Control Programming Research Articles

Jumping Motion Based on Momentum Optimization Control and Differential Dynamic Programming for a Multilocomotion Robot

AbstractJumping motion is an indispensable motion mode for a multilocomotion robot, which will improve the crossing ability of the robot. This paper proposes a novel jumping control scheme for an MLR to perform jumping motion. The control strategy divides the whole jumping motion into three phases: the launch phase, the flight phase, and the landing phase. In the launch and landing phases, the controller is designed based on the centroid dynamics. By controlling the centroid momentum, the robot can achieve the desired centroid trajectory to obtain the initial take‐off speed in the launch phase and to maintain stability and reduce impact in the landing phase. In the flight phase, Differential Dynamic Programming algorithm is used to adjust the posture of the robot to further improve the jumping height and prepare for a smooth landing. Finally, the effectiveness of the proposed method is evaluated through simulations.

Effect of Coaching in Diabetes Program in Glycemic Control in Steelworkers

Effect of Coaching in Diabetes Program in Glycemic Control in Steelworkers

Optimizing signal timing of the arterial‐branch intersection: A fuzzy control and nonlinear programming approach

AbstractArterial‐branch intersections are important components of urban road network but are greatly ignored of its role in maintaining an efficient traffic operation in regional networks. Arterial‐branch intersections are generally featured with significant fluctuations in the flow ratio of the branch road to the arterial road. So, in order to adapt the signal timing to this kind of intersection, an optimization control algorithm based on fuzzy control and nonlinear programming (FCNP) was proposed. To verify this optimization algorithm, the Python and Vissim joint simulation was employed. Prior to the simulation, traffic flow data were collected in 12 consecutive hours at an arterial‐branch intersection in China. The simulation results show that, after signal timing optimization with FCNP, the average vehicle queue length and delay reduced 25.8% and 17.3%, respectively, when compared with the performance of the traffic‐actuated control, which also outperformed previous equivalent research. Besides, the overall operation of the intersection was verified to be greatly improved and stabilized by using the proposed algorithm. The findings of this study provide a reasonable solution of distributing the right‐of‐way at arterial‐branch intersections and suggest the advantage of combining fuzzy control and nonlinear programming in dealing with the signal timing optimization.

MICROPROCESSOR-BASED AUTOMATED CONTROL SYSTEM FOR WATER TREATMENT PROCESSES

Automated control systems for water treatment processes at agricultural enterprises or agro-industrial complex are made using imported digital microprocessor devices. They, in comparison with electromechanical means, have the versatility and simplicity of operational programming of the logical part required, for example, when changing the algorithms of a technological installation or electric drive. Strict control and restrictions applied by unfriendly exporters to domestic consumers of these products force developers and designers to abandon non-constructive interactions, while achieving the necessary results in solving emerging problems. (Research purpose) The research purpose is creating an automated system for managing the processes of water treatment using microprocessor-based programmable technical means of domestic manufacturers and developing the recommendations on the selection of the type and programming of the controller in the operation of water ozonation. (Materials and methods) The article presents the scheme and the logical part of the automated control of pumping units based on programmable logic controllers of domestic manufacturers. (Results and discussion) The article presents the features of the logical part of the system in the CoDeSys environment using libraries of standard functional blocks. Time intervals were chosen, and the procedure for setting up virtual proportional-integral-differentiating regulators set by programmable logic controllers and determining the properties and indicators of ozone concentration during water disinfection are presented. (Conclusions) The emulation of the proposed options confirmed the stability of the system with the necessary regulation parameters. After checking and configuring the program, the program code is copied into the logical controller. Programming of logic controllers for other operations is performed in a similar way.

Sequential convex programming for non-linear stochastic optimal control

This work introduces a sequential convex programming framework for non-linear, finitedimensional stochastic optimal control, where uncertainties are modeled by a multidimensional Wiener process. We prove that any accumulation point of the sequence of iterates generated by sequential convex programming is a candidate locally-optimal solution for the original problem in the sense of the stochastic Pontryagin Maximum Principle. Moreover, we provide sufficient conditions for the existence of at least one such accumulation point. We then leverage these properties to design a practical numerical method for solving non-linear stochastic optimal control problems based on a deterministic transcription of stochastic sequential convex programming.

