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Article

Ben Nasr Hichem and M'Sahli Faouzi

The paper aims to present a new concept based on a multi‐agent approach in the area of nonlinear model predictive control (MPC) for fast systems.

Abstract

Purpose

The paper aims to present a new concept based on a multi‐agent approach in the area of nonlinear model predictive control (MPC) for fast systems.

Design/methodology/approach

A contribution to decentralized implementation of MPC is made. The control of the nonlinear system subject to constraints is achieved via a set of actions taken from different agents. The actions are based on an analytical solution and a neural network is used to monitor the closed system using a supervisory loop concept.

Findings

The high online computational need to solve an optimal control actions in nonlinear MPC, which results in a non‐convex optimization, is compared with the new proposed concept. Simulation results show that this approach has very remarkable performances in time computing and target arrival.

Research limitations/implications

In practice, each MPC problem of the individual agent in multi‐agent MPC can run in parallel at the same time, instead of in serial, one agent after another. A parallel processor can be useful for real time implementation. However, it is estimated that how much time can be gained by performing the computations in parallel instead of in serial.

Practical implications

The proposed concept discussed in the paper has the potential to be applied to systems with rapid dynamics.

Originality/value

The multi‐agent MPC compares favorably with respect to a numerical optimization routine and also offers a solution for non‐convex optimization problems in single‐input single‐output systems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 1 no. 3
Type: Research Article
ISSN: 1756-378X

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Article

Gonzalo Garcia, Shahriar Keshmiri and Thomas Stastny

Nonlinear model predictive control (NMPC) is emerging as a way to control unmanned aircraft with flight control constraints and nonlinear and unsteady aerodynamics…

Abstract

Purpose

Nonlinear model predictive control (NMPC) is emerging as a way to control unmanned aircraft with flight control constraints and nonlinear and unsteady aerodynamics. However, these predictive controllers do not perform robustly in the presence of physics-based model mismatches and uncertainties. Unmodeled dynamics and external disturbances are unpredictable and unsteady, which can dramatically degrade predictive controllers’ performance. To address this limitation, the purpose of this paper is to propose a new systematic approach using frequency-dependent weighting matrices.

Design/methodology/approach

In this framework, frequency-dependent weighting matrices jointly minimize closed-loop sensitivity functions. This work presents the first practical implementation where the frequency content information of uncertainty and disturbances is used to provide a significant degree of robustness for a time-domain nonlinear predictive controller. The merit of the proposed method is successfully verified through the design, coding, and numerical implementation of a robust nonlinear model predictive controller.

Findings

The proposed controller commanded and controlled a large unmanned aerial system (UAS) with unsteady and nonlinear dynamics in the presence of environmental disturbances, measurement bias or noise, and model uncertainties; the proposed controller robustly performed disturbance rejection and accurate trajectory tracking. Stability, performance, and robustness are attained in the NMPC framework for a complex system.

Research limitations/implications

The theoretical results are supported by the numerical simulations that illustrate the success of the presented technique. It is expected to offer a feasible robust nonlinear control design technique for any type of systems, as long as computational power is available, allowing a much larger operational range while keeping a helpful level of robustness. Robust control design can be more easily expanded from the usual linear framework, allowing meaningful new experimentation with better control systems.

Originality/value

Such algorithms allows unstable and unsteady UASs to perform reliably in the presence of disturbances and modeling mismatches.

Details

International Journal of Intelligent Unmanned Systems, vol. 3 no. 2/3
Type: Research Article
ISSN: 2049-6427

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Article

Azadeh Ahifar, Abolfazl Ranjbar Noee and Zahra Rahmani

The purpose of this paper is to design a synergetic controller to precisely and quickly track reference signals in robot manipulators. Having smooth control signal this…

Abstract

Purpose

The purpose of this paper is to design a synergetic controller to precisely and quickly track reference signals in robot manipulators. Having smooth control signal this controller enables the nonlinear robot system to track desired references in presence of disturbances in a finite time.

Design/methodology/approach

A new synergetic manifold is introduced here, followed by adding a nonlinear exponential term to it have a precise tracking within a finite time of the desired references with disturbances. Previously the nonlinear term was inserted in the main synergetic equation which makes it complicated due to its hard mathematical approach. Using Lyapunov function, the stability of the system in the presence of disturbances is proved. The validity of the resulted system is confirmed by simulating it in Simulink.

Findings

Using a terminal synergetic controller with new manifold proposed in this work enables system’s state variables to track desired reference signal in the presence of disturbances from any initial condition with proper precision and rate. Simulation results show that compared to similar methods it provides a more proper speed and a finite time convergence with high precision and speed.

