Mircea-Bogdan Radac

Bio: Mircea-Bogdan Radac is an academic researcher from Politehnica University of Timișoara. The author has contributed to research in topics: Control system & Control theory. The author has an hindex of 24, co-authored 144 publications receiving 1906 citations. Previous affiliations of Mircea-Bogdan Radac include University of Ottawa.

Model-free sliding mode control of nonlinear systems

Abstract: Two model-free sliding mode control system (MFSMCS) structures are proposed.The sliding mode control of the tracking error dynamics is carried out.The design approaches specific to MFSMCS structures are model-free in tuning.Lyapunov's stability theory is employed in the design approaches.The experimental validation on a twin rotor aerodynamic system is included. This paper proposes two model-free sliding mode control system (MFSMCS) structures. The new structures are compared with a model-free intelligent proportional-integral (iPI) control system structure. Two simple design approaches for the MFSMCS structures are suggested. The control system structures and the design approaches are validated by a set of real-time experimental results on a nonlinear laboratory twin rotor aerodynamic system (TRAS). The MFSMCS structures are considered in the framework of a Multi Input-Multi Output TRAS control system, where the azimuth and pitch positions are controlled using separate Single Input-Single Output control system structures for each control channel (azimuth and pitch). The experimental validation is carried out by two scenarios that illustrate and allow the assessment of the MFSMCS structures performance and the comparison versus a model-free iPI control system structure as well. Display Omitted

Novel Adaptive Gravitational Search Algorithm for Fuzzy Controlled Servo Systems

Abstract: 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.

Stable and optimal fuzzy control of a laboratory Antilock Braking System

Abstract: 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.

Fuzzy logic-based adaptive gravitational search algorithm for optimal tuning of fuzzy-controlled servo systems

Abstract: This study proposes an adaptive gravitational search algorithm (AGSA) which carries out adaptation of depreciation law of the gravitational constant and of a parameter in the weighted sum of all forces exerted from the other agents to the iteration index. The adaptation is ensured by a simple single input–two output (SITO) fuzzy block in the algorithm's structure. SITO fuzzy block operates in the iteration domain, the iteration index is the input variable and the gravitational constant and the parameter in the weighted sum of all forces are the output variables. AGSA's convergence is guaranteed by a theorem derived from Popov's hyperstability analysis results. AGSA is embedded in an original design and tuning method for Takagi-Sugeno proportional-integral fuzzy controllers (T-S PI-FCs) dedicated to servo systems modelled by second-order models with an integral component and variable parameters. AGSA solves a minimisation-type optimisation problem based on an objective function which depends on the sensitivity function with respect to process gain variations, therefore a reduced process gain sensitivity is offered. AGSA is validated by a case study that optimally tunes a T-S PI-FC for position control of a laboratory servo system.Representative experimental results are presented.

Fuzzy Control Systems With Reduced Parametric Sensitivity Based on Simulated Annealing

Abstract: 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.

I and i

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. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

A survey on robotic devices for upper limb

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.

Survey paper: A survey on industrial applications of fuzzy control

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.

Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects

Abstract: Current health services are struggling to provide optimal rehabilitation therapy to victims of stroke. This has motivated researchers to explore the use of robotic devices to provide rehabilitation therapy for strokepatients. This paper reviews the recent progress of upper limb exoskeleton robots for rehabilitation treatment of patients with neuromuscular disorders. Firstly, a brief introduction to rehabilitation robots will be given along with examples of existing commercial devices. The advancements in upper limb exoskeleton technology and the fundamental challenges in developing these devices are described. Potential areas for future research are discussed.

Objective measures, sensors and computational techniques for stress recognition and classification

Abstract: Stress is a major growing concern in our day and age adversely impacting both individuals and society. Stress research has a wide range of benefits from improving personal operations, learning, and increasing work productivity to benefiting society - making it an interesting and socially beneficial area of research. This survey reviews sensors that have been used to measure stress and investigates techniques for modelling stress. It discusses non-invasive and unobtrusive sensors for measuring computed stress, a term we coin in the paper. Sensors that do not impede everyday activities that could be used by those who would like to monitor stress levels on a regular basis (e.g. vehicle drivers, patients with illnesses linked to stress) is the focus of the discussion. Computational techniques have the capacity to determine optimal sensor fusion and automate data analysis for stress recognition and classification. Several computational techniques have been developed to model stress based on techniques such as Bayesian networks, artificial neural networks, and support vector machines, which this survey investigates. The survey concludes with a summary and provides possible directions for further computational stress research.