Modelling and Fast Terminal Sliding Mode Control for Mirror-based Pointing Systems

In this paper, we present a new discrete-time Fast Terminal Sliding Mode (FTSM) controller for mirror-based pointing systems. We first derive the decoupled model of those systems and then estimate the parameters using a nonlinear least-square identification method. Based on the derived model, we design a FTSM sliding manifold in the continuous domain. We then exploit the Euler discretization on the designed FTSM sliding surfaces to synthesize a discrete-time controller. Furthermore, we improve the transient dynamics of the sliding surface by adding a linear term. Finally, we prove the stability of the proposed controller based on the Sarpturk reaching condition. Extensive simulations, followed by comparisons with the Terminal Sliding Mode (TSM) and Model Predictive Control (MPC) have been carried out to evaluate the effectiveness of the proposed approach. A comparative study with data obtained from a real-time experiment was also conducted. The results indicate the advantage of the proposed method over the other techniques.Comment: In Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018

Evaluating Yield Performance of Cowpea Varieties under Sole And Intercropping with Sorghum at Bauchi, Nigeria

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Fast terminal sliding mode control for gantry cranes

Cranes remain a vital tool for the construction of infrastructure such as buildings, bridges, etc. Recently, there has been renewed interest in crane automation in dealing with concerns on safety and possible performance degradation due to system uncertainties and disturbances. One potential solution to the problem is the use of robust techniques based on the Sliding Mode Control (SMC) methodology. Much research has been conducted to design controllers based on linear sliding surfaces, aiming at achieving the desired control performance in finite time. In this context, this paper proposes a control method, based on the Fast Terminal Sliding Mode (FTSM), to guarantee finite-time stability of the crane. To do that, we have derived a mathematical model of the crane using Lagrangian formulation with uncertainties as bounding functions. Then, sliding surfaces based on the hierarchical sliding mode are defined, and a control law is derived using the Lyapunov stability theory. The hierarchical sliding surfaces consist of two layers. The first layer include sliding functions based on FTSM to enable faster convergence of the system to equilibrium. This can have advantages in high precision tracking applications. In the second-layer, the sliding surface is designed from the linear combination of the first layer sliding functions. Also, we have given a proof of the stability of the system in finite time. Extensive simulation results show the proposed controller based on FTSM can achieve higher performance in stabilizing the swinging load of a gantry crane. Laboratorial experiments have been conducted to verify the obtained results in terms of the superior convergence time and improved performance over conventional SMC

Adaptive second-order sliding mode control of UAVs for civil applications

Quadcopters, as unmanned aerial vehicles (UAVs), have great potential in civil applications such as surveying, building monitoring, and infrastructure condition assessment. Quadcopters, however, are relatively sensitive to noises and disturbances so that their performance may be quickly downgraded in the case of inadequate control, system uncertainties and/or external disturbances. In this study, we deal with the quadrotor low-level control by proposing a robust scheme named the adaptive second-order quasi-continuous sliding mode control (adaptive 2-QCSM). The ultimate objective is for robust attitude control of the UAV in monitoring and inspection of built infrastructure. First, the mathematical model of the quadcopter is derived considering nonlinearity, strong coupling, uncertain dynamics and external disturbances. The control design includes the selection of the sliding manifold and the development of quasi-continuous second-order sliding mode controller with an adaptive gain. Stability of the overall control system is analysed by using a global Lyapunov function for convergence of both the sliding dynamics and adaptation scheme. Extensive simulations have been carried out for evaluation. Results show that the proposed controller can achieve robustness against disturbances or parameter variations and has better tracking performance in comparison with experimental responses of a UAV in a real-time monitoring task

Low-latency vision-based fiducial detection and localisation for object tracking

Real-time vision systems are widely-used in construction and manufacturing industries. A significant proportion of computational resources of such systems is used in fiducial identification and localisation for motion tracking of moving targets. The requirement is to localise a pattern in an image captured by the vision system precisely, accurately, and with a minimum available computation time. As such, this paper presents a class of patterns and, accordingly, proposes an algorithm to fulfil the requirement. Here, the patterns are designed using circular patches of concentric circles to increase the probability of detection and reduce cases of false detection. In the detection algorithm, the image captured by the vision system is first scaled down for computationally-effective processing. The scaled image is then separated by filtering only the colour components, which are made up of outer circular patches in the proposed pattern. A blob detection algorithm is then implemented for identifying inner circular patches. The inner circles are then localised in the image by using the colour information obtained. Finally, the localised pattern, along with the camera and distortion matrix of the vision system, is applied in a perspective-n-point solving algorithm to estimate the marker orientation and position in the global coordinate system. Our system shows significant enhancement in performance of fiducial detection and identification and achieves the required latency of less than ten milliseconds. Thus, it can be used for infrastructure monitoring in many applications that involve high-speed real-time vision systems

Bladder neck contracture-incidence and management following contemporary robot assisted radical prostatectomy technique

PurposeBladder neck contracture (BNC) is a well-recognized complication following robot-assisted radical prostatectomy (RARP) for treatment of localized prostate cancer with a reported incidence of up to 1.4%. In this series, we report our institutional experience and management results.MethodsA prospectively collected database of patients who underwent RARP by a single surgeon from 2006 to 2012 was reviewed. Watertight bladder neck to urethral anastomosis was performed over 18-French foley catheter. BNC was diagnosed by flexible cystoscopy in patients who developed symptoms of bladder outlet obstruction. Subsequently, these patients underwent cold knife bladder neck incisions. Patients then followed a strict self regimen of clean intermittent catheterization (CIC). We identify the patient demographics, incidence of BNC, associated risk factors and success of subsequent management.ResultsTotal of 930 patients who underwent RARP for localized prostate cancer was identified. BNC was identified in 15 patients, 1.6% incidence. Mean patient age and preoperative prostate-specific antigen was 58.8 years old and 7.83 ng/mL (range, 2.5-14.55 ng/mL) respectively. Mean estimated blood loss was 361±193 mL (range, 50-650 mL). Follow-up was mean of 23.4 months. Average time to BNC diagnosis was 5.5 months. In three patients, a foreign body was identified at bladder neck. On multivariate analysis, estimated blood loss was significantly associated with development of BNC. All patients underwent cystoscopy and bladder neck incision with a 3-month CIC regimen. Out of 15 index patients, none had a BNC recurrence over the follow-up period.ConclusionsBNC was identified in 1.6% of patients in our series following RARP. Intraoperative blood loss was a significant risk factor for BNC. In 20% of BNC patients a migrated foreign body was noted at vesicourethral anastomosis. Primary management of patients with BNC following RARP should be bladder neck incision and self CIC regimen

Multi-agent architecture for waste minimisation in beef supply chain

Food waste is an alarming issue pertaining to the rising global hunger, huge environmental footprint, and high monetary value. In developing and developed nations, it occurs primarily due to inefficiencies upstream and downstream of the supply chain respectively. A common factor in both developed and developing nations is product flow within the supply chain from farms to retailers. This study aims to identify the root causes of waste generated across the product flow of the beef supply chain from farm to retailer. A workshop involving twenty practitioners of the beef industry was conducted and the collected information was transcribed and coded to generate a current reality tree, which assisted in identifying root causes of waste in the entire beef supply chain. A multi-agent architecture framework spanning the entire beef supply chain from farm to retailer is proposed, which is composed of autonomous agents capable of bringing all segments of the beef industry on a single platform and collaboratively assist them in mitigating root causes of waste. The proposed framework will aid the practitioners in the beef industry to reduce waste, improve their operational efficiency thereby raising food security, economic development whilst curbing their carbon footprint