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A data-based approach for designing adaptive controllers for unknown systems

A data-based approach for designing adaptive controllers for...

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International symposium on Communications control and Signal processing (ISCCSP)

作者： Sofiane Khadraoui Hazem Nounou Mohamed Nounou Aniruddha Datta Department of Electrical and Computer Engineering Texas A&M University TX USA

This paper presents an approach for designing gain-scheduled controllers for unknown systems using a set of measured data. In most control approaches, controllers are designed using a mathematical model, which is often obtained on the basis of some simplifying assumptions. Thus, controllers designed through model-based methods may result in degradation of the desired closed-loop performance due to complex dynamics. Hence, the proposed approach is motivated by the fact that: 1) errors associated with the modeling process are avoided since no mathematical model is required for the controller design, 2) the designed adaptive controllers are able to ensure desired performance specifications for the plant operated not only at a given operating point but over a range of operating conditions, and 3) the controller structure can be selected a priori. A simulation example to control a water heating system is presented to validate the proposed method.

关键词： Water heating Frequency response Mathematical model Frequency measurement control design Adaptation models

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Approximate real-time optimal control based on sparse Gaussian process models

Approximate real-time optimal control based on sparse Gaussi...

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IEEE symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Joschka Boedecker Jost Tobias Springenberg Jan Wülfing Martin Riedmiller Department of Computer Science University of Freiburg Freiburg Germany

In this paper we present a fully automated approach to (approximate) optimal control of non-linear systems. Our algorithm jointly learns a non-parametric model of the system dynamics - based on Gaussian process Regression (GPR) - and performs receding horizon control using an adapted iterative LQR formulation. This results in an extremely data-efficient learning algorithm that can operate under real-time constraints. When combined with an exploration strategy based on GPR variance, our algorithm successfully learns to control two benchmark problems in simulation (two-link manipulator, cart-pole) as well as to swing-up and balance a real cart-pole system. For all considered problems learning from scratch, that is without prior knowledge provided by an expert, succeeds in less than 10 episodes of interaction with the system.

关键词： Approximation methods Trajectory Computational modeling Optimization Predictive models Approximation algorithms Optimal control

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Nature-inspired optimization algorithms applied to fuzzy control, fuzzy modeling, mobile robots and optical character recognition

Nature-inspired optimization algorithms applied to fuzzy con...

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International symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Radu-Emil Precup Universitatea Politehnica din Timisoara Timisoara RO

Summary form only given. The plenary talk deals with the presentation of several applications of nature-inspired optimization algorithms (NIOAs) obtained by the process control group of the Department of Automation and Applied Informatics with the Politehnica University of Timisoara, Romania. The algorithms include Simulated Annealing (SA), Particle Swarm Optimization (PSO), Gravitational Search Algorithms (GSAs), Charged System Search (CSS), hybrid and adaptive versions. Aspects concerning the design and tuning of Mamdani and Takagi-Sugeno fuzzy controllers with dynamics focused on proportional-integral fuzzy controllers (PI FCs) and the general formulation of Takagi-Sugeno fuzzy models are first discussed. The optimal tuning of fuzzy controllers is carried out by the definition of optimization problems with the tuning parameters of the fuzzy controllers defined as vector variables, and with objective functions expressed as the weighted sums of functions that depend on the (absolute or squared) control error and of the output sensitivity functions of the state sensitivity models with respect to process parametric variations. The NIOAs minimize the objective functions to achieve optimal fuzzy control systems with reduced parametric sensitivity, and optimal PI-FCs for nonlinear servo systems are offered. The NIOAs are next applied to the optimal tuning of the parameters of Takagi-Sugeno fuzzy models for Anti-lock Braking systems and for magnetic levitation systems. Initial Takagi-Sugeno fuzzy models of the process are derived on the basis of the modal equivalence principle by placing a set of linearized process models at several operating points in the rule consequents. The vector variables in the optimization problems are a part of the parameters of the input membership functions. The NIOAs are inserted in optimal path planning algorithms for mobile. The multi-objective optimization is considered as the NIOAs use two to four objective functions to generate optimal t

关键词： Optimization Algorithm design and analysis Optical character recognition software Tuning Linear programming Informatics Takagi-Sugeno model

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Computing skills in aviation ergatic systems

Computing skills in aviation ergatic systems

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International symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Pavol Kurdel Tobias Lazar Ján Labun Department of Avionics Technical University of Kosice Kosice Slovakia

