Nonlinear Multi-Body Dynamic Modeling and Coordinated Motion Control Simulation of Deep-Sea Mining System

Deep-sea manganese nodules are abundant in the ocean, with high exploitation potential and commercial value, and have become mineral resources that coastal countries compete to develop. The pipeline-lifting mining system is the most promising deep-sea mining system at present. A deep-sea mining vehicle is the core equipment of this system. Mining quality and efficiency rely on mining vehicles to a great extent. According to the topographic and geomorphic environmental characteristics of deep-sea manganese nodules at the bottom of the ocean, a new deep-sea mining system based on an autonomous manganese nodule mining vehicle is proposed in this paper. According to the operating environment and functional requirements of the seabed, a new mining method is proposed, and the global traverse path planning research of the autonomous manganese nodule mining vehicle based on this mining method is carried out. The arc round-trip acquisition path planning method is put forward, and the simulation verification shows that the method effectively solves the problems of low efficiency of mining vehicle traversing acquisition and obstacle avoidance.

As a kind of mobile robot, the intelligent trolley is also called a wheeled robot, and this field is the fastest growing in the current technological development. Smart trolleys have good automatic guidance functions, often used in modern logistics conveying systems. A fuzzy control algorithm has a good control effect for nonlinear systems and has a strong anti-interference ability. In order to optimize the multi-objective longitudinal following system of smart carts, therefore, this paper develops the study of fuzzy PID control algorithm for multi-objective longitudinal following of smart carts. Based on the incremental PID control, an improved PID algorithm is constructed by introducing incomplete differentiation, differential prior, and “optimal curvature” algorithm. Based on the actual control experience, the fuzzy control table is designed, and the adaptive control algorithm is obtained. Finally, the simulation results of the fuzzy PID control algorithm are tested by MATLAB/Simulink, and the most suitable fuzzy PID control algorithm for multi-objective optimal longitudinal following of intelligent carts is derived.

Solving the path-tracking problem of vehicles is a key part of realizing intelligent transportation. The four-wheel- independent-steering (4WIS) electric vehicle (EV) with steer-by-wire (SBW) has the advantages of good controllability, low speed maneuverability and high speed stability, which is beneficial to improving the path tracking performance. In this paper, a novel 4WIS electric vehicle is proposed and the path tracking control research was carried out on it by using the adaptive fuzzy PID algorithm. Firstly, the four-wheel steering strategy was analyzed, and the geometric relationship between the front and rear steering angle when the vehicle's centroid angle is zero was derived. Furthermore, based on the principle of adaptive fuzzy PID control and the single-step heading prediction algorithm, a path-tracking controller was designed for the self-built 4WIS EV. A Simulink/Carsim co-simulation platform was built, on which the simulation was carried out at different condition, and the simulation results show that the designed adaptive fuzzy PID controller has good path-tracking performance and strong robustness. Finally, the serpentine trajectory and the double lane change (DLC) trajectory are taken as the reference trajectory, and the reliability and robustness of the designed adaptive fuzzy PID control algorithm were verified on the open road. The results show that the adaptive fuzzy PID control algorithm has good tracking performance and is far superior to pure PID control.

With the development of wind power technology in recent years, wind power technology has made rapid development. In this paper, the wind farm is the main object of study, the energy storage elements is vanadium redox flow battery (VRB), the use of decoupling control of fuzzy PID control algorithm for real-time changes in PID parameters of the active and reactive power. The outer loop of motor side rectifier is power loop, the inner is current loop. The outer loop of grid side inverter is the voltage loop, the inner is current loop, and based on vector control, the rectifier and inverter achieve decoupling process.The traditional PID is poor in anti-interference ability and robustness,so this paper uses the fuzzy PID control algorithm. The MATLAB/simulation results show that the fuzzy control algorithm can achieve power tracking control,and has strong robustness.

A typical and may be the most prospective deep ocean mining system is an integration of a mining ship system, a hoist pipeline system and a self-propelled seafloor miner system. According to this representative system configuration, China has designed and developed a deep ocean mining pilot system. In order to evaluate and improve the design of the pilot system, and further to provide technical references for the practical system operation, dynamic simulation models of the subsystems and the total integrated system are developed. For the seafloor miner, a multi-body model with the scale of 1:1 to the actual size of the pilot miner is built, which can be used effectively to perform detailed design, analysis and optimization of the miner system. Meanwhile, to make the integration of the total mining system possible, a simplified 3D single-body model with 6 DOF of the miner is also developed, which is capable of real-time simulation and can be easily integrated with other subsystems. For the pipeline system including the rigid lifting pipe, submerged pump, buffer storage and flexible hose, finite element method (FEM) and discrete element method (DEM) are all proposed and developed. With the FEM model, the towing mining operation process, as well as the launching and retrieval process, can be analyzed. Whereas, the DEM model is preferred to perform the dynamic analysis of the total integrated mining system due to its relative high computation efficiency compared with that of the FEM model. To realize the dynamic analysis of the total integrated mining system with relative high efficiency and accuracy, the single body model of the miner and the DEM model of the pipeline are chosen to be integrated to form the total system and perform dynamic analysis, which in a way can provide specific guidance and suggestions for the practical deep ocean mining system analysis, operation and control. For further researches, more attention will be focused on the analysis of the launching and retrieval operation process of the total mining system, including the water entry of the miner, the launching process of the pipeline system and the final seafloor-touchdown of the miner.

