Multi-joint robotic arms have the characteristics of unknown disturbances and dynamic uncertainties. A nonsingular terminal SMC strategy with a Finite time Extended State Observer (FESO) was designed to address its tracking control problem. Uncertainty, nonlinearity, coupling, external disturbances, etc. are considered as total disturbances. The FESO provides observation results within a finite time. It is particularly suitable for handling the total disturbance of robotic arms. The disturbance is compensated, which enhances the system’s anti-interference ability. A composite controller is designed using a nonsingular terminal sliding surface to suppress observation errors and ensure system stability. The finite time extended state observer can estimate and compensate for the total disturbance, which can alleviate system chattering and further improve system performance. Compared with RBF adaptive control, the SMC method based on finite time extended state observer can effectively suppress parameter uncertainty and external disturbances. It can quickly track expected values and has good steady-state characteristics.

The wheeled mobile robot is a typical uncertain robot system, which has typical nonholonomic characteristics and underdrive characteristics with different input and output dimensions.In the unknown environment, the slip and sideslip of the wheeled mobile robot are inevitable.Therefore, the research on trajectory tracking control of the wheeled mobile robot under sliding is of great significance.Aiming at the tracking problem of the wheeled mobile robot system with side slip disturbance, a Lyapunov design method based on extended state observer is proposed by using active disturbance rejection strategy.The influence of the sideslip disturbance on the system is regarded as the total disturbance of the system, and the extended state observer is used to observe the total disturbance in real time.The observation of the total disturbance by the extended state observer plays a patch role in the control law.When there is no disturbance, the system returns to the Lyapunov control under the nominal model.When there is a disturbance, the disturbance is compensated by the extended state observer, so that the system is approximately equivalent to the nominal model without being affected by the disturbance.The simulation results show that the system has better transient performance and anti-interference performance compared with the inverse control regardless of whether it is disturbed or not.

According to the error tracking model of automated-guided vehicle (AGV), considering the uncertain disturbances such as sideslip, ground roughness and friction, this paper designs sliding mode control extended state observer (SMC-ESO) control scheme. ESO describes all the uncertain dynamics in the system as additive total disturbances of the system and estimates the disturbances online and in real time. The SMC is designed to compensate and suppress these disturbances, thus reducing the uncertainty of the feasibility of AGV tracking and the influence of external random interference on the control performance in the tracking process and improving the rapidity and robustness of AGV tracking control. To verify the algorithm, SMC-ESO and active disturbance rejection control (ADRC) are compared by simulation, and the results show that SMC-ESO has better tracking ability, anti-interference ability and robustness.

Selective catalytic reduction (SCR) denitrification system has complex reaction process, which is characterized by large inertia, large delay, strong disturbance and uncertainty. In order to improve the robustness of traditional linear active disturbance rejection controller (LADRC), an improved active disturbance rejection controller (ILADRC) is designed by adding an identical linear extended state observer(LESO) and introducing the estimated error value of total disturbance. In order to better solve the problem of large delay in SCR denitrification system, Smith predictor is used to offset the delay of output variables before entering LESO. Smith-ILADRC control of SCR denitrification system is designed. The tracking performance, anti-jamming performance and robustness of Smith-ILADRC are simulated under the action of external disturbance and the change of model parameters. The results show that the tracking performance and anti-jamming ability of Smith-ILADRC are obviously improved.

A predictive control strategy based on the fuzzy neural network (FNN) for baking furnace is proposed. This method combines T-S fuzzy model with the RBF neural network to form a FNN. The temperature control system of anode baking furnace is taken as the object of simulation and predictive modeling. The T-S fuzzy RBF neural network (T-SFRBFNN) is used to model the off-line predictive control of the controlled system to provide online learning opportunities for the parameters of T-SFRBFNN. The self-compensating feedback correction method is used to adjust the output of the predictive model directly online to achieve the purpose of real-time control. The predictive control algorithm based on the FNN can establish an accurate multi-step predictive control model in the off-line state when the information of the controlled process is not fully understood and the precision of the model of the controlled object is not high. In online state, the predictive control algorithm can be calibrated by on-line feedback with self-compensation function. Meanwhile, the gradient descent method is used to adaptively adjust the parameters in the FNN model of the controller to realize the intelligent control of the controlled process. Simulation results show that the control method is simple, real-time and effective. It has good robustness and adaptability. It provides a theoretical basis for the producing high-quality carbon anode.

