Intelligent flight control: what are the flight programs and why develop this technology?

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

To intelligently control and adjust LED lighting network system, to make use of the sensor technology, wireless communication protocol, intelligent control technology, it overcomes the difference of the various technical standard, the lack of communication that is problem to impede the promotion of the intelligent lighting. Extending the conventional control method with intelligent technology, planning scheme according to the functions, the design carried out the three respectively subsystems, then the debugging and fusion of the software and hardware. By using the method of software, the high or low level of I/O output can simulate PWM control signal whose duty cycle of the PWM can be adjusted. The brightness data collected from the environment is changed into PWM control information. Using acoustic sensors and temperature sensors and voltage sensors to further adjust the distribution curves of the light and color, these collected data are turned into PWM fine tuning signal. The wireless intelligent lighting control system designed can well solve problems such as the large regional span, the high cost of the network transmission and the uncertain of the node number.

The existing urban traffic signal control system exhibits certain inefficiencies, including prolonged waiting times and frequent traffic congestion. Research indicates that the integration of neural networks can enhance the effectiveness of intelligent traffic control systems, potentially improving overall traffic flow and reducing delays. Neural network is a highly parallel, nonlinear and highly redundant system. Meanwhile, the self-learning and self-organizing capabilities of neural network have unique advantages for those systems that cannot establish accurate mathematical models. According to the characteristics of complex, variable and random traffic conditions at urban intersections, this paper analyzes the traffic signal control by using neural network control method. This paper introduces a design method of intelligent traffic light based on dynamic time adjustment of traffic flow. By detecting the traffic flow on site, and then allocating the green time of each lane according to the neural network algorithm, the traffic flow dynamic adjustment can be realized, and the traffic capacity of the intersection can be effectively improved. This kind of intelligent control traffic lights can effectively control traffic, and has obvious effects on dreading traffic flow, improving road capacity and reducing traffic accidents.

Bare-bones languages serve small systems with ease: Cushmann, R HEDN Vol 25 No 16 (5 September 1980) pp 171–177

As we all know, big data and intelligent computing have been widely used in information science, life science, computer science and intelligent control, intelligent robots, vehicle networking, space technology, marine development and other fields, especially in the future life science and medical field. This paper is based on a new digital optimal decision-making idea of intelligent signal processing and control. On the basis of extending non-digital signal processing and information prediction to signal processing and information prediction in the digital generalized information measurement space, and making full use of optimization algorithms such as digital filtering and frequency spectrum analysis, this article discusses in depth the intelligent optimal control of a class of non-stationary random processes in artificial intelligence, biomedicine, radio communication, automatic control and other scientific and technological fields. It provides a new theory, a new approach and an effective and reliable new method for the mathematical modeling and optimal control of such processes, and has broad application prospects and value.

Most of the currently existing microclimate control systems operate on the basis of traditional P, PI, PID controllers. But the work of such systems is effective only in a narrow operating range. With significant fluctuations in environment, it is required to reconfigure the parameters of these regulators each time. In such cases, maintaining comfortable conditions in the room is recommended by using intelligent control technologies, so-called fuzzy control systems, operating in terms of fuzzy logic. The aim of the paper is to research the possibility of implementation of intelligent control systems to maintain the comfortable microclimate in the premises and checking the adequacy of the system through simulation. The climate control system is based on fuzzy inference and provides forming the base of fuzzy production rules, fuzzification of input values, aggregation of truth of sub conditions of each rule, activation of conclusions and defuzzification process that generates an output signal to control the smart home functional devices. Procedures of the fuzzy inference and simulation are implemented in the Matlab programming environment using the Fuzzy Logic Toolbox and Simulink packages. The results of the paper showed that the developed intelligent microclimate control system for premises based on fuzzy logic provides a flexible self-tuning of the engineering equipment and maintaining the microclimate parameters at the required level.

Ensemble of long short-term memory prediction and variable universe fuzzy control for seismic response reduction using electromagnetic dynamic vibration absorber

A description of a new class of organizational and technical systems is given – intelligent road-building compaction control systems, the principles of operation of which provide for ensuring a given quality of compaction of asphalt mixtures in the process of road construction. The development of systems of that class is due, in the first place, to the transition to digital and intelligent control systems in construction. A scientific problem related to the relevance of creating methods for intelligent control of compaction of asphalt mixtures that affect the quality of road surfaces was formulated. To succeed, the usage of neural network structures was proposed. The usage will allow real-time monitoring of changes in the compaction quality index and efficient controlling of road machines using both the driver's manual means and the automatic compaction control system. The properties of the system under study – which determine the principles of its functioning: intelligence, informativity, speed, interconnectedness of subsystems, controllability and modularity – were presented. The above principles of the functioning of the proposed system, which are part of the methodology for managing the quality of asphalt compaction of pavement roads, were implemented in a set of methods and algorithms. Among them should be noted a new method of intelligent continuous control of compaction in the process of laying asphalt mixtures, an advanced method of intelligent prediction of compaction quality by vibrating rollers.

