Author

# Radu-Emil Precup

Other affiliations: University of Ottawa, West University of Timișoara, Edith Cowan University

Bio: Radu-Emil Precup is an academic researcher from Politehnica University of Timișoara. The author has contributed to research in topics: Fuzzy control system & Fuzzy logic. The author has an hindex of 51, co-authored 403 publications receiving 6624 citations. Previous affiliations of Radu-Emil Precup include University of Ottawa & West University of Timișoara.

##### Papers published on a yearly basis

##### Papers

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TL;DR: A survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000 is presented.

Abstract: 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.

475 citations

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TL;DR: Relations for PI and PID controller tuning based on a generalization of the relations after symmetrical optimum method, introduced by Kessler, for a class of systems specific to the field of electrical drives.

Abstract: The paper presents relations for PI and PID controller tuning based on a generalization of the relations after symmetrical optimum (SO) method, introduced by Kessler (Regelungstechnik, 6 (1958), 395-400 and 432-436), for a class of systems specific to the field of electrical drives. The tuning relations, based on a method developed by Preitl and Precup (Transactions on AC and CS 41(55), (1996) 47-55; 42(56) (1997) 97-105), offer values for controller parameters in accordance with previously accepted desired performance. In the case of plants with time-invariant parameter k"P, the tuning after the given relations has the advantage of a maximum value of phase margin (@f"r"M). In the case of plants with time-variant k"P, the given relations enable the computation of controller parameters by fulfilling a minimum guaranteed value of the phase margin (@f"r"m).

239 citations

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TL;DR: The tuning approach is validated in an experimental case study of a position control for a laboratory nonlinear servo system, and TSK PI-FCs with a reduced process small time constant sensitivity are offered.

Abstract: This paper proposes an innovative tuning approach for fuzzy control systems (CSs) with a reduced parametric sensitivity using the Grey Wolf Optimizer (GWO) algorithm. The CSs consist of servo system processes controlled by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs). The process models have second-order dynamics with an integral component, variable parameters, a saturation, and dead-zone static nonlinearity. The sensitivity analysis employs output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The GWO algorithm is used in solving the optimization problems, where the objective functions include the output sensitivity functions. GWO's motivation is based on its low-computational cost. The tuning approach is validated in an experimental case study of a position control for a laboratory nonlinear servo system, and TSK PI-FCs with a reduced process small time constant sensitivity are offered.

230 citations

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TL;DR: The least-squares algorithm specific to Virtual Reference Feedback Tuning is replaced with a metaheuristic optimization algorithm, i.e. Grey Wolf Optimizer, to exploit the advantages of data-driven control and fuzzy control.

Abstract: This paper proposes the Virtual Reference Feedback Tuning (VRFT) of a combination of two control algorithms, Active Disturbance Rejection Control (ADRC) as a representative data-driven (or model-free) control algorithm and fuzzy control, in order to exploit the advantages of data-driven control and fuzzy control. The combination of Active Disturbance Rejection Control with Proportional-Derivative Takagi-Sugeno Fuzzy Control (PDTSFC) tuned by Virtual Reference Feedback Tuning results in two novel data-driven algorithms referred to as hybrid data-driven fuzzy ADRC algorithms. The main benefit of this combination is the automatic optimal tuning in a model-free manner of the parameters of the combination of Active Disturbance Rejection Control with Proportional-Derivative Takagi-Sugeno Fuzzy Control called ADRC-PDTSFC. The second benefit is that the suggested combination is time saving in finding the optimal parameters of the controllers. However, since Virtual Reference Feedback Tuning generally works with linear controllers to solve a certain optimization problem and the fuzzy controllers are essentially nonlinear, this paper replaces the least-squares algorithm specific to Virtual Reference Feedback Tuning with a metaheuristic optimization algorithm, i.e. Grey Wolf Optimizer. The fuzzy control system stability is guaranteed by including a limit cycle-based stability analysis approach in Grey Wolf Optimizer algorithm to validate the next solution candidates. The hybrid data-driven fuzzy ADRC algorithms are validated as controllers in terms of real-time experiments conducted on three-degree-of-freedom tower crane system laboratory equipment. To determine the efficiency of the new hybrid data-driven fuzzy ADRC algorithms, their performance is compared experimentally with that of two control algorithms, namely Active Disturbance Rejection Control with Proportional-Derivative Takagi-Sugeno Fuzzy Control, whose parameters are optimally tuned by Grey Wolf Optimizer in a model-based manner using the nonlinear process model.

186 citations

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TL;DR: This paper proposes the design of fuzzy control systems with a reduced parametric sensitivity making use of Gravitational Search Algorithms (GSAs), and suggests a GSA with improved search accuracy.

Abstract: 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.

150 citations

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TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.
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TL;DR: In this paper, two major figures in adaptive control provide a wealth of material for researchers, practitioners, and students to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs.

Abstract: This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

1,814 citations

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TL;DR: A review of robotic devices for upper limb rehabilitation including those in developing phase is document in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices.

Abstract: The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future The patient population needing physical rehabilitation of the upper extremity is also constantly increasing Robotic devices have the potential to address this problem as noted by the results of recent research studies However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems

851 citations