Researches On Boom Telescopic Path Planning And Counterweight Mechanism Control Techonologies Of All-Terrain Crane

All-terrain cranes are the high-end produces amony cranes with complex technology,high safety and reliability requirements.The research on optimization and control technology of all-terrain cranes has a certain forward-looking and enlightening for the whole series of crane products and even the construction machinery industry.In this thesis,the algorithm of Telescoping Path Optimization(TPO)of Single-cylinder Pin-type Multi-section Boom(SPMB)and techonology of PID parameters adaptive tuning and control are studied,and they are applied to the telescopic boom length changing planning and counterweight lifting mechanism synchronous follow-up control.The multi-stage telescopic boom of an all-terrain crane adopts a SPMB mechanism to extend and retract the boom sections,while the SPMB is inefficient in changing the boom length.The TPO of SPMB refers to the minimum number of telescopic steps and the shortest total travel strokes of single cylinder required to extend from initial position to targe position of the SPMB changing boom length.This thesis puts forward the TPO problem,and conducts a systematic study.The mathematic description of the TPO problem is carried out,and the mathematical model is established.Two enumeration algorithms are invented:channel flow valve method and permutation&combination method.The dynamic programming method is applied to optimize small-scale TPO.Hopfield neural network(HNN)is applied to TPO calculation.A PID adaptive penalty parameter adjustment strategy based on constrained basis control is proposed to guide the network convergence toward the global optimum.An efficacy factor strategy is proposed to balance the conflict between the constraint parameter?and the objective parameter?.Thereby the network quality of HNN is improved,and the valid solution generation is increased.After the improvement of the two strategies,the valid solution generation rate was increased from 40%to more than 90%;the optimal solution generation rate was increased from 10%to 30%.Genetic algorithm(GA)is applied to TPO calculation.A general algorithm of computing large-scale and complex TPO problems is constructed.Aiming at the linear constraint characteristics of the TPO,an adaptive penalty function strategy based on the gravity center of the constraint biases is proposed to calculate the individual fitness of algorithm.Compared with the other two general penalty function strategies,the TPO penalty function strategy has better robustness and better solution quality.Comparating the four TPO algorithms,it is concluded that after path optimization,the telescopic efficiency of SPMB can be increased 10%?40%.For small-scale and simple TPO problems with a small number of boom sections and simple boom structures,permutation&combination algorithm has advantages.For large-scale and complex TPO problems with a large number of boom sections and complex boom structures,Both GA and HNN have their own advantages.The hoisting mechanism,counterweight mechanism,and boom telescopic mechansim with luffers of all-terrain crane are all large-load systems connected by wire ropes,and have synchronization control requirements.The controlled object is a flexibly connected large inertial load.Its lateral vibration is similar to a pendulum motion,which is difficult to stop once excited.The longitudinal vibration is interfered by a variety of sesmic sources,in an environment where multiple vibrations are superimposed,frequent control and adjustment is easy to excite resonance.The poor synchronization of mechanism movement and resonance caused during operation are major safety hazards to large and giant machinery and equipment.In addition,the load weight of mechanism changes with the working conditions,from a few tons to thousands of tons,that is,the controlled object is variable parameter system.Therefore,synchronous control has higher requirements for accuracy,speed,motion stability and variable parameter adaptability.In this thesis,the synchronization control of counterweight lifting mechanism is studied.Firstly,the mathematical model of counterweight lifting mechanism is established based on the valve-controlled asymmetric cylinder system.Meanwhile,the system identification method is used to fit the transfer function of the counterweight system,and the mathematical model of the closed-loop control system is deduced.In order to ensure the control stability,according to Hermite-Biehler theorem,the PID parameter stability domain of the closed-loop control system is calculated,and the PID parameter ranges of are determined when the system is stable.Most of the existing PID tuning method are offline optimization,which is difficult to use for online control.However,the offline tuning process is cubsome and the tuning result may not be ideal for the actual system.In order to solve the problem of parameter online tuning and control instability,the concept of linear-like relationship between the optimized parameter and the performance indicator is proposed,and introduced into objective functions,so as to establish the linear-like relationships between initial parameters K_p0,K_i0,K_d0 and error;incrementsK_p,_iK,K_dand error,error integral,error differential.Based on expert knowledge and gradient increment principle,the sign rules of PID parameter increments are derived.A set of PID parameters adaptive tuning and control methods are proposed.The parameter adaptive tuning controller can realize the servo tracking of the model-free control system,and the controller only requires system input and output signals.This method can avoid the problems that the PSO algorithm is easy to stagnate at the local optimum which is instantly found,and the output instability caused by parameter drastic regulations in the existing online tuning methods.On the Simulink plateform,a variety of controllers were used to test the responses of typical signals:step,ramp and sine;meanwhile,signal response experiments were carried out by using the optimal controller for the modeled system.The results show that the parameters adaptive tuning controller has better response performance than fixed parameter PID controller and fuzzy PID adaptive controller,and its performance indicators such as overshoot,response time,adjustment time and steady-state error all have advantages;meanwhile,the optimal controller with adaptive parameter tuning can obtain further performance improvement than the optimal controller with fixed parameters.The AMESim mechanical and hydraulic system model and Simulink control system model were constructed,and the co-simulation experiment were carried out on the synchronous control of large counterweight lifting system.Two kinds of asynchronous conditions were simulated:the first one was that one side cylinder has internal leakage and the other side cylinder is normal;the second one was that the pilot pressure differences of the balance valves on both sides are inconsistent.The results show that the parameters adaptive tuning controller based on model-free system has good synchronization following performance,motion stability and wide parameter adaptability.Finally,a real vehicle test was carried out on the TPO of the SPMB and the synchronous lifting control of the large counterweight.The test results verified the correctness of the theoretical calculation and simulation results.The research contents and theoretical methods of this thesis can be applied to engineering practice,and some technologies have been industrialized.The research of this thesis can provide a certain reference for the intelligent research and development of crane machinery and related industry equipment.