Originality/value

Providing fast and precise convergence, the proposed controller can be used in robot manipulator systems which need fast response and also have a precise performance such as in printing 3D objects and any industrial process.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 1
Type: Research Article
ISSN: 0332-1649

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Article

Chao Tao, Jing Wan and Jianliang Ai

The purpose of the paper is to design a robust control system for a generic hypersonic vehicle which includes dynamic nonlinear, open loop unstable and parametric uncertainties.

Abstract

Purpose

The purpose of the paper is to design a robust control system for a generic hypersonic vehicle which includes dynamic nonlinear, open loop unstable and parametric uncertainties.

Design/methodology/approach

For a complex longitudinal model of a generic hypersonic vehicle which includes dynamic nonlinear, open loop unstable and parametric uncertainties, a nonlinear dynamic inverse (NDI) approach combined with proportional differential (PD) control is used to design a strong robust control system to deal with the sensitivity to changes of atmosphere condition. In this way, a simple genetic algorithm is used to search a group of parameters of the control system to satisfy the specific performance indices. Then parametric uncertainties are considered to verify the robustness of the control system.

Findings

The PD hypersonic vehicle control system using NDI approach can satisfy the specific flight performance. And it has strong robustness under the parametric uncertainties.

Originality/value

The paper fulfills a complete process of the nonlinear control system design for a generic hypersonic vehicle. And, the simulation results show the efficiency and robustness of the control system.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

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Article

Slim Frikha, Mohamed Djemel and Nabil Derbel

The purpose of this paper is to present an adaptive neuro‐sliding mode control scheme for uncertain nonlinear systems with Lyapunov approach.

Abstract

Purpose

The purpose of this paper is to present an adaptive neuro‐sliding mode control scheme for uncertain nonlinear systems with Lyapunov approach.

Design/methodology/approach

The paper focuses on neural network (NN) adaptive control for nonlinear systems in the presence of parametric uncertainties. The plant model structure is represented by a NNs system. The essential idea of the online parametric estimation of the plant model is based on a comparison of the measured state with the estimated one. The proposed adaptive neural controller takes advantages of both the sliding mode control and proportional integral (PI) control. The chattering phenomenon is attenuated and robust performances are ensured. Based on Lyapunov stability theorem, the proposed adaptive neural control system can guarantee the stability of the whole closed‐loop system and obtain good‐tracking performances. Adaptive laws are proposed to adjust the free parameters of the neural models.

Findings

Simulation results show that the adaptive neuro‐sliding mode control approach works satisfactorily for nonlinear systems in the presence of parametric uncertainties.

Originality/value

The proposed adaptive neuro‐sliding mode control approach is a mixture of classical neural controller with a supervisory controller. The PI controller is used to attenuate the chattering phenomena. Based on the Lyapunov stability theorem, it is rigorously proved that the stability of the whole closed‐loop system is ensured and the tracking performance is achieved.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 3 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

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Article

Tim Chen, N. Kapronand, C.Y. Hsieh and J. Cy Chen

To guarantee the asymptotic stability of discrete-time nonlinear systems, this paper aims to propose an evolved bat algorithm fuzzy neural network (NN) controller algorithm.

Abstract

Purpose

To guarantee the asymptotic stability of discrete-time nonlinear systems, this paper aims to propose an evolved bat algorithm fuzzy neural network (NN) controller algorithm.

Design/methodology/approach

In evolved fuzzy NN modeling, the NN model and linear differential inclusion representation are established for the arbitrary nonlinear dynamics. The control problems of the Fisher equation and a temperature cooling fin for high-speed aerospace vehicles will be described and demonstrated. The signal auxiliary controlled system is represented for the nonlinear parabolic partial differential equation (PDE) systems and the criterion of stability is derived via the Lyapunov function in terms of linear matrix inequalities.

Findings

This representation is constructed by sector nonlinearity, which converts the nonlinear model to a multiple rule base for the linear model and a new sufficient condition to guarantee the asymptotic stability.

Originality/value

This study also injects high frequency as an auxiliary and the control performance to stabilize the nonlinear high-speed aerospace vehicle system.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

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Article

Femi Thomas and Mija Salomi Johnson

This paper aims to propose output feedback-based control algorithms for the flight control system of a scaled, un-crewed helicopter in its hover flight mode.

Abstract

Purpose

This paper aims to propose output feedback-based control algorithms for the flight control system of a scaled, un-crewed helicopter in its hover flight mode.