Recent aviation technologies are characterized by high flight security guaranteed by wide information basis, which decreases error tolerance range on a large scale. It is tolerant towards flight parameters entropy, it is obtained by using cybernetic systems, which shape human - operator - control abilities in more and more urgent way. The existence of mutuality of intolerance needs requires narrow information connection between the machine (aircraft) and the person (its operator). In the presented paper the intolerance is perceived as an ergatic effect, the principle of which is based on machine artificial intelligence and human natural intelligence. Learning is the common name of presented intellects, i.e. perception of error existence, their recognition and compensation. Locomotion organs (most frequently arms and legs) present the disposition of the human - operator for entering control process, the dynamics and amplitude relevance are the result of the transformation of information flows worked out by his intellect. Degree and quality of informative evaluation of the situation (in time) of mutuality of the position (aircraft) and required position of the control is decided by the operator. In the paper, the adequacy of visible movement is called a skill. The development of the operator pilot skills is based on many factors. His improvement is a subject of physical laws, mathematical model of which is presented in the paper and explained by an example.

关键词： Vectors Mathematical model Aircraft control systems Informatics Aerospace control Concrete

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Data-driven partially observable dynamic processes using adaptive dynamic programming

Data-driven partially observable dynamic processes using ada...

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IEEE symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Xiangnan Zhong Zhen Ni Yufei Tang Haibo He Department of Electrical University of Rhode Island Kingston RI USA

ISBN: (纸本)9781479945511

Adaptive dynamic programming (ADP) has been widely recognized as one of the “core methodologies” to achieve optimal control for intelligent systems in Markov decision process (MDP). Generally, ADP control design requires all the information of the system dynamics. However, in many practical situations, the measured input and output data can only represent part of the system states. This means the complete information of the system cannot be available in many real-world cases, which narrows the range of application of the ADP design. In this paper, we propose a data-driven ADP method to stabilize the system with partially observable dynamics based on neural network techniques. A state network is integrated into the typical actor-critic architecture to provide an estimated state from the measured input/output sequences. The theoretical analysis and the stability discussion of this data-driven ADP method are also provided. Two examples are studied to verify our proposed method.

关键词： Dynamic programming Performance analysis Neural networks Optimal control Stability analysis Equations Markov processes

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A dynamic angle calibration method for sensored FOC-controlled IPMSM in field weakening region

A dynamic angle calibration method for sensored FOC-controll...

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International symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM

作者： Florian Ludwig Habil. Andreas Möckel Technische Universitat Ilmenau Ilmenau ThÃ¼ringen DE

In this paper a new method of dynamic flux angle adjustment as a function of field weakening d-axis current by passing through a pre-application teach-in process is proposed. The aim is to reduce torque ripple, power dissipation in the electric drive system and instability of the current control loop caused by faulty rotor flux angle information. Torque-forming parts of the supposed d-current are measured at idle and iteratively forced to zero by varying the actual flux angle. Experiments showed that the proposed calibration method is able to compensate flux angle shifts and their effects on the operation behavior at field weakening.

关键词： Calibration Rotors Torque Stators Microcontrollers dynamics Power systems

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FVMS Software-in-the-Loop Flight Simulation Experiments: Guidance, Navigation and control

FVMS Software-in-the-Loop Flight Simulation Experiments: Gui...

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IEEE Latin American Robotics symposium, LARS

作者： Romulo Rodrigues Rafael C.B. Sampaio A. Pedro Aguiar Marcelo Becker Department of Electrical and Computer Engineering University of Porto (FEUP) Porto Portugal Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR

This paper proposes a new and powerful methodology to the evaluation of guidance, navigation and control algorithms (GNC) in Software-in-the-Loop (SiL) flight simulation using Microsoft Flight Simulator (MSFS). The SiL was assisted by the Flight Variables Management System (FVMS), a Graphic User Interface (GUI) that fully interfaces communication between MSFS and general purpose custom GNC algorithms. The originality of this new approach is to make the FVMS communication layer completely transparent to the designer so that full attention may be focused exclusively on guidance algorithm development and the debugging process as well. Furthermore, the application may be extended to both multi-engine fixed and rotary wing aircraft. When it comes to the design, development and validation of brand new control algorithms of GNC for unmanned systems, SiL flight simulation becomes an exceedingly useful tool since end-product may misbehave in-flight. It impacts over avoiding hazard situation of crew and population in the ground and on preserving expensive equipment of being damaged. To illustrate FVMS capabilities and assets on GNC systems design, a nonlinear path following algorithm is set up. FVMS GNC module is endowed with a full map interface and a mission management through which one may build/rebuild the UAV path on-line. The results demonstrate the potential of the framework on the implementation of either simple or more complex solutions for the GNC problem.