Research on Medical Record Quality Management Based on FOCUS-PDCA Program

Objective: To explore the application value of FOCUS-PDCA program in quality control of medical records. Methods: 200 medical records of gynecological inpatients in our hospital were selected and randomly divided into two groups. The observation group was treated with FOCUS-PDCA procedure, while the control group was treated with traditional medical record quality control method, and the quality defects of the two groups were compared. Results: The defect rate of terminal medical records in the observation group (including homepage information missing or error, progress note defect, admission records defect, operation records defect, informed consent defect, and discharge note defect) was significantly lower than that of control group, P < 0.05. Conclusion: FOCUS-PDCA program can significantly improve the medical record quality, which is worthy of promotion in clinic.

Effect of cowpea (Vigna unguiculata L. Walp.) sowing season on population dynamics of pest insects

Several factors limit cowpea quality and yield, such as the choice of a cultivar better adapted to the region, the ideal sowing season, as well as diseases and pests. Aimed to evaluate the effect of different sowing seasons on the population dynamics of pest insects of cowpea crops. The study was carried out during the dry season, the rainy season, and the season recommended for sowing by the Experimental Farm of the Federal University of Amazonas (FAEXP–UFAM), Brazil. A total of 33 weekly collections were carried out during the three sowing seasons, distributed in two ways according to the phenological stage of the crop: manual collection per linear meter of plantation and entomological scanning net. The faunistic analysis detected the pest insects Acromyrmex laticeps nigrosetosus, Cerotoma arcuata, Crinocerus sanctus, Euschistus heros, Horciasinus signoreti, Liriomyza sativae, and Nezara viridula. Of these species, H. signoreti stands out for being recorded for the first time as predominant in cowpea crops in the Brazilian state of Amazonas. Infections by hemipterans such as C. sanctus, E. heros, H. signoreti, and N. viridula were detected throughout the study, regardless of the sowing season, except for H. signoreti, which was dominant in all three seasons. The highest infestation of C. arcuata occurred during the recommended sowing season for cowpeas (June to August). According to the Jaccard index, plantation I e II share 86% of the species. This study provides important information to programs in insect control and management and to the agronomic decision-making process.

Sequential linear integer programming for integer optimal control with total variation regularization

We propose a trust-region method that solves a sequence of linear integer programs to tackle integer optimal control problems regularized with a total variation penalty. The total variation penalty implies that the considered integer control problems admit minimizers. We introduce a local optimality concept for the problem, which arises from the infinite-dimensional perspective. In the case of a one-dimensional domain of the control function, we prove convergence of the iterates produced by our algorithm to points that satisfy first-order stationarity conditions for local optimality. We demonstrate the theoretical findings on a computational example.

Data-Driven Adaptive Dynamic Programming for Optimal Control of Continuous-Time Multicontroller Systems With Unknown Dynamics

This paper investigates the optimal control of continuous-time multi-controller systems with completely unknown dynamics using data-driven adaptive dynamic programming (DD-ADP). In this investigation, all controllers take actions together as a team, and they have precisely the same cost function, which is actually a fully cooperative game. According to optimal control theory, the HJB equation corresponding to the fully cooperative game is derived. To obtain the solution to HJB equation, a model-based policy iteration (PI) algorithm is first presented. On the basis of the PI algorithm, a DD-ADP algorithm without requiring the system dynamics is developed, and the neural networks (NNs) implementation scheme of the developed DD-ADP algorithm is given. Stability and convergence analysis are derived by Lyapunov theory. Finally, numerical simulation examples on linear and nonlinear multi-controller systems demonstrate the effectiveness of the designed scheme.

