In this post, we delve into the design and implementation of a Proportional-Integral-Derivative (PID) controller using Field-Programmable Gate Arrays (FPGA). PID controllers are fundamental in control systems for maintaining an expected output despite various external changes. FPGAs, with their parallel processing capabilities, offer an excellent platform for implementing these controllers to achieve real-time performance.
Design
The PID controller algorithm adjusts a control input to bring a system’s output to its desired setpoint. It consists of three parameters: Proportional (P), Integral (I), and Derivative (D), which work together to minimize the error over time. In an FPGA, we can implement this using hardware description languages like VHDL or Verilog, which allow precise timing and parallel execution, critical for real-time applications.
Specifications
- Error Signal (e): Difference between the setpoint and the measured value.
- Proportional Term (P): Directly proportional to the error.
- Integral Term (I): Accumulation of past errors.
- Derivative Term (D): Predicts future errors based on the rate of change.
We’ll use Verilog for our implementation, due to its widespread use and suitability for describing hardware behavior.
Implementation
Here’s a simplified version of the PID controller in Verilog:
module PID_Controller(
input wire clk,
input wire reset,
input wire [15:0] setpoint,
input wire [15:0] measured_value,
output reg [15:0] control_signal
);
reg [31:0] error;
reg [31:0] integral;
reg [31:0] derivative;
reg [15:0] previous_error;
// PID coefficients
parameter Kp = 3.14;
parameter Ki = 1.59;
parameter Kd = 0.20;
always @(posedge clk or posedge reset) begin
if (reset) begin
integral <= 0;
derivative <= 0;
previous_error <= 0;
control_signal <= 0;
end else begin
error = setpoint - measured_value;
integral = integral + error;
derivative = error - previous_error;
control_signal = Kp*error + Ki*integral + Kd*derivative;
previous_error = error;
end
end
endmodule
Notice the always block is triggered on a positive edge of the clock or reset. It calculates the error, integral, and derivative terms based on the current and previous measurements, then computes the control signal using the PID formula.
Debugging
During the simulation phase, several issues were noted:
- Overflow: The integral term can overflow if not managed properly. Solution: Implement an anti-windup mechanism.
- Noise Sensitivity: The derivative term is sensitive to measurement noise. Solution: A filtering mechanism was added to the derivative calculation.
Results
After implementing the suggested fixes and running multiple simulations, the PID controller showed excellent performance in tracking the setpoint changes accurately with minimal overshoot and stable behavior.
Conclusion
FPGA-based PID controllers are ideal for real-time applications requiring rapid and precise control adjustments. This walkthrough not only demonstrates the basic implementation but also highlights common pitfalls and their solutions in a real-world scenario. By leveraging the concurrent processing capabilities of FPGAs, we can achieve more efficient and faster control systems that are robust against various operational challenges.