关键词： Vehicles Libraries Navigation Aircraft Algorithm design and analysis Computer architecture Vehicle dynamics

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Using System dynamics to Integrate Spatial-Temporal Model in Taiwan Coastal Zone

Using System Dynamics to Integrate Spatial-Temporal Model in...

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International symposium on Computer, Consumer and control (IS3C)

作者： Tsung Fu Lin Yan Ping Chi Department of Management Information Systems National Chengchi University Taipei City Taiwan

ISBN: (纸本)9781479952786

Coastal area has abundant resources however, overdevelopment and utilization by mankind has caused severe abuse of original landscapes. In order to mitigate such deterioration, the concept of Integrated Coastal Zone Management (ICZM) has been proposed to take measurements of geographic nature, applied construction, ecology system, economic value and environmental protection. The objective is to establish a reasonable utilization and sustainable development goal. However, most of the studies on coastal zone management are focused on qualitative approaches or quantitative modules such as sequential (i.e. statistics model) or spatial (i.e. geographic information system) assessment. It is seldom to apply integrated spatial-temporal model with artificial decision assessment, therefore this study combines both system dynamic (SD) which is best known in process timing dynamic complexity, causal loop and timing stagnant, together with cellular automata (CA), which can effectively present spatial interactions of each parameters, to develop a set of integrated spatial and temporal assessment system for coastal area. The objective is to facilitate decision maker or managers to conduct simulation and strategic analysis based on various subjects and modules, and lay out a sustainable coastal management strategy.

关键词： Sea measurements Biological system modeling Complexity theory Economics Automata Market research Environmental factors

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Three-term relation neuro-fuzzy cognitive maps

Three-term relation neuro-fuzzy cognitive maps

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International symposium on Computational Intelligence and Informatics

作者： Michal Puheim Ján Vaščák Ladislav Madarász Technicka univerzita v Kosiciach Kosice KoÅ¡ice SK Department of Cybernetics and Artificial Intelligence Technical University of Kosice Košice Slovak Republic

In this paper, we propose a novel approach to modeling using fuzzy cognitive maps, which we refer to as the Three-Term Relation Neuro-Fuzzy Cognitive Map or simply the TTR NFCM. The proposed method is mostly suited to model complex nonlinear technical systems with dynamic internal characteristics. With this method we aim to solve some of the most critical problems of the conventional fuzzy cognitive maps. We target two of these problems by hybridization with artificial neural networks. First of them is a linear nature of relations between the concepts. The second is a lack of mutual dependence between the relations connecting to the same concept. Finally, we tackle a problem of relation dynamics using an inspiration from the control engineering. While focusing on bringing these advanced additional methods to the design of cognitive maps, we also aim to keep the degree of dependency on expert knowledge on the same level as with the conventional fuzzy cognitive maps. We achieve this by utilizing the machine learning methods. However, since the proposed method is heavily dependent on automated data-driven learning, it is suitable mainly for systems which are well observable and can produce sufficient training datasets.

关键词： Fuzzy cognitive maps Computational modeling Approximation methods process control Visualization Computational intelligence Informatics

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Learning system for myoelectric prosthetic hand control by forearm amputees

Learning system for myoelectric prosthetic hand control by f...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Haruhisa Kawasaki Masayasu Kayukawa Hirofumi Sakaeda Tetsuya Mouri Faculty of Engineering Gifu University Gifu Japan Gifu Red Cross Hospital Gifu Japan Gifu Daigaku Gifu Gifu JP

This paper presents a novel learning system for myoelectric prosthetic hand control by forearm amputees using estimations of continuous joint angles. Wavelengths calculated using surface electromyogram (sEMG) signals of forearm amputees are input into a neural network (NN); past inputs are also used to take finger dynamics into consideration when estimating the metacarpophalangeal joint angles of each finger and wrist joint angle of pronation/supination and palmar flexion/dorsiflexion. The learning system has a three-step learning dataset generation process: (1) continuous motion of a virtual prosthetics hand (VR-hand) and motion timing bar are displayed to a subject; (2) the subject contracts his/her muscles following the VR-hand motion; and (3) sEMG signals and joint angles of VR-hand are measured and saved as the learning dataset. This system does not need to measure actual joint angles. To demonstrate the effectiveness of this learning system, RMS error of joint angle estimations are presented in cases of a motion set with 8 patterns for a healthy subject, and a motion set with 4 patterns for a right forearm amputee.

关键词： Joints Thumb Muscles Wrist Artificial neural networks Learning systems

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