This study focuses on a hydraulically driven manipulator for disposing of explosives and other hazardous materials. A mathematical model of this manipulator is established using fuzzy control technology, and its automatic control is investigated. Simulation and experimental results show that the fuzzy control system of this manipulator not only possesses good dynamic and static performance but also exhibits strong robustness. Furthermore, the manipulator demonstrates excellent adaptability in complex terrain environments.
1. Introduction
The explosives disposal robot studied in this paper is a mechatronic device designed to perform specific tasks such as explosives disposal and effective obstacle removal. It is primarily used for unexploded ordnance, oil tanks, or other explosives in identified locations, and can also be used for clearing surface obstacles. It has wide applications in public security, fire departments, and other sectors. Furthermore, it can be used by troops in field conditions to clear landmines and unexploded ordnance, effectively improving the mobility of troops in modern warfare.
For example, when a bomb disposal robot locates an explosive device in a known position, the highly uncertain geographical environment poses significant challenges to control. Therefore, it is crucial to select an appropriate control strategy as quickly as possible to dispose of the explosive. This paper employs fuzzy control, utilizing human experience, skills, and direct reasoning without relying on a precise mathematical model of the controlled object. This approach exhibits strong adaptability, satisfies control performance requirements, and enables automatic control of the bomb disposal robot.
Table 1 Control Rules Table Table 2 Lookup Table2. Fuzzy Control Algorithm
Let the error E and its change EC be the input language variables, and the voltage signal u output by the computer be the output language. The quantization universes of variables E, EC, and U are respectively:
The language values for E, EC, and U are as follows:
The membership functions of E, EC, and U are selected from the normal distribution. Based on practical experience in operating the robot, a set of control rules consisting of 52 fuzzy conditional statements is derived:
The 52 Fuzzy conditional statements mentioned above are summarized to establish a fuzzy control rule table, as shown in Table 1. Fuzzy inference composition rules and the maximum membership method are applied, and after experimental correction, a fuzzy control lookup table is established, as shown in Table 2.
During the control process, the real-time acquired error e(k) and the calculated error change ec(k) are multiplied by quantization factors, respectively. This yields a lookup table representing the corresponding universe of discourse elements. The lookup table contains the required E <sub>ki</sub> and EC <sub>kj</sub> . From the lookup table, the control quantity change U <sub>kij </sub> corresponding to E <sub>ki</sub> and EC<sub>kj</sub> is obtained. Multiplying U<sub> kij</sub> by the scaling factor ku ( ku = Δu<sub> max</sub> / 6) gives the actual control quantity change value applied to the control process at each time step, i.e., Δu<sub> k</sub> = ku × U<sub> kij</sub> .
3. Theoretical Model
This paper uses electro-hydraulic proportional technology to control a mine-clearing robot. However, a drawback of electro-hydraulic proportional valves is the existence of a dead zone. Therefore, the dead zone must be compensated for during control. This paper selects a static compensation method, namely...
(1)In the formula: is the actual voltage value acting on the electro-hydraulic proportional valve; is the voltage value output by the fuzzy controller. The schematic diagram of the control system for the bomb disposal manipulator is shown in Figure 1.
Figure 1. Schematic diagram of fuzzy control principle for bomb disposal robot.The controlled system in Figure 1 is a proportional hydraulic system controlled by an electro-hydraulic proportional valve, and its state equation and output equation are as follows:
(twenty three)In the formula: y<sub>x</sub> represents the state variable; A is a 6×6 coefficient matrix; B is a 6×2 coefficient matrix; C is a 1×6 coefficient matrix; x and f are the given input and disturbance input of the controlled object; y<sub>x</sub> and y<sub>f</sub> are the outputs of the controlled object under the given input and disturbance input.
In the formula: Ku is the proportional coefficient of the electro-hydraulic proportional valve; Kf is the feedback signal gain; Kce is the total flow-pressure coefficient of the proportional valve; is the natural frequency of the system; is the damping ratio of the system; is the equivalent bulk modulus of the hydraulic oil; A is the effective area of the piston of the manipulator cylinder.
4. Experimental Research
4.1 Test System
The bomb disposal robot uses electro-hydraulic proportional control. A computer controls the telescopic cylinder and the finger opening and closing cylinder through two electro-hydraulic proportional valves to complete the robot's digging and grasping operations. Figure 2 is a schematic diagram of the experimental system.
Figure 2. Block diagram of the computer control system.4.2 Test Results
The aforementioned fuzzy controller was experimentally studied on a robotic arm testing device. Figures 3 and 4 show the step response curves of the finger joints and extension joints when using the conventional PID control method, respectively. Figures 5 and 6 show the step response curves of the finger joints and extension joints when using the fuzzy control method, respectively. The finger joint opening ranged from 0 to 12.5 cm, and the extension of the extension joint ranged from 0 to 15.0 cm. The experimental results are shown in Table 3.
As can be seen from the control performance indicators of the two control strategies in Table 3, the fuzzy control method gives the control performance good dynamic quality and steady-state accuracy.
Figure 3. Step response curve of finger joint Figure 4. Step response curve of telescopic joint Figure 5. Step response curve of finger joint Figure 6. Step response curve of telescopic joint Table 3. Comparison of PID and Fuzzy control performance of robotic arm5. Conclusion
This paper establishes a mathematical model of a bomb disposal manipulator using fuzzy control theory and studies its automatic computer control. During the experiment, the fuzzy control algorithm established in this paper and the conventional PID control method were compared. The results show that the fuzzy control system of the bomb disposal manipulator not only has good dynamic and static performance but also strong robustness. This makes the manipulator more adaptable to the disposal of explosives in harsh environments or the removal of landmines or obstacles in field conditions.