The paper designs a high power DC motor closed-loop control system, mainly including design of H bridge drive circuit, speed detection circuit and signal conditioning circuit. In order to improve the performance of motor running, one proposes a fuzzy adaptive PID control algorithm. Firstly, one determines the degree of membership of the input values to defined fuzzy sets, then constructs the fuzzy rule table according to experience and experiments, finally, makes defuzzification for every parameter of PID controller, that is, Kp, Ki, Kd. Experiments show that both hardware implementation and software control algorithms are reliable, the running performance of the system is robust before or after adding load.

To improve solar energy utilization efficiency, address control precision issues in solar panel tracking systems, and strengthen the sustainable supply capacity of clean renewable energy, this study proposes an innovative variable universe fuzzy adaptive PID control algorithm for high-precision solar tracking systems. Based on this algorithm, a fusion scheme combining a high-precision four-quadrant detector and GPS positioning is employed to achieve real-time and precise positioning of the tracking system. The azimuth and elevation angle deviations between the real-time solar rays and the system’s actual position are calculated and used as input signals for the tracking control system. These deviations are dynamically corrected by the variable universe fuzzy adaptive PID controller, which drives a stepper motor to achieve high-precision solar tracking. The results demonstrate that, under ideal operating conditions, the proposed algorithm reduces the steady-state error by 3.5–4.9°, shortens the settling time by 4.4–5.8 s, decreases the rise time by 0.6 s, lowers the overshoot by 18–19%, and reduces the disturbance recovery time by 1.3 s. These improvements significantly enhance tracking accuracy and dynamic response efficiency. Under complex operating conditions, the algorithm reduces the steady-state error by 3.2–5.9°, shortens the settling time by 5.4–6.2 s, decreases the rise time by 0.7 s, lowers the overshoot by 17.5–19%, and reduces the disturbance recovery time by 1.5 s, thereby ensuring stable and efficient solar tracking and maintaining continuous energy capture. By quantitatively optimizing multiple performance metrics, this algorithm significantly enhances the control precision of solar panel tracking and improves solar energy utilization efficiency. It holds substantial significance for promoting the transition of the energy structure toward cleaner and more sustainable sources.

Focusing on strong nonlinearity and time variation of switching-inverter power, this paper presents a fuzzy adaptive PID control algorithm. This algorithm not only avoids complex modeling of the controlled object, but also combines advantages of fuzzy control and PID control. In addition, this algorithm realizes real-time and effective online control for switching-inverter power by setting parameters of PID based on fuzzy reasoning. Furthermore, the control algorithm improves steady-state precision and dynamic performance of system, either of which the PID algorithm can be realized simultaneously. A simulation model of system was made aiming at the response of unit step, constant load and cyclical load simulation. The simulation results show that the switching-inverter power based on fuzzy adaptive PID has excellent control performance and self-adjustable ability, and this controller improves the output waveform.

In hatching process, temperature, relative humidity and oxygen concentration are three main parameters to the success of the incubator. Incubation system is a multi-variable multi-interference and time delay complex dynamic system, a hybrid intelligent control method is proposed. Based on characteristics of complexity and uncertainty for its mathematical models in the hatching process, this paper will divide the system into two structures, considering of the effect of throttle opening which causes temperature and relative humidity big interference and strong coupling, feed-forward compensation decoupling control algorithm is employed for before-class structure to realize the decoupling of main parameters. After decupling, according to different conditions fuzzy immune PID control algorithm or fuzzy control algorithm is selected for back-class structure to realize incubator intelligent control. Finally, the run of system verifies the effectiveness of the control algorithm.

In the process of vegetable plug seedling cultivation, packaging, and transportation, there may be missing, unhealthy or injured seedlings in the tray, which results in a missed planting or a low seedling survival rate after automatic transplanting. In this study, a seedling selection system with the function of seedlings identification, week seedlings elimination, and missing seedlings supplement was developed for an automatic transplanter. A plug seedling identification system based on a machine vision was used to detect vegetable plug seedlings based on the area characteristics of plug seedlings, stem leaves and plug bodies. The identification results were transmitted to a programmable logic controller (PLC), which controlled a nozzle to eliminate the unqualified seedlings from the conveyor belt lattice. When the empty conveyor belt lattice reaches the seedling throwing funnel, the rear conveyor belt lattice with the plug seedling is accelerated to ensure the continuity of seedlings supply. The adaptive fuzzy PID control algorithm was used to control the stepper motor of the conveyor belt to realize accurate seedling conveying and a seedling supplement. Using 30 days pepper plug seedlings as experimental seedlings, a comparative field experiment was carried out to evaluate the performance of the seedling selection system. The results showed that when the seedling selection system was turned on and the seedling extracting frequencies were 60, 80, and 100 plants/min, the success rates of plug seedling identification were 98.84%, 98.38%, and 96.99%, and the robust seedling rates were 98.05%, 97.78%, and 95.83%. The robust seedling rates were increased by 15.64%, 16.07%, and 13.89%, respectively, in contrast to turning off the seedling selection system.

