Study Of Sliding Mode Control Method For Trajectory Tracking Of Condenser Cleaning Robot

Condenser is a large heat transfer equipment in the power, chemical, machinery and other industries. It is one of the key equipments in thermal power plant and It is the cold source of the thermodynamic cycle of the large steam turbine. Good or bad performance of its work will directly affect the economics and safety of the entire steam turbine . However, in the course of their work will always have some fouling inside the condenser, which will produce a series of harm. To solve the problem, there are some fouling cleaning methods . In recent years, Condenser cleaning robot is the new technology of domestic which is proposed. In this paper, two joints fixed condenser cleaning robot is as the main object of study,its trajectory tracking method of sliding mode control method has been studied:Firstly,the cause of fouling accumulation and the influence on heat transfer performance of condenser is investigating. Then the advantages and disadvantages of general fouling cleaning methods are summarized. The paper review the status of control method for trajectory tracking of robot .Secondly, the paper introduce the structure of condenser cleaning robot, its mathematical models and knowledge of the relevant mathematical is given . Described in detail the principle of sliding mode variable structure control, characteristics. Sliding mode controller is design to solve the problem of uncertainties which are appeared in the process of robot work. In conventional sliding mode control, chattering is more serious. To solve the problem, a neural network sliding mode controller is designed. RBF neural network (RBFNN) is used to approximate system dynamic and elimination errors of model. The chattering is weakened effectively. In the neural network sliding mode control, value of control gain is estimated. In order to guarantee the stability of the system and reach the sliding mode fast, it is always large .But the value is too large and it may also cause system chattering. Therefore it is improved. The sliding mode control gain is adjusted by the adaptive fuzzy systems to compensate the network approximation error and the external disturbances. And the chattering is reduced. Dual-loop control is good for position and speed tracking . This paper design a RBFNN based double-loop integral sliding mode controller and it is good tracking of targets. External disturbances are considered as part of the system uncertainties in this article. And a RBFNN is used to adapt to close to the system uncertainties which can reduce the impact of uncertainty of the system.Finally in order to verify the validity of the proposed algorithm, use MATLAB to simulate. And the results of simulation are show that the algorithms are feasible and effective.