The coordinated control object of supercritical units is characterized by multivariable coupling, strong nonlinearity and uncertainty. For multivariable system Active Disturbance Rejection Control (ADRC), the coupling between channels can be regarded as disturbance, which can be estimated by Extended State Observer (ESO) of each channel. For strongly coupled system, the coupling may not be eliminated in time. The coupling between loops is regarded as internal disturbance, and the internal and external disturbances of the system are observed and compensated as a total disturbance by the Improved ADRC(IADRC). An IADRC method based on similar feedforward decoupling is proposed. Simulation results show that the decoupling performance, tracking performance and robustness of the feedforward-like decoupling IADRC control method are better than those of ADRC control scheme.

The reaction process of selective catalytic reduction (SCR) denitrification system is complex, which has the characteristics of large inertia, large delay, strong interference and uncertainty. Traditional PID control can’t achieve accurate control of ammonia injection. Based on linear active disturbance rejection control (LADRC), Smith predictor is used to eliminate the delay output variables before entering extended state observer. The nonlinear state error feedback control law of ADRC structure is designed by using sliding mode control law, which improves the fast response and stability of the system. To solve the problem that the selective catalytic reduction denitrification system is difficult to achieve accurate modeling and large delay, Smith-SMC linear extended state observer (Smith-SMC-LESO) is designed. The simulation results of tracking characteristics, anti-jamming characteristics and robustness show that the set-point tracking performance and anti-jamming ability of Smith-LADRC and Smith-SMC-LESO are significantly improved.

Distillation tower process is a typical multivariable system, which has the characteristics of time-varying, coupling and time-delay. For multivariable systems, decentralized Active Disturbance Rejection Control (ADRC) can regard the coupling between channels as disturbance. Estimating disturbances through Extended State Observer (ESO) of respective channels may not eliminate coupling in time for strongly coupled systems. Based on ADRC's excellent tracking and anti-interference ability, the model's known information is fully utilized, and the multivariable extended state observer is adopted. The inverse decoupling design and ADRC are integrated into a complete multivariable control scheme to achieve better decoupling control. The simulation results show that the multivariable inverse decoupling ADRC control scheme can effectively estimate and compensate the uncertainties such as coupling and interference existing in the system. Its tracking capability and anti-jamming capability are superior to the conventional decentralized ADRC control scheme.

The distillation column process is a typical multivariable system, which is characterized by time variability, coupling and time delay. For multivariable systems, decentralized Active Disturbance Rejection Control (ADRC) can regard the coupling between channels as disturbance, which can be estimated by Extended State Observer (ESO) of each channel. For strongly coupled systems, the coupling may not be eliminated in time. Based on ADRC's excellent tracking anti-disturbance ability, an Improved Inverse Decoupling ADRC Internal Model Control (IIDADRCIMC) method is proposed by using multivariable extended state observer and making full use of the known information of the model. Decoupling of distillation column system is realized by inverse decoupling method, and improved internal model control and Linear ADRC (LADRC) are adopted for the decoupled subsystem. By introducing internal model compensator and gain to compensate time delay, the dependence of the system on the model is reduced. By adjusting the parameters of LADRC, internal model compensator and gain, the adverse effects of model mismatch, external interference and uncertainties on the system are suppressed. Simulation results show that the decoupling performance, tracking performance and robustness of the IIDADRCIMC are better than those of the conventional decentralized ADRC control scheme.

Aiming at the problems of complex equipment unbinding, poor universality and poor user experience in traditional smart home system, this paper designs a real-time control system of smart home based on MQTT. The system consists of client, WIFI module and cloud server. ESP8266 wireless WIFI module is used to push messages through MQTT protocol. One-click unbinding function is added to realize convenient management, real-time control and uploading of status information. The system has the characteristics of low cost, high speed, stable communication and simple operation. At the same time, it is convenient to expand the system. It can meet the needs of smart home control.

In this paper, an efficient controller design method is proposed based on active disturbance rejection control (ADRC) scheme for stabilization problem of wheeled mobile robots with parametric uncertainties, which can make the system converge quickly. By using the extended state observer (ESO), both the system states and the unknown parametric uncertainties could be estimated. In addition, the input-state scaling technique is used to transform the system into two decoupled subsystems. Based on the decoupled subsystems, a switching controller and ADRC are designed. Simulation results show that the proposed scheme can stabilize the wheeled mobile robot system asymptotically despite the presence of parametric uncertainties.