The paper realizes a design of digital fuzzy adaptive tuning PID electronic governor. It is based on VHDL description and implemented on FPGA. The paper proposes to detect the speed with duty cycle calculation and use fuzzy-control rules to amend the PID parameters on line to achieve the fuzzy adaptive tuning PID control. On this basis, the paper introduces the implementation of the system in detail, including speed detection, fuzzy logic inference, and fuzzy adaptive tuning PID algorithm. The experiment proves that digital wide-range electronic speed governor implemented on control chip FPGA can be used widely and fuzzy adaptive tuning PID control algorithm can improve the dynamic response of the system, which makes the electronic speed governor under good control in a wider work scope.

To ensure the safety and the production efficiency as well as the component lifetime of deep-sea mining system, a novel heave compensation system of deep-sea mining based on dynamic vibration absorber was proposed in the light of 5000m deep sea poly-metallic mining system of China in this paper. According to the work condition of heave compensation system, the response of deep-sea mining ship under random wave of sea state 4 in China’s deep sea poly-metallic mining field are numerically simulated in time domain. The proposed heave compensation system was simplified to a two-degree-of-freedom system stimulated by the displacement motion of the deep-sea mining ship and its dynamic model was built. Taking the minimum of the displacement variance of the proposed heave compensation system as the optimal object and considering the allowed displacement of the dynamic vibration absorber itself, the computation formula of the optimum parameters of dynamic vibration absorber for heave compensation system of deep-sea mining is derived. Thus the parameter of dynamic vibration absorber was determined and its effect on the performance index of the heave compensation system was simulated and compared. The dynamic vibration absorber with optimum parameters was simulated and tested on the test bench of double-storey mass-spring vibration system in the lab. The results of the example show that the performance of vibration control of the designed dynamic vibration absorber is satisfactory and the computational formulas given in the paper are effective. The results also verified that the heave compensator based on dynamic vibration absorber with the optimal parameters can have good performance of heave compensation and it is practical to isolate the lifting pipeline and its deployment platform from the vibration of the ship motion induced by the irregular wave with simplicity and less energy consumption. This work in the paper will be of great theoretical guidance in the optimum design of the dynamic vibration absorber for heave compensation system of deep-sea mining.

When flexible risers in the ocean are subjected to various environmental loads in the ocean, vibration will inevitably occur. Due to the nonlinearity and uncertainty of the actual riser system, it is impossible to obtain an accurate mathematical model of the riser system. The existing control algorithms designed based on the precise model of the riser system cannot meet the actual control requirements. A flexible riser boundary control method based on fuzzy control algorithm is proposed to suppress the vibration of marine flexible riser systems with uncertain models. Firstly, the dynamic models of existing marine flexible risers were studied. In response to the uncertainty of the riser system model, the control experience was transformed into an automatic control strategy in the form of fuzzy language control rules to improve the adaptability of the controller. Then, combining boundary control technology with fuzzy control, a boundary controller is constructed to stabilize the riser in a small neighborhood of its original position and reduce fatigue damage to the riser. Finally, the effectiveness of the designed fuzzy boundary control algorithm was verified through MATLAB simulation results, and the vibration suppression effect of the algorithm on the vertical tube was better than that of traditional PD control.

For a load object, the air balance compensated servo electric cylinder is used as the actuator to drive the vertical part to aim target. The nonlinear links in the super load electric cylinder servo system include the trigonometric nonlinear relationship between the pitch angle and the motor angle, the time-varying relationship between the pitch angle and the supporting torque and gravity distance of the electric cylinder, the servo system and other nonlinear links. Simply using the position PID control algorithm can not meet the tracking accuracy requirements of the system. By using the fuzzy PID control algorithm with nonlinear compensation, the tracking accuracy problem in the servo system can be effectively solved. The fuzzy PID control algorithm with nonlinear feedforward compensation is designed. The simulation and test results show that the method effectively improves the servo control accuracy.

Servo hydraulic system is important one of driving patterns of quadruped robot. While servo hydraulic system has characteristics of parameters time-varying and strong nonlinearity, so traditional PID control pattern cannot meet all the control demands well. To solve these problems, a set of control hardware is designed for a quadruped robot and a new control algorithm which can adjust PID parameters in real-time condition based on fuzzy control theory is proposed. By deducing transfer function, establishing system model and using MATLAB simulation tools to simulate the two algorithms, we compared the two algorithms and the simulation result turns out that compared with traditional PID control algorithm, the fuzzy PID control algorithm has features such as low overshoot, high stability precision, strong robustness. At the same time, the result turns out that the fuzzy PID control algorithm is much fitter for the joint control of quadruped robot.