High-speed UAV flight control is challenged by unknown external aerodynamic disturbances and internal system variations due to complex aerodynamic configuration, propellant consumption, the center of gravity movement, and possible actuator failures. Redundant aerodynamic control effectors and engine inlet control mechanisms are exploited/blended to maintain adequate force/moment control to satisfy flight control reliability requirements. A control allocation (CA) mixing matrix is an essential element of the redundancy design in addressing fault tolerance capabilities. This paper employs an Intelligent Flight Controller (IFC) implemented in an adaptive control augmentation fashion to assist the UAV’s primary Nonlinear Dynamic Inversion (NDI) controller in restoring aircraft stability and command following objective when subjected to effector performance degradation, including failures. Through a blended design between optimal control modification (OCM) and derivative-free model reference adaptive control (DF-MRAC), the IFC offers performance consistency in comparison to traditional MRAC. The proposed IFC framework has demonstrated its effectiveness in assisting the baseline NDI flight control system to maintain its mission subjected to actuator’s failures (via an implicit automatic CA ‘re-distributing’ action). Furthermore, the IFC also works well with any existing onboard CA algorithm in dealing with effector failures without requiring restructuring of the CA blending matrix. It therefore deserves consideration for application to future high Mach UAVs.

This paper investigates intelligent PID flight control approaches for a small Unmanned Aerial Vehicle (UAV) pitch attitude. These methods are based on the longitudinal motion models of the small UAV. These intelligent PID controllers, including integral separated PID controller and adaptive proportion PID controller are designed and simulated for UAV’s pitch attitude control. In order to illuminate the performance of intelligent controller, the classic PID controller is designed and simulated being set to the opposite place. Our results demonstrate that the control result of the adaptive proportion PID controller is highly accepted in both dynamic and stability performance, for the controller’s ability to set a larger proportion control parameter of PID and adjust the parameter according to control process. The work described in this paper provides proposals for the design of Flight Control System of the small UAV.

The paper presents Intelligent Control (IC) Interfaces for real time control of mechatronic systems applied to Hardening Process Control (HPC) in order to improvement of the material’s mechanical characteristics. Implementation of IC laws in the intelligent real time control interfaces depends on the particular circumstances of the models characteristics used and the exact definition of optimization problem. The results led to the development of the IC interfaces in real time through Particle Swarm Optimization (PSO) and neural networks (NN) using off­line the regression methods.

Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency

Reliability and vehicle survivability are key factors in achieving mission success for UAV aircraft. Maximizing these qualities is a challenging goal for tactical UAV’s exposed to target defenses as well as adverse environmental conditions and to structural or control system failures during extended length missions. Under damage conditions, using any operable control effectors becomes a critical need. These effectors could include conventional control surfaces, propulsion changes for multi-engine vehicles, and mass (fuel) transfer in lateral or longitudinal axes. Also needed may be recovery situations from extreme loss of control and upset conditions requiring correction flight control commands during flight with large angle of attack and sideslip. A major control effector for these conditions is the propulsion system of the vehicle. This control method requires two or more engines on the UAV. Engine thrust changes can change the flight path and attitude of the vehicle, and can be used as either an augmentor or for primary control of the vehicle. This use of propulsion changes to stabilize and control flight path of UAV’s is possible if sufficiently fast response time can be obtained from the engines. Flight test research conducted by NASA and Boeing on both high performance tactical aircraft and transport aircraft have demonstrated excellent potential for use of Propulsion Flight Control as part of the primary control system for UAV aircraft. Control techniques, remote pilot command methods and control station displays from these flight development programs can be applied to UAV aircraft. An important consideration for UAV aircraft is flight path control during operation outside of the normal maneuver boundaries of the vehicle, possibly caused by gust upsets, severe maneuvers for threat avoidance, structural failure, or other unanticipated causes. Propulsion control offers better response at extreme angle of attack, often better than using conventional control surfaces. Another UAV design issue is control of a tailless aircraft configuration, where the usual approach is use of split ailerons or flaps to give directional forces to the vehicle. The problem with this approach is the drag generated by these split surfaces can reduce range and speed. An alternate approach for tailless UAV’s with two or more engines is to use commanded differential thrust from the left and right engines to act as the control effector for yaw stability and for crosswind landings. Propulsion control can be a significant factor in UAV normal and adverse operating conditions. Engine controller modes integrated with flight control offer the means to achieve required flight path control during varied operating conditions of the UAV.

The characteristics and applications of the system for welding machines based on SCM , based on PLC control system and PC-based industrial control system was introduced. It has certain significance to the design of welding machine control system.

At present, the intelligent control technology of highway tunnel lighting mainly includes two types, graded dimming and stepless dimming, both of which have certain energy-saving effects. Tunnel lighting energy saving and consumption reduction, traffic safety, and the security degree are important indicators used to measure the efficient operation of a tunnel. By adding variable correlated color temperature (CCT) control based on stepless dimming, the adjustment of a lamp’s CCT according to changes in the external tunnel environment can be achieved. This not only serves the dual purpose of secondary energy saving and providing comfortable lighting, but also plays a significant role in reducing the reaction time and ensuring tunnel traffic safety. This paper mainly discusses the research achievements and applications of the main intelligent control technologies for highway tunnel lighting. Combining on-site investigations, operating and energy-saving effects achieved are evaluated, and the future development direction of intelligent control technology for highway tunnel lighting is summarized. Furthermore, this paper proposes an optimization model of a stepless dimming control system and intelligent control technology in the tunnel’s variable CCT based on stepless dimming. The results of this review can provide useful technical support for the design, operation and management of intelligent lighting control in highway tunnels.