Time-varying disturbance of drum water level is difficult to estimate and compensate, which leads to time-varying periodic error of the whole system. System model is reconstructed by using prior information of equivalent disturbance, and the components of known modes in equivalent disturbance are estimated and compensated by the generalized extended state observer. Thus, the error can be eliminated and the control accuracy of the system can be improved. Compared with the traditional active disturbance rejection control (ADRC) system based on linear extended state observer, the control performance under different types of external disturbances is studied. Simulation results show that the proposed generalized extended state observer can completely estimate and compensate the components of the known modes in the equivalent disturbance with small overshoot, short adjustment time, strong anti-interference ability and high control precision.

Drum water level systems show strong disturbance, big inertia, large time delay, and non-linearity characteristics. In order to improve the antidisturbance performance and robustness of the traditional active disturbance rejection controller (ADRC), an improved linear active disturbance rejection controller (ILADRC) for drum water level is designed. On the basis of the linear active disturbance rejection controller (LADRC) structure, an identical linear extended state observer (ESO) is added with the same parameters as that of the original one. The estimation error value of the total disturbance is introduced, and the estimation error of the total disturbance is compensated, which can improve the control system's ability to suppress unknown disturbances, so as to improve the antidisturbance performance and robustness. The antijamming performance and robustness of LADRC and ILADRC for drum water level are simulated and analyzed under the influence of external disturbance and model parameter variation. Results show that the proposed control system ILADRC has shorter settling time, smaller overshot, and strong anti-interference ability and robustness. It has better performance than the LADRC and has certain application value in engineering.

The characteristics of the drum water level system are strong disturbance, nonlinear, strong coupling and multivariable.The sliding mode control (SMC) technique has the advantages of quick response and strong robustness.The linear extended state observer (LESO) takes the total disturbance of the system as the extended state of the system for modeling and reconstruction, so that the state observer has the ability to estimate the equivalent disturbance of the system.Combined with the advantages of two methods, the sliding mode control based on the extended observer (SMC-LESO) is applied to the control of drum water level.In the case of external disturbance and model parameter mismatch, the dynamic performance of the system is compared with that of the linear active disturbance rejection control (LADRC) system.Simulation results show that the SMC-LESO has the advantages of small overshoot, short settling time, strong anti-interference ability and good robustness.It has good engineering application value and the prospect.

In order to solve the problems of nonlinearity and large time delay in complex system, this paper combined T-S RBF fuzzy neural network control with predictive control, and proposed a fuzzy neural network prediction model model which integrates the fuzzy logic ability of fuzzy control, the powerful learning ability of neural network and the nonlinear expression ability. The method of feedback correction with self-compensation ability was applied to the online correction of the prediction model model. And the controller of T-S RBF fuzzy neural network was designed. The simulation result shows that the self-adaptive predictive controller of fuzzy neural network can build accurate prediction model model for the controlled objects, control the difference of network output and sample output in a small range, and enable actual output to properly follow model output, and it can be applied to any complex nonlinear system. Meanwhile, this model has good anti-noise performance, robustness, tracking ability and self-adaptability.

The network control system is a closed-loop feedback control system composed of controller, sensor and actuator that are connected together through the computer communication network. Aiming at the problem that colleges and universities demand more and more practices but lack relevant experimental facilities and fields, this paper puts forward a solution of building network control laboratory based on EPA. By using the generalized network control system, it can not only control and detect the control system itself, but also realize remote monitoring and management of the experimental process on the basis of the public computer network data transmission of network control system. Through TCP/IP communication mode and the web publishing of the Force Control, it realized the direct operation of the network control laboratory development. After testing, it can realize the operation of the network control laboratory, adjust the corresponding parameters, observe the results and verify the algorithm. The system has practical value and referential value.

In order to improve the teaching quality of electrical and electronic courses,the class teaching,the practical teaching and the independent learning are discussed. The innovative method which can assists students’learning by using Proteus simulation software,realizes the the link from theory to practice for electrical and electronic courses.Taking the experimental proj ect of integrated DC regulated power supply as an example, the specific process of Proteus aided experimental teaching is illustrated. The simulation experiment is beneficial to students’practical ability.And their interest of learning has been enhanced.A solid foundation for the follow-up study of theory and practice has been built.

The function block model and configuration technology were studied. A method of function block instantiation is advanced in allusion to the problem that the number of function block is fixed. At the same time, the parallelism was employed for the schedule of function blocks. And the advantages in the complex control system were analyzed. The study has practical significance to engineering application.