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In the recent years, wireless sensor network technology (WSN) has been widely adopted in precision agriculture for determining the needs of the soil in term of water by monitoring some environmental parameters. To do this, WSN is constructed using several sensor nodes; these small sensing devices are prone to failure and may produce erroneous measurements. To ensure good management of freshwater, the network service quality is necessary. To avoid the degradation of service, the detection of the faulty sensor in WSN is required. In this paper, a fault detection and isolation (FDI) algorithm derived from a parity space approach and based on direct redundancy is proposed toward detecting and isolating sensor fault in WSN. In laboratory experiments, the proposed FDI algorithm proved its effectiveness.

The safety of manipulators systems is receiving a lot of attention these days. Faults have the ability to carry out harmful activities that harm equipment, the environment, or persons. As a result, it is critical to detect and diagnose problems as soon as possible, as well as to incorporate fault tolerance to avoid performance deterioration and harmful circumstances. Robust sensor fault detection and isolation (FDI) as well as fault-tolerant control (FTC) for a robotic system are discussed in this work. The goal of this research is to create an FDI method that uses a super-twisting third-order sliding mode (STW-TOSM) observer to estimate residual signals. A suggested system based on a higher-order sliding mode (HOSM) observer/controller approaches is used to accomplish this. In comparison to an active FTC technique, the test results demonstrate high level of performance. Finally, simulation results illustrate the efficacy of the presented techniques.

Pumping water is one of the most popular technologies of solar energy for irrigation or drinking water supply. Its performance depends on the characteristics of the site (sunlight, ambient temperature, geographical obstacles), on the performance of the modules, as well as, on the characteristics of other equipment (converter and pump). The optimal sizing of a photovoltaic water pumping system makes it possible to guarantee the satisfaction of the water demand throughout the irrigation period and to model the electrical energy needs to supply the pump to irrigate the crops and water livestock. This paper proposed a novel algorithm for dimensioning the elements of an autonomous photovoltaic system equipped with irrigation water storage. The proposed algorithm determines the optimal surface area of the photovoltaic modules and the electrical power necessary to satisfy the water requirement for irrigation in the observed time. The results obtained from the proposed algorithm for optimal sizing are compared to calculation scenarios to show better results. A case study from the Fez-Meknes region in Morocco has been selected for applying the optimal sizing algorithm.

Wireless Sensor Network (WSN) technology plays an important role in the application of smart irrigation by monitoring environmental soil conditions, which helps determine the amount of water required for an agricultural field. These sensors are exposed to harsh environmental conditions over long period of time and became prone to failure. These failures may lead the base station to take the wrong decision. This Paper presents a centralized approach toward detecting and isolating sensor fault in WSN using analytical redundancy which to achieve water saving and guarantee a good crop quality. Simulation results are proved the effectiveness of the proposed method.

Water is an indispensable resource in agriculture, and with the likely increase in restrictions on the volumes of water allocated to agriculture, irrigation is required to meet the needs of plants. In this sense, this article proposes the design and implementation of an intelligent irrigation system based on the IoT architecture. These systems are designed especially for urban areas where remote IoT devices don’t have direct access to the internet or power grids and where wireless communications are difficult.

For the high risk of accidents when the vehicle is under braking condition, a robust controller of the vehicle longitudinal dynamic is required. This paper presents an adaptive robust fractional-order sliding mode controller of the vehicle longitudinal dynamic that takes into account uncertainties and disturbances (such as road conditions, vehicle loading, and variable parameters) at the design stage. The controller is designed according to the sliding mode control theory and the Lyapunov stability theorem to ensure both the system stability and the tracking of the desired slip ratio. The effectiveness and high performances of the proposed control strategy are demonstrated by a simulation example. Also, a comparison with the conventional sliding mode controller has been performed, showing the advantages of our proposal.

The autonomy of the photovoltaic pumping system and the need for water irrigation are the most demanding criteria that can only be satisfied by the reliability of the installation, which depends essentially on the size of the system components. In this regard, this paper presents an approach to optimize the element size of photovoltaic water pumping systems. This approach ensures the satisfaction of the water demand throughout the irrigation period. It is based on several criteria for optimal sizing including the characteristics of panels, sites, and also crops. A case study of the Fez-Meknes region in Morocco is selected to apply the optimal sizing approach to ensure its effectiveness.

