To address the problem of the sparrow search algorithm (SSA) has poor global search ability, weak local development ability, and easily falls into the local optimal solution, a multi-strategy improved evolutionary sparrow search algorithm (MSSA) is proposed. The introduction of the tent chaotic map improves the diversity of the initialization population, accelerates algorithm convergence, and improves convergence accuracy. Endow sparrow finders with a random search ability to coordinate the balance between global search and local development. To discover dangerous sparrow individuals, the mutation evolution operation is completed, and a greedy strategy is combined to improve the processing ability of the algorithm for local optimal solutions and make full use of each sparrow individual. Six benchmark functions were used to comprehensively verify the feasibility of the proposed algorithm based on four aspects: optimization ability, robustness, convergence ability, and optimization trajectory. These results indicate that the proposed algorithm is superior. Finally, through the comparison and analysis of the parameter identification and control strategies of the two servo systems in practical application, on the one hand, the advantages of the proposed algorithm in practical engineering applications are illustrated. In addition, a fuzzy PID control strategy based on MSSA is proposed. By adding step, sinusoidal, triangular wave and disturbance signals, simulation experiments show that the control strategy can significantly improve the dynamic and steady performance of the servo system.
In a high-precision servo system, the nonlinear friction link is the key factor affecting the system performance. Reasonable solving of the friction link in servo systems has become a focus of current research. This paper summarizes the friction nonlinearity that affects the control performance of servo systems. First, the characteristics of friction are summarized, and the advantages and disadvantages of typical friction models in recent years are analyzed. Subsequently, existing friction model parameter identification methods are introduced and evaluated. On this basis, the development level of the friction nonlinear control strategy is analyzed from three aspects: friction model-based control, friction model-free control, and compound control. Finally, the objective advantages and disadvantages of the existing technology are summarized, and the future development direction of the friction model and selection reference for the nonlinear friction control strategy are comprehensively discussed.
Aiming at the multi-parameter identification problem of an electro-hydraulic servo system, a multi-parameter identification method based on a penalty mechanism reverse nonlinear sparrow search algorithm (PRN-SSA) is proposed, which transforms the identification problem of a non-linear system into an optimization problem in a high-dimensional parameter space. In the initial stage of the sparrow search algorithm (SSA), the population distribution is not uniform, and the optimization process is easily disturbed by the local optimal solution. First, adopting a reverse learning strategy increases the exploratory nature of individuals in a population, improves population diversity, and prevents premature maturity. Subsequently, a flexible strain mechanism is provided through the nonlinear convergence factor, adaptive weight factor, and golden sine and cosine factor. The introduction of a nonlinear factor fully balances the global search and local development abilities of the algorithm. Finally, a punishment processing mechanism is developed for vigilantes while retaining the population, providing a suitable search scheme for individuals beyond the boundary, and making full use of the value of each sparrow individual. The effectiveness of each improved strategy is verified through simulation experiments with 23 benchmark functions, and the improved algorithm exhibits better robustness. The results of the model parameter identification of the electro-hydraulic servo system show that the method has a high fitting accuracy between the identification model data and the experimental data, and the fitting degree of the identification model exceeds 97.54%, which further verifies the superiority of the improved algorithm and the effectiveness of the proposed identification strategy.
The nonlinearity of clearance has a significant influence on the performance of a system while ensuring the reliability of the variable-speed transmission, and hinders the development of the controlled object according to the predetermined trajectory. Aimed at the transmission clearance problem in different systems, this study summarizes the existing literature and provides a reference for the research and compensation of clearance characteristics. First, the influence of clearance on system performance is analyzed and summarized, and it is shown that the existence of clearance causes problems, such as system response delay and limited cycle oscillation. Then, the control strategies for studying clearance are introduced, which are mainly divided into the control strategy based on the clearance model and the non-clearance model control strategy, and these are respectively explained. Finally, some opinions are proposed for the perfection and development of future clearance nonlinear control theory. Ideas for realizing the suppression of the adverse effects of clearances have their characteristics, and in practical applications, the difficulty of implementation and cost control should be comprehensively considered. In the future, to cope with complex and changeable environments, the clearance control strategy will continue to be optimized.
Background: ADRC (active disturbance rejection controller) technology is a new practical technology that does not rely on the mathematical model of the controlled object and has strong robustness. It integrates the essence of modern control theory and classical proportion integral derivative theory, and has good engineering application prospects. But with the research and development of the adaptive disturbance rejection controller, the problem of many parameters and difficult to adjust also arise. Objective: To act as a guide for future studies on the enhancement of ADRC parameter setting, to support the growth of ADRC technology, and to promote the effective use of the technology in other control fields. Method: The basic concepts and principles of ADRC control, the research methodologies for ADRC parameter tuning, and the research progress for ADRC parameter tuning in each direction are all introduced in this paper. The benefits and drawbacks of each method are then compiled, and a potential course of future development is suggested. This information is expected to serve as a guide for future studies on the enhancement of ADRC parameter tuning. Conclusion: The parameter tuning of the ADRC is a complex adjustment process. At present, the mainstream parameter tuning methods include the empirical method, the bandwidth method, the intelligent algorithm tuning method, and the time scale tuning method. Among them, the empirical method demands the debugging personnel to adjust conform to the accumulated experience, and the adjustment process is cumbersome; The bandwidth method needs to go through a lot of tedious calculations to determine the control parameters according to the model of the system, and the generality is poor; and the use of intelligent algorithms to tune ADRC parameters has become the most widely used method for tuning parameters.
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