Radu-Emil Precup
Edith Cowan University
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Radu-Emil Precup.
Computers in Industry | 2011
Radu-Emil Precup; Hans Hellendoorn
Fuzzy control has long been applied to industry with several important theoretical results and successful results. Originally introduced as model-free control design approach, model-based fuzzy control has gained widespread significance in the past decade. This paper presents a survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000.
Information Sciences | 2013
Radu-Codru David; Radu-Emil Precup; Emil M. Petriu; Mircea-Bogdan Rdac; Stefan Preitl
This paper proposes the design of fuzzy control systems with a reduced parametric sensitivity making use of Gravitational Search Algorithms (GSAs). The parametric variations of the processes lead to sensitivity models. Objective functions expressed as integral quadratic performance indices, which depend on the control error and squared output sensitivity functions are suggested. GSAs are employed to minimize the objective functions in the appropriately defined optimization problems. This paper also suggests a GSA with improved search accuracy. The new GSA is characterized by the modification of the denominator in the expression of the force acting on an agent from the other agent; the denominator depends not only on the Euclidian distance between the two agents but also on the position of the latter: A design method for Takagi-Sugeno proportional-integral fuzzy controllers (PI-FCs) is proposed. The PI-FCs are dedicated to a class of processes characterized by second-order linear or linearized models with an integral component. Two discrete-time sensitivity models of the fuzzy control systems are derived. An example dealing with the angular position control of direct current (DC) servo system laboratory equipment validates the new controller design. A set of real-time experimental results illustrates the fuzzy control system performance.
international conference on advanced intelligent mechatronics | 2010
Radu-Emil Precup; Sergiu Spataru; Emil M. Petriu; Stefan Preitl; Mircea-Bogdan Radac; Claudia-Adina Dragos
This paper discusse four new Takagi-Sugeno fuzzy controllers (T-S FCs) for the longitudinal slip control of an Antilock Braking System laboratory equipment. Two discrete-time dynamic Takagi-Sugeno fuzzy models of the controlled plant are derived based on the parameters in the consequents of the rules using the domains of the input variables, and doing the local linearization of the plant model. The original T-S FCs are designed by parallel distributed compensation to obtain the state feedback gain matrices in the consequents of the rules. Two T-S FCs are tuned by imposing relaxed stability conditions to the fuzzy control systems (FCSs) and the other two T-S FCs are tuned by the linear-quadratic regulator approach applied to each rule. Linear matrix inequalities are solved to guarantee the global stability of the FCSs. Real-time experimental results validate the original T-S FCs and design approaches.
IEEE-ASME Transactions on Mechatronics | 2008
Radu-Emil Precup; Stefan Preitl; Imre J. Rudas; Marious L. Tomescu; Jósef K. Tar
This paper proposes a new fuzzy control solution employing 2-DOF proportional-integral-fuzzy controllers dedicated to a class of servo systems. The controlled plants in these systems, widely used in mechatronics applications, can be characterized by second-order dynamics with integral type. The original design method suggested here starts with linear design results in terms of the extended symmetrical optimum method accompanied by an iterative feedback tuning (IFT) algorithm. Next, these results are transferred to the fuzzy case by the modal equivalence principle. The convergence of the IFT algorithm is guaranteed by the derivation of sufficient global asymptotic stability conditions based on Krasovskii-LaSalles invariant set theorem with quadratic Lyapunov function candidate. Real-time experimental results corresponding to a low-cost fuzzy controlled servo system validate the theoretical approaches.
IEEE Transactions on Industrial Informatics | 2012
Radu-Emil Precup; Radu-Codrut David; Emil M. Petriu; Stefan Preitl; Mircea-Bogdan Radac
This paper presents a novel adaptive Gravitational Search Algorithm (GSA) for the optimal tuning of fuzzy controlled servo systems characterized by second-order models with an integral component and variable parameters. The objective functions consist of the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The proposed adaptive GSA solves the optimization problems resulting in a new generation of Takagi-Sugeno proportional-integral fuzzy controllers (T-S PI-FCs) with a reduced time constant sensitivity. A design method for T-S PI-FCs is then proposed and experimentally validated in the representative case study of the optimal tuning of T-S PI-FCs for the position control system of a servo system.