Efficacy and safety of BI 425809 in patients with schizophrenia: CONNEX, a Phase III randomised controlled trial programme

Efficacy and safety of BI 425809 in patients with schizophrenia: CONNEX, a Phase III randomised controlled trial programme

Laser intensity noise evaluation system for space-based gravitational wave detection

The space-based gravitational wave detection can acquire the gravitational wave source information with larger characteristic mass and scale, forming a complementary detection scheme with ground-based gravitational wave detection, primordial gravitational wave detection, and pulsar gravitational wave detection. The space-based gravitational wave detection is based on a long-distance laser interference device, which mainly detects gravitational wave signals in a frequency range of 0.1 mHz–1 Hz. The noise evaluation and noise suppression of the laser light source system directly affect the detection sensitivity. In this work, based on low-noise photoelectric detection, a very low-frequency laser intensity noise test and evaluation system is constructed with high-precision digital multimeter, software control and algorithm programming of the host computer. The laser intensity noise can be converted into the fluctuation of the current signal by utilizing the photodiode, and the current signal is converted into the voltage signal and amplified by the transimpedance circuit. Thus the high-frequency interference components are filtered out by a passive low-pass filtering, and the extremely low-frequency noise components are retained. According to the definition of shot noise, it can be known that the photocurrent injected into the detector is inversely proportional to the shot noise, so at least 5 mW laser is chosen for photoelectric detection. After controlling the high-precision digital multimeter through LabVIEW software programming, the acquisition is detected. The output voltage signal by the laser is subjected to the fast Fourier transform and logarithmic frequency axis power spectral density estimation algorithm for noise evaluation in the frequency domain, forming a complete laser intensity noise evaluation and measurement system. The 0.1 mHz–1 Hz frequency band laser intensity noise evaluation is finally obtained. The experimental results show that the noise of the high-precision multimeter in a frequency band of 0.1 mHz–1 Hz is lower than 5×10&lt;sup&gt;–5&lt;/sup&gt; V/Hz&lt;sup&gt;1/2&lt;/sup&gt;; the noise of the detector electronics ina frequency band of 0.1 mHz–1 Hz is lower than 4×10&lt;sup&gt;–5&lt;/sup&gt; V/Hz&lt;sup&gt;1/2&lt;/sup&gt;. The electronic noise of the high-precision multimeters and the detectors meet the requirements for space gravitational wave detection. The experimental results show that the 0.1 mHz–1 Hz frequency band laser intensity noise evaluation system we built meets the needs of space-based gravitational wave detection program, and provides an important foundation for building a laser source that meets the needs of space-based gravitational wave detection.

Multi-Stage Real-Time Operation of a Multi-Energy Microgrid With Electrical and Thermal Energy Storage Assets: A Data-Driven MPC-ADP Approach

This paper studies the multi-stage real-time stochastic operation of grid-tied multi-energy microgrids (MEMGs) via the hybrid model predictive control (MPC) and approximate dynamic programming (ADP) approach. In the MEMG, practical power and thermal network constraints, heterogeneous energy storage devices, and distributed generations are involved. Given the relatively large thermal inertia and slow thermal energy fluctuation, only uncertainties of renewable energy sources and active/reactive power loads are considered. Then, historical data are adopted as training scenarios for the MPC-ADP method to acquire empirical knowledge for dealing with all the diverse uncertainties. Further, piecewise linear functions are used to approximate value functions with respect to the operation status of energy storage assets, which enables sequentially solving the Bellman’s equation forward through time to minimize MEMG operation cost. Finally, numerical case studies are conducted to illustrate the effectiveness and superiority of the proposed MPC-ADP approach. Simulation results indicate that with sufficient information embedded, the MPC-ADP approach could obtain good-enough real-time operation solutions with the successively updated forecast. Further, it outperforms alternative real-time operation benchmarks in terms of optimality and convergence for various application scenarios.

Tracking Control for a Quadrotor via Dynamic Surface Control and Adaptive Dynamic Programming

Tracking Control for a Quadrotor via Dynamic Surface Control and Adaptive Dynamic Programming

ОПТИМАЛЬНЕ ТРАСУВАННЯ ТРАЄКТОРІЙ ГЛИБОКИХ СВЕРДЛОВИН МЕТОДАМИ НЕЛІНІЙНОГО ПРОГРАМУВАННЯ

The issues of rational (optimal) trajectory trajectory of oil and gas wells are apparently one of the few areas of the oil and gas industry that still does not use optimal control and nonlinear programming methods. 133 At the same time, the use of these methods makes it possible to design smoother and shorter trajectories with less risk of emergency situations occurring in them, leading to resonant vibrations of the system, buckling of the drill string and its sticking. In addition, in such columns, the conditions for the hydrodynamic and aerodynamic flow of the working fluid are improved, and the likelihood of the formation of blood clots and plugs is reduced. In this paper, a new approach for the optimal design of curved well trajectories based on the application of the anti-gradient descent method is proposed, resolving equations are formulated, algorithms for their solution are developed, a practical example is considered, and it is shown that solving this problem leads to a decrease in the total curvature of the well and its length. KEYWORDS: DEEP BOREHOLE, BOREHOLE TRAJECTORY OPTIMIZATION, ANTIGRADIENT RUNING METHOD, OBJECTIVE FUNCTIONS, NONLINEAR PROGRAMMING.