Design/methodology/approach

The proposed control schemes are based on H control and composite nonlinear control. The gains of the output feedback controllers are obtained as the solution of a set of linear matrix inequalities (LMIs).

Findings

In the proposed schemes, the finite-time convergence of system states to trim condition is achieved with minimum deviation from the steady-state. As the proposed composite nonlinear output feedback design improves the transient response, it is well suited for a scaled helicopter flight. The use of measured output vector instead of the state vector or its estimate for feedback provides a simple control structure and eliminates the need for an observer in real-time application. The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints.

Practical implications

The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints. They also have significance in applications where the number of measurement quantities needs to be minimized such as in a fully functional rotor-craft unmanned aerial vehicle.

Social implications

The developed output feedback control algorithms can be used in small-scale helicopters for numerous civilian and military applications.

Originality/value

This work addresses the LMI-based formulation and solution of an output feedback controller for a hovering un-crewed helicopter. The stability and robustness of the closed-loop system are proved mathematically and the performance of the proposed schemes is compared with an existing strategy via simulation studies.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

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Article

Zbigniew Krzemiński, Arkadiusz Lewicki and Mirosław Włas

To develop general forms of multiscalar models of the induction motor and to present properties of the sensorless control systems based on such models.

Abstract

Purpose

To develop general forms of multiscalar models of the induction motor and to present properties of the sensorless control systems based on such models.

Design/methodology/approach

Previously presented multiscalar model of the induction motor based on a stator current and rotor flux vector is generalized as a model of type 1. New model of type 2 is defined for stator current and the vector which is directly controlled by a voltage vector. The above models are applied in a sensorless control system with speed observer. Dynamical properties of the sensorless control systems are investigated by simulations and experiments.

Findings

Application of the multiscalar model of type 2 results in higher exactness of sensorless control system than application of the multiscalar model of type 1. Controlled variables are more smooth in transients.

Research limitations/implications

This is not an analytical proof of stability of the control systems.

Practical implications

Provides very useful information for development of sensorless control systems for the induction motor.

Originality/value

This paper extends the known method of nonlinear control of the induction motor to the general form. It is possible to choose the sensorless control system of better properties than those used so far.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 25 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

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Article

Yih‐Guang Leu and Yi‐Xuan Hong

The purpose of this paper is to propose an adaptive output feedback controller using wavelet neural networks with nonlinear parameterization for unknown nonlinear systems

Abstract

Purpose

The purpose of this paper is to propose an adaptive output feedback controller using wavelet neural networks with nonlinear parameterization for unknown nonlinear systems with only system output measurement.

Design/methodology/approach

An error observer is used to estimate the tracking errors through output measurement information, and the wavelet neural networks are utilized to online approximate an unknown control input by adjusting their internal parameters.

Findings

The controller integrates an error observer and wavelet neural networks with nonlinear parameterization into adaptive control design and is derived in accordance with implicit function and mean value theorem. The adjustment mechanism for the parameters of the wavelet neural networks can be derived by means of mean value theorem and Lyapunov theorem, and the stability of the closed‐loop system can be guaranteed.

Originality/value

This paper utilizes the nonlinear parametric wavelet neural networks with estimate state inputs to obtain the adaptive control input for nonaffine systems with only system output measurement, and the nonlinear wavelet parameters can be adjusted efficiently.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 3 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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Article

Chin-Tsung Hsieh, Her-Terng Yau and Cheng-Chi Wang

This study aims to investigate the dynamic motion of an ultrasonic machining system comprising two Duffing oscillators, each with a single degree of freedom. After…

Abstract

Purpose

This study aims to investigate the dynamic motion of an ultrasonic machining system comprising two Duffing oscillators, each with a single degree of freedom. After derivation of the differential equations of the system using the Lagrange equations and dimensionless time, numerical analysis was used to observe changes in the system caused by differences in excitation frequency.

Design/methodology/approach

To suppress this effect and improve performance, proportional differential (PD) control was used. The integral absolute error was used as the fitness function, and particle swarm optimization was used to find the best value for the gain constant of the PD controller.

Findings

The results showed that with specific changes of excitation frequency, the dynamic motion of the system became nonlinear and chaotic behavior resulted. This made the system unstable and affected performance.

Originality/value

A range of methods, including fuzzy control, was used to analyze the results, and exhaustive laboratory work was carried out. Means of control were found that were effective in suppressing the chaotic behavior, and differences in response to control were investigated and verified. The findings of this study can be used as a basis for system parameter settings or control circuit design.

Details

Engineering Computations, vol. 34 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

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