The aim of this study is to design and analyze a fault detection and isolation technique (FDI) for a class of affine nonlinear systems using observer-based technique. The observer is applied for robot manipulator in order to detect and isolate sensor fault. The simulations results prove the effectiveness, performances and the robustness of the approach.

The inverse kinematic analysis is required in many technical applications. Due to the non linearity of the system, resolving the Inverse Kinematics (IK) for robotic system becomes more challenging problem. In this chapter, the problem of IK for medical application is faced, based on human lower limb as being the three arm robotic system depending on the physiological constaints. A system analysis is carried out specially in three dimensionnel space. The developed forward kinematic model leads to define the feasible workspace of the human leg in the considered configuration. A constructive algorithm to compute the optimal IK of robot system is outlined, based on human performance measure that incorporates a new objective function of musculoskeletal discomfort. The effectiveness of the proposed approach is tested, and the algorithmic complexity is finally discussed.

Cloud Robotics (CR) is a rising field of robotics rooted in cloud computing, cloud storage, and other Internet technologies centered around the benefits of converged infrastructure and shared services. It allows robots to benefit from the powerful computational, storage, and communications resources of modern data centers. In addition, it removes overheads for maintenance and updates, and reduces dependence on custom middleware. This chapter reviews the concept of cloud-enabled robotics with some of the most applications related to it. Also, it explores the trends of robotic technology in Industry 4.0. Since the advent of Information and Communication Technologies (ICT), economies around the world have ground dramatically as companies can compete on a global scale. The Fourth Industrial Revolution will be based on cyber-physical systems, the Internet of Things and Internet of Services.

Fault detection and isolation (FDI) techniques is becoming one of the most phenomena in robotics in order to ensure higher levels of safety and productivity. Research, has been produced a considerable effort in seeking systematic approaches to fault detection for both linear and non-linear dynamical systems. In this paper, we present a high gain based observer to solve fault detection and isolation scheme for a class of affine non-linear systems. In order to test the effectiveness of the proposed approach, a case study is developed, based on simulation for a special robot manipulator named Articulated Nimble Adaptable Trunk ”ANAT” for five-degree-of-freedom in order to detected and isolated sensor fault.

Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of a residual generator for FDI in nonlinear systems which are affine in the control signals and in the failure modes is studied. The (FDI) approach is used to detect sensor faults on a robot manipulator that occurs on a system's specific component. The sliding mode observer is one of the FDI's methods, which are used to generate residuals when sensor faults is presented. This paper aims to improve the detection of sensor faults for an affine nonlinear system class. For a better detection of faults, a proportional derivative (PD) controller is used to improve the system's stability. Both the aforementioned method and the (PD) controller are based on the Lyapunov equation. The proposed approach is verified in simulation on a robot manipulator.

The object of this paper is to study the problem of robust stabilizability for a class of continuous-time Linear Systems with Markovian Jumps (LSMJ) and saturated input. Sufficient conditions for stochastic stabilizability with constrained control input are given in terms of Linear Matrix Inequalities (LMIs). The approach gives a direct expression of the linear state feedback controller that respects the condition of saturation. Also, the robustness of these systems for four types of structural uncertainties: (1) matching conditions, (2) norm bounded, (3) value bounded and (4) linear combinations is treated. Finally, numerical examples are given to illustrate the usefulness of the proposed results.

This paper presents a new accurate multiple model of nonlinear pneumatic lateral forces. The bicycle representation is used in order to build up an easy implemented vehicle dynamic model. Moreover, the Takagi&ndash, Sugeno fuzzy approach is applied in order to handle the vehicle model nonlinearities. This structure allows for taking into account the small variation of the vehicle longitudinal velocity. Subsequently, a Fault Tolerant Control strategy that is based on a bank of fuzzy Luenberger observers is proposed. The robustness of the control scheme against external noises is guaranteed by applying H&infin, performance. Sufficient stability conditions that are based on Lyapunov method are formulated as Linear Matrix Inequality. Thus, allowing the computation of the observers&rsquo, and the controllers&rsquo, gains by using MATLAB. Finally, the simulation examples are performed to show the effectiveness of our proposal.

In robotics various factors must be take into account for task execution in the presence of a fault. Fault detection and isolation (FDI) are very important for systems in industrial applications. One of the popular approaches is model-based fault detection. In this works, a fault detection and isolation scheme is presented for class of affine nonlinear systems to detect sensor fault for a hyper redundant articulated nimble adaptable trunk (ANAT) robot for five-degree-of-freedom. Simulation results are provided to show the performance of the detection and isolation of the methods.