A Low Cost Intelligent Fuzzy-Controlled Multipass-Multibaffle Dry-Air Sterilizer Device for Small-Sized Surgical Instruments

A major constraint in hospitals and clinics in the interior villages of low resource countries is the access to stable power supply. Decontamination of reusable metal-based surgical tools is an energy-intensive process, the power required for this procedure may not be accessible in many health centres in low resource countries. Hence, decontamination device with low-energy requirements could immensely benefit village clinical settings. The developed sterilizer utilizes a Fresnel lens in a multi-baffle multi-pass chamber to amplify radiation intensity. An intelligent scheme of air passage was achieved using Fuzzy logic control to ensure control of pressure and temperature regime thermal transport within the chamber. The Fuzzy logic controller program was designed on Matlab's fuzzy logic toolbox and simulated with Simulink to evaluate its accuracy. The performance evaluation of the device showed that at an ambient temperature of 27℃ and a solar radiation intensity of 1362 W/m2, the sterilizer was able to sterilize at a temperature of 169.69℃ which is within the range for efficient dry heat sterilization to take place (140℃-170℃). This work has demonstrated that fuzzy logic controlled dry air sterilizer could achieve temperature ~ 150℃ within the heater chamber which may be suitable for sterilizing used surgical equipment.

Adaptive dynamic programming for optimal control of discrete‐time nonlinear system with state constraints based on control barrier function

AbstractAdaptive dynamic programming (ADP) methods have demonstrated their efficiency. However, many of the applications for which ADP offers great potential, are also safety‐critical and need to meet safety specifications in the presence of physical constraints. In this article, an optimal controller for solving discrete‐time nonlinear systems with state constraints is proposed. By introducing the control barrier function into the utility function, the problem with state constraints is transformed into an unconstrained optimal control problem, addressing state constraints which are difficult to handle by traditional ADP methods. The constructed sequence of value function is shown to be monotonically non‐increasing and converges to the optimal value. Besides, this article gives the stability proof of the developed algorithm, as well as the conditions for satisfying the state constraints. To implement and approximate the control barrier function based adaptive dynamic programming algorithm, an actor‐critic network structure is built. During the training process, two neural networks are used for approximation separately. The performance of the proposed method is validated by testing it on a simulation example.

Communication Topology Assignment and Control Co-design for Vehicle Platoons in LTE-V2V Network

In this study, we investigate the problem of inter-vehicle communication topology (IVCT) assignment and control for vehicular platoons in LTE-V2V networks based on the cooperative awareness message dissemination mechanism. A sampled-data feedback controller is proposed for platoons to eliminate the effect of stochastic packet dropouts and external disturbance, where the controller gain depends on the IVCT. To guarantee the stability requirement of a platoon with the minimized cost function, a unified control framework is established to jointly determine the optimal IVCT from all the available ones and the associated feedback controller gain. This co-design procedure is based on the optimal control and dynamic programming technique, where both fixed and periodic switching IVCTs are available. A useful algorithm is proposed to implement the established co-design framework. Furthermore, we present numerical examples to demonstrate the effectiveness of the proposed method.

Strategies to aid self-isolation and quarantine for individuals with severe and persistent mental illness during the COVID-19 pandemic: A systematic review.

