Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

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A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges

International Joint Conference on Neural Networks

In order to optimize the speed-control performance of the permanent-magnet synchronous motor (PMSM) system with different disturbances and uncertainties, a nonlinear speed-control algorithm for the PMSM servo systems using sliding-mode control and disturbance compensation techniques is developed in this paper. First, a sliding-mode control method based on one novel sliding-mode reaching law (SMRL) is presented. This SMRL can dynamically adapt to the variations of the controlled system, which allows chattering reduction on control input while maintaining high tracking performance of the controller. Then, an extended sliding-mode disturbance observer is proposed to estimate lumped uncertainties directly, to compensate strong disturbances and achieve high servo precisions. Simulation and experimental results both show the validity of the proposed control approach.

Nonlinear Speed Control for PMSM System Using Sliding-Mode Control and Disturbance Compensation Techniques

In this paper, sliding-mode control is applied on multi-input/multi-output (MIMO) nonlinear systems. A novel approach is proposed, which allows chattering reduction on control input while keeping high tracking performance of the controller in steady-state regime. This approach consists of designing a nonlinear reaching law by using an exponential function that dynamically adapts to the variations of the controlled system. Experimental study was focused on a MIMO modular robot arm. Experimental results are presented to show the effectiveness of the proposed approach, regarding particularly the chattering reduction on control input in steady-state regime.

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Sliding-Mode Robot Control With Exponential Reaching Law

This paper presents the design of a controller based on the block control technique combined with the super twisting control algorithm for trajectory tracking of a quadrotor helicopter. A first order exact differentiator is used in order to estimate the virtual control inputs, which simplifies the control law design. In addition, the wind parameter resulting from the aerodynamic forces is also estimated in order to ensure robustness against these unmatched perturbations. The stability and finite time convergence of the exact differentiator have been recently proved by means of Lyapunov functions, and therefore the stability analysis of the proposed controller has been carried out along the same lines. The performance and effectiveness of the proposed controller are tested in a simulation study taking into account external disturbances.

Robust block second order sliding mode control for a quadrotor

The inspection of high voltage power transmission lines is mainly carried out by manned aerial vehicles or foot patrol. However, these maintenance methodologies for inspection are somehow inefficient and expensive. Moreover, helicopter assisted inspection endangers the human life. Recently, unmanned aerial vehicles have been under development in several research centers all over the world due to its potential applications. In this paper, we present an unmanned aerial system based on the quadrotor helicopter for high voltage power line inspection. Our interest is to equip the quadrotor helicopter with the necessary payload in order to be able to carry out a qualitative inspection, therefore the hardware architecture of the aerial robotic system is presented. Finally, some experimental results are shown to demonstrate the feasibility of the proposed system.

Power line inspection via an unmanned aerial system based on the quadrotor helicopter

In this paper, we propose a solution to the well-known problem of ensuring a simultaneous globally convergent online estimation of the state and the frequencies of a sinusoidal signal composed of n sinusoidal terms. We present an estimator which guarantees global boundedness and convergence of both the state estimation and the frequency estimation for all initial conditions and frequency values.

A globally convergent estimator for n-frequencies

In this paper, a controller for induction motors is proposed. A continuous feedback is first applied to obtain a discrete-time model in closed form. Then, on the basis of these exact sampled dynamics, a discrete-time controller ensuring speed and flux modulus reference tracking is determined, making use of the sliding mode technique. The resulting controller is hence hybrid, in the sense that it contains both continuous and discrete-time terms. It is shown how to implement such a hybrid controller using the so-called exponential holder, which is the only device to be implemented analogically, together with an analog integrator. Moreover, a discrete-time reduced-order observer is designed for rotor fluxes and load torque estimation. The performance of the proposed controller is finally studied by simulation and experimental tests.

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Hybrid Control of Induction Motors via Sampled Closed Representations

An adaptive discrete-time tracking controller for a direct current motor with controlled excitation flux is presented. A recurrent neural network is used to identify the plant model; this neural identifier is trained with an extended Kalman filter algorithm. Then, the discrete-time block-control and sliding-mode techniques are used to develop the trajectory tracking. This paper also includes the respective stability analysis for the whole closed-loop system. The effectiveness of the proposed control scheme is verified via real-time implementation.

Bernardino Castillo-Toledo

Papers

Robust block second order sliding mode control for a quadrotor

Power line inspection via an unmanned aerial system based on the quadrotor helicopter

A globally convergent estimator for n-frequencies

Hybrid Control of Induction Motors via Sampled Closed Representations

Discrete-Time Neural Sliding-Mode Block Control for a DC Motor With Controlled Flux