Knowledge Based Systems | 2013
Radu-Emil Precup; Radu-Codru David; Emil M. Petriu; Mircea-Bogdan Rdac; Stefan Preitl; János C. Fodor
This paper suggests the optimal tuning of low-cost fuzzy controllers dedicated to a class of servo systems by means of three new evolutionary optimization algorithms: Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO) algorithm and Simulated Annealing (SA) algorithm. The processes in these servo systems are characterized by second-order models with an integral component and variable parameters; therefore the objective functions in the optimization problems include the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The servo systems are controlled by Takagi-Sugeno proportional-integral-fuzzy controllers (T-S PI-FCs) that consist of two inputs, triangular input membership functions, nine rules in the rule base, the SUM and PROD operators in the inference engine, and the weighted average method in the defuzzification module. The T-S PI-FCs are implemented as low-cost fuzzy controllers because of their simple structure and of the only three tuning parameters because of mapping the parameters of the linear proportional-integral (PI) controllers onto the parameters of the fuzzy ones in terms of the modal equivalence principle and of the Extended Symmetrical Optimum method. The optimization problems are solved by GSA, PSO and SA resulting in fuzzy controllers with a reduced parametric sensitivity. The comparison of the three evolutionary algorithms is carried out in the framework of a case study focused on the optimal tuning of T-S PI-FCs meant for the position control system of a servo system laboratory equipment. Reduced process gain sensitivity is ensured.
IEEE Transactions on Industrial Electronics | 2008
Radu-Emil Precup; Stefan Preitl; József K. Tar; Marius-Lucian Tomescu; Márta Takács; Péter Korondi; Péter Baranyi
This paper suggests low-cost fuzzy control solutions that ensure the improvement of control system (CS) performance indices by merging the benefits of fuzzy control and iterative learning control (ILC). The solutions are expressed in terms of three fuzzy CS (FCS) structures that employ ILC algorithms and a unified design method focused on Takagi-Sugeno proportional-integral fuzzy controllers (PI-FCs). The PI-FCs are dedicated to a class of servo systems with linear/linearized controlled plants characterized by second-order dynamics and integral type. The invariant set theorem by Krasovskii and LaSalle with quadratic Lyapunov function candidates is applied to guarantee the convergence of the ILC algorithms and enable proper setting of the PI-FC parameters. The linear PI controller parameters tuned by the extended symmetrical optimum method are mapped onto the PI-FC ones by the modal equivalence principle. Real-time experimental results for a dc-based servo speed CS are included.
Engineering Applications of Artificial Intelligence | 2004
Radu-Emil Precup; Stefan Preitl
The paper proposes new optimisation criteria as extended quadratic performance indices (QPIs) that can be used in the development of fuzzy controllers (FC) with dynamics based on an attractive development method for a Takagi-Sugeno PI-fuzzy controller meant for controlling a class of plants with variable parameters applicable to servo systems. In the first phase, there are derived sensitivity models with respect to the parametric variations of the controlled plant used in decision making concerning the operating mode of the FC. The developed fuzzy control systems can be considered suboptimal in terms of the optimisation criteria defined in dynamic regimes with respect to modifications (particularly of step type) of the reference input and of four disturbance input scenarios, and quasi-insensitive with respect to the parametric variations of the controlled plant.
IEEE Transactions on Industrial Electronics | 2012
Radu-Emil Precup; Emil M. Petriu; Stefan Preitl; Mircea-Bogdan Radac
This paper discusses the design of fuzzy control systems (FCSs) with a reduced parametric sensitivity using simulated-annealing (SA) algorithms. Four generic families of objective functions expressed as integral quadratic performance indexes, which depend on the control error and squared output sensitivity functions, are suggested. SA algorithms are employed to minimize the objective functions in the appropriately defined optimization problems. A design method for Takagi-Sugeno proportional-integral fuzzy controllers (PI-FCs) is proposed. The resulting PI-FCs are intended for a class of plants characterized by second-order linearized models with integral component. A case study dealing with the angular position control of a dc servo system is used as test bed to validate the proposed new controller design. Experimental results illustrate the FCS performance.
Journal of The Franklin Institute-engineering and Applied Mathematics | 2009
Radu-Emil Precup; Stefan Preitl; Emil M. Petriu; József K. Tar; Marius-Lucian Tomescu; Claudiu Pozna
Abstract This paper presents a new framework for the design of generic two-degree-of-freedom (2-DOF), linear and fuzzy, controllers dedicated to a class of integral processes specific to servo systems. The first part of the paper presents four 2-DOF linear PI controller structures that are designed using the Extended Symmetrical Optimum method to ensure the desired overshoot and settling time. The second part of the paper presents an original design method for 2-DOF Takagi–Sugeno PI-fuzzy controllers based on the stability analysis theorem. Experimental results for the speed control of a servo system with variable load illustrate the performance of the new generic control structures.