CLADDING TECHNOLOGY SHANXI CO., LTDPressure-Flow Composite Control Characteristics of Independent Load Hydraulic System Based on Two-Level Fuzzy Controller
Literature Overview
This paper investigates the pressure-flow composite control characteristics of an independent load hydraulic system employing a two-level fuzzy controller. Independent load hydraulic systems are critical components in heavy machinery, including hydraulic press brakes, injection molding machines, and hydraulic support systems used in mining operations. The control of both pressure and flow simultaneously presents significant challenges due to the nonlinear, time-varying, and coupled nature of hydraulic systems. The two-level fuzzy controller architecture proposed in this paper addresses these challenges through hierarchical control logic that separates pressure regulation from flow regulation while maintaining system stability.
Core Technical Architecture
Two-Level Fuzzy Controller Structure
The controller architecture consists of two hierarchical levels:
- Upper level (pressure control): Regulates system pressure to match the load demand, ensuring energy efficiency by avoiding unnecessary pressure buildup.
- Lower level (flow control): Regulates pump displacement or valve opening to achieve the required flow rate for actuator motion.
- Coupling mechanism: Information exchange between levels ensures coordinated operation without instability.
Fuzzy Logic Implementation
| Component | Description | Implementation Details |
|---|---|---|
| Fuzzification | Conversion of crisp inputs to fuzzy sets | Triangular membership functions |
| Rule base | Control rules based on expert knowledge | 49 rules (7×7 rule matrix) |
| Inference engine | Fuzzy reasoning using Mamdani method | Min-max composition |
| Defuzzification | Conversion of fuzzy outputs to crisp values | Center of gravity method |
| Input variables | Pressure error, flow error, rate of change | Normalized to [-1, +1] |
| Output variables | Pump displacement command, valve position | Mapped to actuator range |
System Dynamics and Control Challenges
The independent load hydraulic system exhibits several challenging dynamic characteristics:
| Characteristic | Description | Control Challenge |
|---|---|---|
| Nonlinearity | Hydraulic component nonlinearity | Fixed-gain controllers perform poorly |
| Time-varying parameters | Temperature-dependent fluid properties | Adaptive control required |
| Coupling | Pressure-flow interaction | Decoupling strategy needed |
| Load disturbance | Variable external loads | Disturbance rejection required |
| Hysteresis | Valve and pump hysteresis | Compensation needed |
| Dead zone | Valve dead zone at low flows | Minimum flow management |
Performance Comparison
The following table compares the control performance of the two-level fuzzy controller with conventional control strategies:
| Performance Metric | PID Controller | Single-Level Fuzzy | Two-Level Fuzzy |
|---|---|---|---|
| Pressure settling time | 0.8–1.2 s | 0.4–0.6 s | 0.2–0.3 s |
| Flow settling time | 1.0–1.5 s | 0.5–0.8 s | 0.3–0.4 s |
| Pressure overshoot | 15–25% | 5–10% | 2–5% |
| Flow overshoot | 20–30% | 8–12% | 3–6% |
| Steady-state error | 2–5% | 0.5–1.5% | <0.5% |
| Energy efficiency | Baseline | 10–15% improvement | 15–25% improvement |
| Robustness to load changes | Poor | Good | Excellent |
Application to Hydraulic Support Systems
In my engineering practice with hydraulic support systems for mining applications, the pressure-flow composite control is directly relevant to the following scenarios:
- Crawler support advancement: Precise pressure control during roof support advancement requires simultaneous management of lifting pressure and hydraulic fluid flow to prevent sudden roof movements.
- Mining face advance: The control of hydraulic cylinders during face advance operations requires coordinated pressure and flow management to ensure smooth, controlled movement without damaging the roof or floor strata.
- Emergency response: During roof falls or equipment failures, the hydraulic system must respond rapidly with precise pressure and flow control to prevent catastrophic failures.
- Energy management: During periods of low demand, the system must reduce pump displacement while maintaining pressure control to minimize energy consumption and hydraulic fluid heating.
Hydraulic System Parameters
| Parameter | Typical Value | Design Consideration |
|---|---|---|
| System pressure | 31.5–40 MPa | Mining support standard |
| Pump displacement | 0–200 mL/rev | Variable displacement pump |
| Flow rate | 0–63 L/min | Matched to cylinder speed |
| Hydraulic fluid | ISO VG 46 | Temperature stability |
| Cylinder bore | 160–280 mm | Load capacity |
| Cylinder stroke | 500–1000 mm | Support height range |
| Response time | <0.5 s | Safety requirement |
| Temperature range | -20°C to +60°C | Operating environment |
Control Stability Analysis
The stability of the two-level fuzzy controller is analyzed through:
- Bode plot analysis: Gain margin > 6 dB, phase margin > 45° across operating range.
- Nyquist criterion: Enclosure count verification for closed-loop stability.
- Sensitivity analysis: Robustness to parameter variations within ±20% of nominal values.
- Disturbance rejection: Step disturbance response with settling time < 0.5 s.
Study Insights and Reflections
The two-level fuzzy controller architecture represents a practical solution to the fundamental challenge of hydraulic system control — managing multiple interacting variables simultaneously without requiring precise mathematical models of the system. Traditional PID controllers struggle with the nonlinear, coupled dynamics of hydraulic systems, while model-based controllers require detailed system identification that is impractical for field applications.
The hierarchical separation of pressure and flow control into distinct fuzzy logic levels provides an intuitive control structure that mirrors the physical behavior of the hydraulic system. Pressure control at the upper level ensures energy efficiency by matching pump output to load demand, while flow control at the lower level ensures precise actuator positioning. This separation simplifies the control design while maintaining system performance.
For engineers working with hydraulic systems in heavy industry, the key takeaway is that fuzzy logic controllers offer a practical path to improved performance without requiring the complex system identification and model development associated with modern control theory. The two-level architecture provides a structured approach to implementing fuzzy control that can be adapted to specific system requirements through modification of the rule base and membership functions.
The energy efficiency improvements demonstrated in this work are particularly significant for mining support systems, where hydraulic pumps operate continuously and represent a major energy consumption component. The 15-25% energy savings achieved through intelligent pressure-flow control translate directly to reduced operating costs and extended equipment life.