BackgroundIndividuals with severe and persistent mental illness (SPMI) have a higher risk of contracting COVID‐19 than individuals without SPMI. In combination with physical distancing, hygiene protocols, and vaccines, quarantine and self‐isolation are primary means of viral containment. However, individuals with SPMI may experience more difficulties with mandated quarantine or self‐isolation because of their illness(es), stigma, and marginalization. To date, there is a lack of consensus on strategies that could aid such individuals in completing isolation.AimThis review aimed to synthesize evidence for interventions to support self‐isolation and mandated quarantine for COVID‐19 among individuals with SPMIs.MethodsWe followed the PRISMA guidelines, searching 19 electronic databases (9 published literature registries and 10 gray literature sources). We looked for relevant randomized controlled trials, quasi‐experimental studies, and program evaluations of the effectiveness of relevant psychosocial, pharmacological, harm reduction, and addiction management strategies to support isolation settings or quarantine requirements for individuals with any SPMI (e.g., any mental disorder, substance use disorder, or their combination).FindingsOf 10,298 total records that were located, 5582 were duplicate citations. Upon screening the remaining 4716 unique records by title and abstract, we excluded a further 3562 records. Only one original article met our inclusion criteria after reviewing the full texts of the remaining 1154 citations. To support individuals experiencing homelessness during the COVID‐19 pandemic, San Francisco developed an isolation hotel that reduced COVID‐19 hospital strain for 1009 participants (25% had a mental health disorder and 26% had a substance use disorder). While 81% completed their hotel stay, 48 patients had behavioral health needs that exceeded the hotel's capabilities. No other studies met our review's eligibility criteria. Most articles located by the search simply proposed solutions or discussed the challenges brought by COVID‐19 for people with SPMIs. While some documents went a step further (e.g., shelter guidance documents to support individuals experiencing homelessness), these rarely addressed individuals with SPMIs directly.ConclusionsThis systematic review evaluated evidence from published and gray literature on interventions to support self‐isolation and mandated COVID‐19 quarantine for individuals with SPMIs. Only one study met our inclusion criteria. This study found a beneficial effect of a dedicated isolation hotel for individuals experiencing homelessness and COVID‐19—where approximately 25%–50% of the study sample had a mental or substance use disorder. While there has been an abundance of COVID‐19 protocols in general, information for SPMIs is lacking. As the pandemic continues and we better prepare for future pandemics, developing protocols for supporting SPMIs in this context is imperative.

Adaptive polyhedral meshing for approximate dynamic programming in control

This work proposes a new criterion for adaptive meshing in polyhedral partitions which interpolate a value function in Approximate Dynamic Programming (ADP) in optimal control problems. The criterion adds new points to a simplicial mesh, based on: a user-defined initial condition probability density function which determines ‘influential’ regions of the state space, uncertainty (variance) propagation, and temporal-difference error. A collection of lemmas justifies the algorithmic proposal. Comparative analysis with other options in literature highlights the advantages of our proposal. The developed methods are applied to simulation examples and an experimental robotic setup.

Development of mock-up Ion cyclotron resonance heating system with a new algorithmic approach for automatic impedance matching

This paper presents the development of a mock-up Ion Cyclotron Resonance Heating (ICRH) system along with a new algorithmic approach for fast automatic impedance matching. The mock-up is developed for low power (few watts) and frequency (182.5 MHz) i.e. five times the ICRH frequency of SST-1. The size of the mock-up is considerably reduced to be fit on the test bench using it. The main objective of the work is to develop different matching approaches in order to get the optimum speed of matching. Reducing the size of the mock-up allows frequent implementation and testing of new algorithms which is generally difficult to implement in the real system of tokamak because of its size and complexity. The system consists of indigenously developed components such as 3 dB hybrid coupler, 20 dB directional coupler, tapped transmission line, rigid coaxial stub tuners, line stretcher, service stub, RF antenna, movable water tank based load. The developed system is capable of automatically match any arbitrary load in the range, (35–260)Ω, resistive + (-j25 to +j220)Ω, reactive or VSWR in the range 1.5–4.0 within 200 ms. The matching system also consists of power detectors which automatically sense the forward and reflected power using coupler and the feedback controlled moving coaxial stubs, line stretchers respond as per developed algorithms. The matching algorithm incorporates the various matching steps based on VSWR which have been interpreted for the controller program to control the devices used in the matching network. The developed system is tested using an RF antenna facing the movable saltwater tank that emulates the plasma-like loading behavior. The developed setup is also useful for various high power RF applications like RF heating, sputtering, plasma generation, RADAR, etc. in the RF frequency range.