruple-tank process. The performance of the compensation is studied through extensive simulations and experiments.

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xuejuan Shao ◽  
Jinggang Zhang ◽  
Xueliang Zhang

The dynamic model of overhead crane is highly nonlinear and uncertain. In this paper, Takagi-Sugeno (T-S) fuzzy modeling and PSO-based robust linear quadratic regulator (LQR) are proposed for anti-swing and positioning control of the system. First, on the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method. Then, considering the uncertainty of the model, robust LQR controllers with parallel distributed compensation (PDC) structure are designed. The feedback gain matrices are obtained by transforming the stability and robustness of the system into linear matrix inequalities (LMIs) problem. In addition, particle swarm optimization (PSO) algorithm is used to overcome the blindness of LQR weight matrix selection in the design process. The proposed control methods are simple, feasible, and robust. Finally, the numeral simulations are carried out to prove the effectiveness of the methods.


Author(s):  
Vladimir Milic ◽  
Srecko Arandia-Kresic ◽  
Mihael Lobrovic

This paper is concerned with the synthesis of proportional–integral–derivative (PID) controller according to the [Formula: see text] optimality criterion for seesaw-cart system. The equations of dynamics are obtained through modelling a seesaw-cart system actuated by direct-current motor via rack and pinion mechanism using the Euler–Lagrange approach. The obtained model is linearised and synthesis of the PID controller for linear model is performed. An algorithm based on the sub-gradient method, the Newton method, the self-adapting backpropagation algorithm and the Adams method is proposed to calculate the PID controller gains. The proposed control strategy is tested and compared with standard linear matrix inequality (LMI)-based method on computer simulations and experimentally on a laboratory model.


Author(s):  
T Yamamoto ◽  
Y Ohnishi ◽  
S L Shah

In order to manufacture high-quality products it is necessary to regularly monitor the performance of the control loops that regulate the quality variables of interest. This paper describes a design scheme of performance-adaptive controllers which are based on the above control strategy. According to the proposed control scheme, the output prediction error is monitored regularly and system identification is initiated if this error exceeds a user-defined threshold. Subsequently proportional—integral—derivative (PID) parameters are updated for the new model. Optimal PID parameters are calculated based on the linear quadratic Gaussian (LQG) trade-off curve obtained for the reidentified process model. The behaviour of the proposed control scheme is numerically evaluated by some simulation examples.


Author(s):  
Maria Cecilia Zanardi ◽  
Paola da Rosa Prado ◽  
Leandro Baroni

This paper proposed a study of a spatial tether system (STS), composed by two satellite (a main satellite and a subsatellite), with the objective of developing a control system in which the motion of the subsatellite is limited in the orbital plane of the main satellite. The linear quadratic regulator (LQR) method is used to implement this control, which is an optimal control with state feedback to predict the linearization of the equations of motion to calculate the feedback gain, using the resolution of Riccati equation. The results show an effective control, with the motion of the subsatellite limited only to the stretch of the cable that links both satellites. However, it is necessary to introduce an auxiliary torque, since the linearized equation associated with the second variation of the angle out of the plan does not have a term independent of the state vector.


2021 ◽  
pp. 107754632110055
Author(s):  
Abolfazl Simorgh ◽  
Abolhassan Razminia ◽  
Vladimir I Shiryaev

The second-order systems can capture the dynamics of a vast majority of industrial processes. However, the existence of uncertainty in second-order approximation of such processes is inevitable because the approximation may not be accurate or the operating condition changes, resulting in performance degradation or even instability. This article aims at designing a novel robust proportional–integral–derivative controller for the uncertain second-order delay-free and time-delay systems in an optimal manner. The method is simple, effective, and can efficiently improve the performance of the uncertain systems. The approach is based on the linear quadratic theory, in which by adding a new matrix in the quadratic cost function regarding the uncertainties, the stability of the perturbed system is guaranteed and proven for both time-delay and delay-free second-order cases. The comparison with the recent works in the literature supports the effectiveness of the proposed methodology.


Sign in / Sign up

Export Citation Format

Share Document