An intelligent control design for non-linear MIMO processes

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.

An Intelligent Control Strategy for the Intervals of Temperature in a Plate Heat Exchanger

Intelligent control, inspired by biological and AI (artificial intelligence) principles, has increased the understanding of controlling complex processes without precise mathematical model of the controlled process. Through customized applications, intelligent control has demonstrated that it is a step in the right direction. However, intelligent control has yet to provide a complete solution to the problem of integrated manufacturing systems via intelligent reconfiguration of the robotics systems. The aim of this paper is to present an intelligent control architecture and design methodology based on biological principles that govern self-organization of autonomous agents. Two key structural elements of the proposed control architecture have been tested individually on key pilot applications and shown promising results. The proposed intelligent control design is inspired by observed individual and collective biological behavior in colonies of living organisms that are capable of self-organization into groups of specialized individuals capable of collectively achieving a set of prescribed or emerging objectives. The nervous and brain system in the proposed control architecture is based on reinforcement learning principles and conditioning and modeled using adaptive neurocontrollers. Mathematical control theory (e.g. optimal control, adaptive control, and neurocontrol) is used to coordinate the interactions of multiple robotics agents.

Cost mitigation strategy for microgrid using an advanced energy management system with an intelligent controller

Proposed work is aimed at designing an intelligent fuzzy controller with guaranteed stability. We employ Lyapunov theory on the linguistic fuzzy rules to constrain action set for the fuzzy controller. Lyapunov theory constrained control action results in an intelligent controller that exhibits stability even under disturbances. Proposed controller is suitable for continuous state action spaces as it employs fuzzy systems for generalization in a reinforcement learning (RL) framework. We employ proposed controller on the benchmark task of balancing of an Inverted Pendulum under disturbances. Simulation results elucidate practicality and reliability of the proposed control scheme.

The Boeing Company is conducting a series of programs with NASA, DARPA, and the USAF that apply intelligent control technology to flight control systems. These control systems are designed to adapt to off-nominal damage or failure conditions. Reconfigurable control, artificial neural network models, self-learning neural networks, and matrix inverse control methods are some of the technologies used in these flight research projects. This paper addresses the need for intelligent control and the general requirements for the design of intelligent systems. A description is given of the major intelligent controls programs being conducted by Boeing.

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.

Recent years have seen exciting new research and developments in Robotics, Automation and Intelligent Control. Computer and control technology, intelligent control, robotics and automation are changing many aspects of our productive lives. Thanks to computers and control algorithms brought by intelligent control and artificial intelligence, machines are becoming smarter. ICRAIC 2022 focused on the development and integration of robotics, digitalization, automation and artificial intelligence technologies. Therefore, the 2nd International Conference on Robotics, Automation and Intelligent Control (ICRAIC 2022) took place on December 9th-11th, 2022 in Changsha.ICRAIC 2022 has brought together leading academic scientists, researchers and research scholars to exchange their experience and research results in the field of intelligent robotics and systems and share their discoveries, insight and lessons learned, and take home exciting new ideas to perform further state of the art research to make mind-blowing collaborations and innovations.ICRAIC 2022 accepted 50 full papers which was divided into 3 tracks, including Robotics, Automation and Intelligent Control. And all submissions were peer-reviewed through a single-blind review process by an international panel of expert referees, and decisions were taken based on the criteria.Thanks to the ICRAIC 2022 Committee for their efforts in preparing the conference and ensuring its smooth running.:List of General Chairs, Program Chairs, Technical Chairs, Technical Program Committee, Organizers, Co-Organizer, Editors are available in this pdf

Considering different types of time-varying lag system, control strategy is determined by recognition of transient characteristics of responses and cooperation with expert system, forming the basic idea of intelligent controller design. Based on the dynamic response mode of the controlled object, multi-control mode was applied in control law, which can solve the oscillation problems appeared in common control system during pure lag link and improve the robustness of the control system. The application of intelligent temperature controller based on the pattern recognition in the same category of controlled objects requires no specific parameters and mathematical model of the controlled objects, but can bring a stable increase of manipulated variable, quick response, small overshoot, and no steady-state error, enabling it appropriate for different types of controlled objects and achieving perfect control effect.

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.

The paper concerns with the intelligent control of an over-actuated robotic arm. First, it will be presented the original mechanical design of the redundant, cable-driven robot arm with 7 degrees of freedom, whose prototype is being built. Then, it will be synthesized, at the high-control level, an intelligent fuzzy controller that manages activation of the redundant number of robot arm actuators. Structure of the fuzzy controller is given in the paper. Then, the intelligent controller will be applied in the frame of a mathematical model of the considered robotic arm. Performance verification of the synthesized intelligent controller of robotic arm will be accomplished by means of several simulation experiments. Corresponding results are presented and analyzed at the end of the paper. Future directions of research and development in this field will be emphasized as well as the expected results and applications to be planned.

The vehicle backward auto-parking process can be divided into three steps. First, the relative position between the Ego car and an available parking space should be detected using additional sensors, and the two-dimensional (2D) environmental map can be constructed. Then, the optimal parking trajectory is planned online based on this 2D environmental map. Finally, the auto-parking controller executes the real-time vehicle motion path estimation and the planned parking trajectory-tracking control. Here, multiple ultrasonic sensors were installed on a model vehicle to construct the 2D map of the area surrounding the vehicle. A sinusoidal function parking trajectory is planned and the corresponding state variable trajectories of the X and Y components and front-wheel steering angle are derived. A model-free intelligent self-organizing fuzzy controller is proposed to track the parking path by regulating the deviation of a selected state variable. The output command is the real-time front-wheel steering angle. This intelligent controller has a system-learning mechanism without expertise knowledge or a trial-and-error process. It is implemented on a one-sixth model vehicle for experimental study. The experimental results are compared with those of a non-linear feedback linearization controller.

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.

Turning up the heat on obsolete thermostats: A simulation-based comparison of intelligent control approaches for residential heating systems

In order to meet the needs of capital city construction and development, this paper studies the problems of building energy conservation from the aspects of computer intelligent control, green energy-saving building and integrated system of new energy utilization. Using computer intelligence to establish a comprehensive utilization of renewable energy demonstration system, namely the heat pump technology, building CCHP and total heat exchange ventilation system, set up a computer intelligent monitoring system, monitoring and control of building energy consumption, indoor heat and humidity environment, air quality and energy system, optimize the system operation[1].